Conference Proceeding
Refine
Year of publication
Institute
- Fachbereich Elektrotechnik und Informationstechnik (234)
- Fachbereich Medizintechnik und Technomathematik (212)
- Fachbereich Luft- und Raumfahrttechnik (183)
- Fachbereich Energietechnik (177)
- IfB - Institut für Bioengineering (148)
- Solar-Institut Jülich (110)
- Fachbereich Maschinenbau und Mechatronik (107)
- Fachbereich Bauingenieurwesen (75)
- Fachbereich Wirtschaftswissenschaften (55)
- ECSM European Center for Sustainable Mobility (53)
Language
- English (1170) (remove)
Document Type
- Conference Proceeding (1170) (remove)
Keywords
- Biosensor (25)
- CAD (7)
- Finite-Elemente-Methode (7)
- civil engineering (7)
- Bauingenieurwesen (6)
- Blitzschutz (6)
- Enterprise Architecture (5)
- Clusterion (4)
- Energy storage (4)
- Gamification (4)
- Leadership (4)
- Limit analysis (4)
- Natural language processing (4)
- Power plants (4)
- Sonde (4)
- Telekommunikationsmarkt (4)
- hydrogen (4)
- solar sail (4)
- Air purification (3)
- Associated liquids (3)
- Concentrated solar power (3)
- Einspielen <Werkstoff> (3)
- Eisschicht (3)
- Elektromagnetischer Schutzschild (3)
- Führung (3)
- Hybrid energy system (3)
- Hämoglobin (3)
- Lightning (3)
- Luftreiniger (3)
- MASCOT (3)
- Out-of-plane load (3)
- Plasmacluster ion technology (3)
- Raumluft (3)
- Shakedown analysis (3)
- Training (3)
- earthquakes (3)
- education (3)
- shakedown analysis (3)
- Additive manufacturing (2)
- Adjacent buildings (2)
- Bruchmechanik (2)
- Case Study (2)
- Clustering (2)
- Deep learning (2)
- Digital Twin (2)
- Direkter Blitzschlag (2)
- Diversity (2)
- Diversity Management (2)
- Electricity generation (2)
- Energy (2)
- Engineering education (2)
- Engineering optimization (2)
- Erneuerbare Energien (2)
- Erythrozyt (2)
- FEM (2)
- Future Skills (2)
- GOSSAMER-1 (2)
- Historical centres (2)
- Hybridsystem (2)
- Hydrogen (2)
- INODIS (2)
- IO-Link (2)
- Induzierte Spannungen (2)
- Information extraction (2)
- Innovation Management (2)
- Interdisciplinarity (2)
- Kohlenstofffaser (2)
- L-PBF (2)
- Lightning protection (2)
- Lightning protection system (2)
- Lipopolysaccharide (2)
- MINLP (2)
- Machine Learning (2)
- Magnetische Felder (2)
- Micromix (2)
- NOx emissions (2)
- Natural Language Processing (2)
- PCM (2)
- Renewable energy (2)
- Risikoabwägung (2)
- Robotic Process Automation (2)
- Seismic loading (2)
- Serious Game (2)
- Serious Games (2)
- Shake table test (2)
- Shakedown (2)
- Solar thermal technologies (2)
- Spacecraft (2)
- Stickstoffmonoxid (2)
- Stone masonry (2)
- Sustainability (2)
- Text Mining (2)
- Text mining (2)
- Trajectory Optimization (2)
- UAV (2)
- Ventilation System (2)
- Water distribution system (2)
- autonomous driving (2)
- biosensor (2)
- building information modelling (2)
- celldrum technology (2)
- combustor development (2)
- cyber physical production system (2)
- digital shadow (2)
- electro mobility (2)
- electromagnetic shielding (2)
- engineering education (2)
- fuels (2)
- industrial facilities (2)
- industrial gas turbine (2)
- installations (2)
- limit analysis (2)
- lipopolysaccharides (2)
- multiple NEA rendezvous (2)
- nitric oxide gas (2)
- piping (2)
- regulation (2)
- reinforced concrete (2)
- seismic design (2)
- seismic loading (2)
- small spacecraft (2)
- technology transfer (2)
- 10BASE-T1L (1)
- 3-nitrofluoranthene (1)
- 3D object detection (1)
- 3D printing (1)
- 3D-printing (1)
- Acceptance (1)
- Accuracy (1)
- Active learning (1)
- Adaptive Systems (1)
- Additive Manufacturing (1)
- Adsorption (1)
- Agent-based modeling (1)
- Agent-based simulation (1)
- Agile development (1)
- Agility (1)
- Aircraft design (1)
- Analytical models (1)
- Analytischer Zulaessigkeitsnachweis (1)
- Anastomose (1)
- Anastomosis (1)
- Android (1)
- Angle Sensor (1)
- Anomaly detection (1)
- Ansaugsystem (1)
- Antarctica (1)
- Arduino (1)
- Artificial Intelligence (1)
- Assessment (1)
- Asset Administration Shell (1)
- Asteroid Deflection (1)
- Attitude dynamics (1)
- Audio-visual Art (1)
- Augmented Reality (1)
- Autofluoreszenzverfahren (1)
- Automated Optimization (1)
- Automation (1)
- Awareness (1)
- BIM (1)
- BTEX compounds (1)
- Bakterien (1)
- Binder Jetting (1)
- Bio-Sensors (1)
- Biomechanics (1)
- Biomechanik (1)
- Biomedizinische Technik (1)
- Biophoton (1)
- Biosensorik (1)
- Blind prediction competition (1)
- Blitz (1)
- Blitzrisiko (1)
- Blitzschlag (1)
- Bloom Taxonomy (1)
- Breitband Markt (1)
- Building Automation (1)
- Building Systems (1)
- Bumblebees (1)
- Bundesnetzagentur (1)
- Business Engineering (1)
- Business Process (1)
- Business Process Intelligence (1)
- Business Simulations (1)
- CAD ; (1)
- CDG (1)
- CEO career variety (1)
- CFD (1)
- CO (1)
- CO2 (1)
- COMSOL Multiphysics (1)
- Camera system (1)
- Capacity Building Higher Education (1)
- Capacity Curve (1)
- Carbon Dioxide (1)
- Case study (1)
- Ceramics (1)
- Challenges (1)
- Chance constrained programming (1)
- Change Management (1)
- Cloud Computing (1)
- Cloud Service Broker (1)
- Cloud passages (1)
- Coaching (1)
- Communication (1)
- Comparative simulation (1)
- Competence Developing Game (1)
- Competence Developing Games (1)
- Computational modeling (1)
- Conducing polymer (1)
- Connected Automated Vehicle (1)
- Conpot (1)
- Control (1)
- Control engineering (1)
- Control optimization (1)
- Cooling system (1)
- Corporate Culture (1)
- Correlations (1)
- Cryptographic protocols (1)
- Customer Orientation (1)
- DC machines (1)
- DNI forecast (1)
- DNI forecasting (1)
- Data analysis (1)
- Data visualization (1)
- Database (1)
- Datasets (1)
- Dattel (1)
- Decision theory (1)
- Dekontamination (1)
- Design Thinking (1)
- Design rules (1)
- Digital Age (1)
- Digital Twin Evolution (1)
- Digital Twins (1)
- Digital transformation (1)
- Digital triage (1)
- Digital twin (1)
- Digitalization (1)
- Direct lightning strike (1)
- Direct normal irradiance forecast (1)
- Directed Energy Deposition (1)
- Discrete Optimisation (1)
- District data model (1)
- District energy planning platform (1)
- Drag (1)
- Drinking Water Supply (1)
- ECT (1)
- EEG (1)
- EN 1998-4 (1)
- EPN (1)
- ESATAN (1)
- ESHM20, industrial facilities (1)
- Earthquake (1)
- Earthquake Engineering (1)
- Education (1)
- Efficiency (1)
- Efficiency optimization (1)
- Einspiel-Analyse (1)
- Einspielanalyse (1)
- Elastodynamik (1)
- Electrical Flight (1)
- Electrocardiography (1)
- Electrochemistry (1)
- Electronic Commerce (1)
- Electronic learning (1)
- Elektrodynamik (1)
- Elektromagnetische Kopplung (1)
- Elektronische Kunst (1)
- Elicit (1)
- Emissions (1)
- Endothelzelle (1)
- Energietechnik (1)
- Energy Disaggregation (1)
- Energy Systems (1)
- Energy dispatch (1)
- Energy efficiency (1)
- Energy market (1)
- Energy market design (1)
- Energy system (1)
- Energy system planning (1)
- Engineering (1)
- Engineering Education (1)
- Engineering optimisation (1)
- Erasmus+ United (1)
- Error Recovery (1)
- Ethernet (1)
- Ethics (1)
- European Framework and South East Asia (1)
- Evolution of damage (1)
- Evolutionary Neurocontrol (1)
- Exact Ilyushin yield surface (1)
- Experimental validation (1)
- Extension fracture (1)
- Extension strain criterion (1)
- FPGA (1)
- Festkörper (1)
- Fibroblast (1)
- Field device (1)
- Finite element method (1)
- First Order Reliabiblity Method (1)
- First-order reliability method (1)
- Flame residence time (1)
- Flame temperature (1)
- Flight Mechanics (1)
- Flight Tests (1)
- Flight control (1)
- Fluorescence (1)
- Focusing (1)
- Force (1)
- Frequency Doubler (1)
- Freshmen (1)
- Fuel-flexibility (1)
- Future skills (1)
- Führungsansätze (1)
- GEO (1)
- GPU (1)
- GaAs hot electron injector (1)
- Gas sensor (1)
- Gas turbine combustion (1)
- Gasturbine (1)
- Gender (1)
- Geometry (1)
- Glass powder (1)
- Global change (1)
- Gossamer (1)
- Gossamer structures (1)
- Graph Theory (1)
- Green aircraft (1)
- Grid Computing (1)
- Guide Tube (1)
- Guidelines (1)
- Gunn diode (1)
- HVAC (1)
- Hand-on-training (1)
- Harmonic Radar (1)
- Heavy metal detection (1)
- Heliostat Field Calibration (1)
- Heliostats (1)
- Heuristic algorithms (1)
- High throughput experimentation (1)
- Higher Education (1)
- Home Assistant (1)
- Home Automation Platform (1)
- Hotplate (1)
- Human factors (1)
- Human-robot collaboration (1)
- Humidity (1)
- Hybrid Art (1)
- Hybrid Propellants (1)
- Hybrid-electric aircraft (1)
- Hybride Kunst (1)
- Hydrodynamik (1)
- Hydrogel (1)
- Hydrogen sensor (1)
- I3S 2005 (1)
- ICS (1)
- ISFET (1)
- ITS (1)
- Image Database (1)
- Image Forensics (1)
- Impedance Spectroscopy (1)
- Implementation Case (1)
- In- plane damage (1)
- In-plane (1)
- In-plane load (1)
- Incremental Encoder (1)
- Industrial Communication (1)
- Industrial facilities (1)
- Industrial optimisation (1)
- Industrieanlagen (1)
- Industry 4.0 (1)
- Inflight Regeneration, Recuperation (1)
- Information Extraction (1)
- Infused Thermal Solutions (1)
- Innovation (1)
- Instagram store (1)
- Instruments (1)
- Interaction (1)
- Interculturality (1)
- International Symposium on Sensor Science (1)
- Internet (1)
- Interplanetary flight (1)
- Isolation (1)
- Iterative learning control (1)
- Jupiter (1)
- Kalkulation (1)
- Kalman filter (1)
- Kernenergie (1)
- Key competences (1)
- Klangkunst (1)
- Knee (1)
- Knowledge Transfer (1)
- Kommunikation (1)
- Kraftwerke (1)
- Körpertemperatur (1)
- LED chip (1)
- LEO (1)
- LPBF (1)
- LQR (1)
- Labyfrinth weirs (1)
- Laminare Strömung (1)
- Laminarprofil (1)
- Large Eddy Simulation (1)
- Laser processing (1)
- Laser-Powder Bed Fusion (1)
- Latin Hypercube Sampling (1)
- Leadership Approaches (1)
- Leadership Theories (1)
- Level sensor (1)
- LiDAR (1)
- Lichtstreuungsbasierte Instrumente (1)
- Lightning Protection (1)
- Lightning Risk (1)
- Literature review (1)
- LiveLink for MATLAB (1)
- Load modeling (1)
- Low voltage (1)
- Low-Thrust Propulsion (1)
- MATLAB , MLPI , Motion control , Open Core , industrial drives , rapid control prototypin , sercos automation bus (1)
- MAV (1)
- MEMS (1)
- MEMS ; education and training foundry (1)
- MPC (1)
- Machine learning (1)
- Main sensitivity (1)
- Malaysian Automotive Industry (1)
- Malaysian automotive industry (1)
- Malicious model (1)
- Manifolds (1)
- Map (eTOM) Process reference model Process design Telecommunications industry (1)
- Market modeling (1)
- Mars (1)
- Masonry infill (1)
- Masonry structures (1)
- Matlab (1)
- Maßstabsgetreues Modell (1)
- Measurement (1)
- Measuring instruments (1)
- Mechanische Beanspruchung (1)
- Medienkunst (1)
- Melting (1)
- Micro turbine (1)
- Microreactors (1)
- Mikrogasturbine (1)
- Minimum Risk Manoeuvre (1)
- Mixed integer linear programming (MILP) (1)
- Mixed-Integer Nonlinear Optimisation (1)
- Mixed-integer nonlinear programming (1)
- Mixed-integer programming (1)
- Mobile Phones (1)
- Mohr–Coulomb criterion (1)
- Molten salt receiver (1)
- Molten salt receiver system, (1)
- Monitoring (1)
- Motivation (1)
- Mpc (1)
- Multi-agent Systems (1)
- Multi-dimensional wave propagation (1)
- Multiphase (1)
- NOx (1)
- Nano Materials (1)
- Nanomaterial (1)
- Nanoparticles (1)
- Nanopartikel (1)
- Nanostructuring (1)
- Nanotechnologie (1)
- Nanotechnology ; Microelectronics ; Biosensors ; Superconductor ; MEMS (1)
- Natriumhypochlorit (1)
- Natural language understanding (1)
- Navigation (1)
- Neo-Deterministic (1)
- Network design (1)
- Neural networks (1)
- Next Generation Network (1)
- Nichtlineare Gleichung (1)
- Nichtlineare Optimierung (1)
- Nichtlineare Welle (1)
- Nowcasting (1)
- Nozzle (1)
- Nuclear Applications (1)
- OR 2019 (1)
- Obstacle avoidance (1)
- Online services (1)
- Open Data (1)
- Open Source (1)
- Open source (1)
- Operational Design Domain (1)
- Optimal Topology (1)
- Optimization (1)
- Optimization module (1)
- Orbital dynamics (1)
- Organophosphorus (1)
- Ostazine Orange (1)
- Out-of-plane (1)
- Out-of-plane failure (1)
- Out-of-plane strength (1)
- PEM fuel cells (1)
- PFM (1)
- PHILAE (1)
- PLS (1)
- PPO (1)
- PTC (1)
- Parabolic trough collector (1)
- Parametric Design (1)
- Parametric Modelling (1)
- Path-following (1)
- Performance (1)
- Personality (1)
- Pflanzenphysiologie (1)
- Pflanzenscanner (1)
- Phenylalanine determination (1)
- Photovoltaics (1)
- Photovoltaikanlage (1)
- Piecewise Linearization (1)
- Piecewise linearization (1)
- Planetary Protection (1)
- Planetary exploration (1)
- Player Types (1)
- Position Encoder (1)
- Potentiometry (1)
- Powder Material (1)
- Power dissipation (1)
- Powertrain (1)
- Preface (1)
- Privacy-enhancing technologies (1)
- Process Model Extraction (1)
- Process design (1)
- Process engineering (1)
- Process mining (1)
- Process model (1)
- Process optimization (1)
- Process prediction (1)
- Process reference model (1)
- Profile Extraction (1)
- Profile extraction (1)
- Profilumströmung (1)
- Propeller Aerodynamics (1)
- Proteine (1)
- Prototype (1)
- Provocative Coaching (1)
- Provocative Style (1)
- Provokativer Stil (1)
- Pseudomonas putida (1)
- Pump System (1)
- Pyrometrie (1)
- Quadrocopter (1)
- Quality control (1)
- Quantum Computing (1)
- Quantum Machine Learning (1)
- Quartz crystal nanobalance (QCN) (1)
- Quartz micro balances (1)
- Query learning (1)
- RC frames (1)
- RaWid (1)
- Random variable (1)
- Rapid-prototyping (1)
- Ratcheting (1)
- Reaction-diffusion (1)
- Reference Process Model (1)
- Refining (1)
- Regulierung (1)
- Reinforcement Learning (1)
- Relation classification (1)
- Relative exploration orientation (1)
- Reliability of structures (1)
- Renewable energy integration (1)
- Renewable energy sources (1)
- Reproducible research (1)
- Rescue System (1)
- Research process (1)
- Resilience (1)
- Resilience Assessment (1)
- Resilience assessment (1)
- Resilience metric graph theory (1)
- Resilient infrastructure (1)
- Reusable Rocket Engines (1)
- Risiko (1)
- Risk (1)
- Risk Assessment (1)
- Risk Management (1)
- Rotational Encoder (1)
- Rotatory Inverted Pendulum (1)
- SME (1)
- Secure multi-party computation (1)
- Seismic (1)
- Seismic Hazard (1)
- Seismic design (1)
- Self-Leadership (1)
- Sensitivity (1)
- Sensors (1)
- Sensors comparison (1)
- Sepsis (1)
- Sequence-Search (1)
- Sharing mobility (1)
- Similarity Theory (1)
- Simulation (1)
- Skill Assessment (1)
- Sleep EEG (1)
- Small Solar System Body Lander (1)
- Small Spacecraft (1)
- Smart Building (1)
- Smart Building Engineering (1)
- Social impact measurement (1)
- Society (1)
- Software (1)
- Software Robots (1)
- Software packages (1)
- Solar Power Sail (1)
- Solar Sail (1)
- Solar irradiance (1)
- Solar sail (1)
- Solid amalgam electrodes (1)
- Solver Per- formance (1)
- Sound Art (1)
- Spacecraft Trajectory Optimization (1)
- Stahlbeton (1)
- Stahlbetonkonstruktion (1)
- Star design (1)
- Statistics (1)
- Stochastic programming (1)
- Story (1)
- Stress testing (1)
- Structural health monitoring (1)
- Structuralist Architecture (1)
- Subject-oriented Business Process Management (1)
- Suction (1)
- Support System (1)
- Supraleiter (1)
- Sustainable engineering education (1)
- Synchronous machines (1)
- System Design Problem (1)
- TGA (1)
- TICTOP (1)
- TMT composition (1)
- TMT structure (1)
- TTIP (1)
- Tag (1)
- Tanks (1)
- Teamwork (1)
- Technical Operations Research (1)
- Technische Mechanik (1)
- Technologietransfer (1)
- Technology Transfer (1)
- Telecommunication (1)
- Telecommunication Industry (1)
- Telecommunications Industry. (1)
- Temperaturmessung (1)
- Text analytics (1)
- Thermal Energy Storage (1)
- Three-dimensional displays (1)
- Throughput (1)
- Time-series (1)
- Time-series aggregation (1)
- Time-series synchronization (1)
- Tin oxide (1)
- Tobacco mosaic virus (1)
- Traglast (1)
- Traglastanalyse (1)
- Transdisciplinarity (1)
- Transformation Project (1)
- Transformative Competencies (1)
- Transiton of Control (1)
- Transponder (1)
- Triage-app (1)
- Trustworthy artificial intelligence (1)
- Typical periods (1)
- UML (1)
- UTeM Engineering Knowledge Transfer Unit (1)
- Umwelt (1)
- Uncertainty analysis (1)
- Unified Modeling Language (1)
- Unmanned Air Vehicle (1)
- Unmanned aerial vehicle (1)
- Unreinforced masonry walls (1)
- V2X (1)
- Validation (1)
- Video Game (1)
- Virtual Technology Lab (1)
- Virtuelles Labor (1)
- Virtuelles Laboratorium (1)
- Vulnerability Curves (1)
- Wafer (1)
- Wasserbrücke (1)
- Wasserstoffperoxid (1)
- Water (1)
- Water Supply System (1)
- Water supply system (1)
- Wearable electronic device (1)
- Wellen (1)
- Wiegand Effect (1)
- Windenergieanlage (1)
- Window opening (1)
- Workflow (1)
- Workflow Orchestration (1)
- Zero-knowledge proofs (1)
- acetoin (1)
- acoustic pyrometry (1)
- activated nanostructured carbon (1)
- active learning (1)
- additive manufactureing (1)
- agile (1)
- aircraft engine (1)
- aktivierte nanostrukturierte Kohlenstofffaser (1)
- ammonia gas sensors (1)
- amperometric sensor (1)
- anticipation strategy (1)
- antimony doped tin oxide (1)
- asteroid lander (1)
- asteroid sample return (1)
- autofluorescence-based detection system (1)
- avalanche (1)
- aviation application (1)
- behaviour factor q (1)
- best practice (1)
- biopotential electrodes (1)
- broadband market (1)
- business analytics (1)
- business models (1)
- business simulation (1)
- calculations (1)
- capacitive field-effect biosensor (1)
- capillary micro-droplet cell (1)
- carcinogens (1)
- catalytic decomposition (1)
- chemical reduction method (1)
- collaboration of architects and structural engineers (1)
- combustion (1)
- combustor (1)
- competence developing games (1)
- connection detail (1)
- construction (1)
- contamination (1)
- contractile tension (1)
- control system (1)
- cross sensitivity (1)
- current distribution (1)
- cyber-physical production system (1)
- cybersecurity (1)
- cytosolic water diffusion (1)
- date palm tree (1)
- decision analytics (1)
- design-by-analysis (1)
- digital economy (1)
- digital twin (1)
- digitalization (1)
- dissemination (1)
- diversity (1)
- do-it-yourself (1)
- doped metal oxide (1)
- doped silicon (1)
- doping (1)
- down-conductor (1)
- eTOM (1)
- early warning and response system (1)
- earthquake (1)
- elastomeric bearing (1)
- electrical capacitance tomography (1)
- electrically driven compressors (1)
- electro-migration (1)
- electromagnetic coupling (1)
- electromagnetic shield (1)
- electronic communications markets (1)
- electronic noses dendronized polymers inverted mesa technology (1)
- embedded hardware (1)
- emission (1)
- emission index (1)
- emote practical training (1)
- energy disspation (1)
- energy transition (1)
- engine demonstration (1)
- enhanced Telecom Operations Map (eTOM) (1)
- environment (1)
- enzymatic methods (1)
- enzyme immobilisation (1)
- enzyme immobilization (1)
- fault detection (1)
- fenitrothion (1)
- finite element analysis (1)
- finite element method (1)
- flotilla missions (1)
- flue gas components (1)
- fluid structure interaction (1)
- fluidic (1)
- food production (1)
- fragility curves (1)
- friction (1)
- friction pendulum bearing (1)
- fuel cell (1)
- fuel cell systems (1)
- gas sensor (1)
- gas sensor array (1)
- gas turbine (1)
- gender and diversity (1)
- glass (1)
- habitability (1)
- health management systems (1)
- heater metallisation (1)
- heliosphere (1)
- hemoglobin (1)
- hemoglobin dynamics (1)
- high-temperature stability (1)
- honeynet (1)
- honeypot (1)
- human digital shadow (1)
- human factors (1)
- human-machine interface (1)
- humidity (1)
- hybrid laminar flow (1)
- hybrid system (1)
- hybrid-system (1)
- hydrogel (1)
- hydrogen peroxide (1)
- ice moons (1)
- icy moons (1)
- image sensor (1)
- imaging (1)
- impedance spectroscopy (1)
- in-plane (1)
- in-plane and out-of-plane failure (1)
- induced voltage (1)
- induced voltages (1)
- information systems (1)
- innovation (1)
- integration SHM in BIM (1)
- interconnected sensor systems (1)
- interdisciplinary student projects (1)
- internal combustion engine (1)
- internet of production (1)
- ion propulsion (1)
- ion-selective electrodes (1)
- kontraktile Spannung (1)
- lab work (1)
- lab-on-a-chip (1)
- lab-on-chip (1)
- laser based powder fusion (1)
- latent heat (1)
- lattice (1)
- layer expansion (1)
- learning theories (1)
- lenslet array (1)
- liberalisation (1)
- life detection (1)
- light scattering analysis (1)
- lightning flash (1)
- limit and shakedown analysis (1)
- limit load (1)
- linear elastic analysis; (1)
- linear kinematic hardening (1)
- liquid storage tank (1)
- lockdown conditions (1)
- low-thrust (1)
- low-thrust trajectory optimization (1)
- lower bound theorem (1)
- magnetic field (1)
- magnetic fields (1)
- magnetic particles (1)
- masonry structures (1)
- material shakedown (1)
- mathematical optimization (1)
- matrix method (1)
- mechanical waves (1)
- metal façade (1)
- metal oxide (1)
- metrological characterization (1)
- microreactor (1)
- microwave generation (1)
- mobility behaviour (1)
- model-predictive control (1)
- modeling biosensor (1)
- modelling (1)
- modern constructions (1)
- modified electrode (1)
- motivation theories (1)
- multi-interface measurement (1)
- nanostructured carbonized plant parts (1)
- nanostrukturierte carbonisierte Pflanzenteile (1)
- near-Earth asteroid (1)
- next generation access networks (1)
- nitric oxides (1)
- nitrogen oxides (1)
- nonlinear kinematic hardening (1)
- nonlinear optimization (1)
- nonlinear solids (1)
- nonlinear tensor constitutive equation (1)
- open educational resources (1)
- operational aspects (1)
- organic PVC membranes (1)
- out-of-plane (1)
- overvoltages (1)
- pH-based biosensing (1)
- passive inter-modulation (1)
- passive thermal control (1)
- pattern-size reduction (1)
- perception of structures (1)
- photovoltaic system (1)
- planetary defence (1)
- plant scanner (1)
- plasma generated ions (1)
- polymer composites (1)
- porous Pt electrode (1)
- power integrity (1)
- prefabrication (1)
- principal component (1)
- probabilistic fracture mechanics (1)
- professional skills (1)
- protection measures (1)
- protein (1)
- purchase factor (1)
- quantum charging (1)
- ratchetting (1)
- reliability (1)
- remote teamwork (1)
- renewable energies (1)
- renewable energy (1)
- requirements (1)
- responsive space (1)
- rhAPC (1)
- risk assessment (1)
- risk sharing (1)
- roleplay (1)
- safety control (1)
- sample return (1)
- scaled model (1)
- screen-printing (1)
- second-order reliability method (1)
- seismic hazard (1)
- seismic isolation (1)
- seismic risk (1)
- seismic structural damage detection via SHM (1)
- seismic vulnerability (1)
- self-aligned patterning (1)
- sensing properties (1)
- sensor networks (1)
- sensors (1)
- shakedown (1)
- shopping behavior (1)
- signal integrity (1)
- simplified approach (1)
- small and medium scaled companies (1)
- small solar system body characterisation (1)
- small spacecraft asteroid lander (1)
- small spacecraft solar sail (1)
- smart building engineering (1)
- smart engineering (1)
- snow (1)
- social responsible engineering (1)
- software engineering (1)
- solar sails (1)
- solar system (1)
- space missions (1)
- star tracker (1)
- steam production (1)
- steel columns (1)
- sterilisation (1)
- storage dispatch (1)
- storage optimisation (1)
- structural equation model (1)
- structural systems (1)
- subglacial aquatic ecosystems (1)
- subroutine (1)
- subsurface ice (1)
- subsurface ice research (1)
- subsurface probe (1)
- suction structure (1)
- suction systems (1)
- surface modification (1)
- sustainability (1)
- swift heavy ions (1)
- system engineering (1)
- systematic literature review (1)
- tablet game (1)
- teaching (1)
- teaching of structures (1)
- technology diffusion (1)
- temperature measurement (1)
- thermal storage (1)
- thermo-physical (1)
- thick-film technology (1)
- thin-film microsensors (1)
- touch voltage (1)
- underwater vehicle (1)
- unreinforced masonry buildings (1)
- upper echelons theory (1)
- urban farming (1)
- user & usage (1)
- virtual reality (1)
- vocal fold oscillation (1)
- voltammetry (1)
- wafer-level testing (1)
- water bridge phenomenon (1)
- water supply system (1)
- wave run-up (1)
- wind turbine (1)
- Überspannung (1)
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
Useful market simulations are key to the evaluation of diferent market designs existing of multiple market mechanisms or rules. Yet a simulation framework which has a comparison of diferent market mechanisms in mind was not found. The need to create an objective view on different sets of market rules while investigating meaningful agent strategies concludes that such a simulation framework is needed to advance the research on this subject. An overview of diferent existing market simulation models is given which also shows the research gap and the missing capabilities of those systems. Finally, a methodology is outlined how a novel market simulation which can answer the research questions can be developed.
Kawasaki Heavy Industries, Ltd. (KHI), Aachen University of Applied Sciences, and B&B-AGEMA GmbH have investigated the potential of low NOx micro-mix (MMX) hydrogen combustion and its application to an industrial gas turbine combustor. Engine demonstration tests of a MMX combustor for the M1A-17 gas turbine with a co-generation system were conducted in the hydrogen-fueled power generation plant in Kobe City, Japan.
This paper presents the results of the commissioning test and the combined heat and power (CHP) supply demonstration. In the commissioning test, grid interconnection, loading tests and load cut-off tests were successfully conducted. All measurement results satisfied the Japanese environmental regulation values. Dust and soot as well as SOx were not detected. The NOx emissions were below 84 ppmv at 15 % O2. The noise level at the site boundary was below 60 dB. The vibration at the site boundary was below 45 dB.
During the combined heat and power supply demonstration, heat and power were supplied to neighboring public facilities with the MMX combustion technology and 100 % hydrogen fuel. The electric power output reached 1800 kW at which the NOx emissions were 72 ppmv at 15 % O2, and 60 %RH. Combustion instabilities were not observed. The gas turbine efficiency was improved by about 1 % compared to a non-premixed type combustor with water injection as NOx reduction method. During a total equivalent operation time of 1040 hours, all combustor parts, the M1A-17 gas turbine as such, and the co-generation system were without any issues.
Industrial facilities must be thoroughly designed to withstand seismic actions as they exhibit an increased loss potential due to the possibly wideranging damage consequences and the valuable process engineering equipment. Past earthquakes showed the social and political consequences of seismic damage to industrial facilities and sensitized the population and politicians worldwide for the possible hazard emanating from industrial facilities. However, a holistic approach for the seismic design of industrial facilities can presently neither be found in national nor in international standards. The introduction of EN 1998-4 of the new generation of Eurocode 8 will improve the normative situation with
specific seismic design rules for silos, tanks and pipelines and secondary process components. The article presents essential aspects of the seismic design of industrial facilities based on the new generation of Eurocode 8 using the example of tank structures and secondary process components. The interaction effects of the process components with the primary structure are illustrated by means of the experimental results of a shaking table test of a three story moment resisting steel frame with different process components. Finally, an integrated approach of
digital plant models based on building information modelling (BIM) and structural health monitoring (SHM) is presented, which provides not only a reliable decision-making basis for operation, maintenance and repair but also an excellent tool for rapid assessment of seismic damage.
A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived.
In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced.
Process mining gets more and more attention even outside large enterprises and can be a major benefit for small and medium sized enterprises (SMEs) to gain competitive advantages. Applying process mining is challenging, particularly for SMEs because they have less resources and process maturity. So far, IS researchers analyzed process mining challenges with a focus on larger companies. This paper investigates the application of process mining by means of a case study and sheds light into the particular challenges of an IT SME. The results reveal 13 SME process mining challenges and seven guidelines to address them. In this way, the paper contributes to the understanding of process mining application in SME and shows similarities and differences to larger companies.
A capacitive electrolyte-insulator-semiconductor (EISCAP) biosensor modified with Tobacco mosaic virus (TMV) particles for the detection of acetoin is presented. The enzyme acetoin reductase (AR) was immobilized on the surface of the EISCAP using TMV particles as nanoscaffolds. The study focused on the optimization of the TMV-assisted AR immobilization on the Ta 2 O 5 -gate EISCAP surface. The TMV-assisted acetoin EISCAPs were electrochemically characterized by means of leakage-current, capacitance-voltage, and constant-capacitance measurements. The TMV-modified transducer surface was studied via scanning electron microscopy.
Quantitative evaluation of health management designs for fuel cell systems in transport vehicles
(2022)
Focusing on transport vehicles, mainly with regard to aviation applications, this paper presents compilation and subsequent quantitative evaluation of methods aimed at building an optimum integrated health management solution for fuel cell systems. The methods are divided into two different main types and compiled in a related scheme. Furthermore, different methods are analysed and evaluated based on parameters specific to the aviation context of this study. Finally, the most suitable method for use in fuel cell health management systems is identified and its performance and suitability is quantified.
Electric flight has the potential for a more sustainable and energy-saving way of aviation compared to fossil fuel aviation. The electric motor can be used as a generator inflight to regenerate energy during descent. Three different approaches to regenerating with electric propeller powertrains are proposed in this paper. The powertrain is to be set up in a wind tunnel to determine the propeller efficiency in both working modes as well as the noise emissions. Furthermore, the planned flight tests are discussed. In preparation for these tests, a yaw stability analysis is performed with the result that the aeroplane is controllable during flight and in the most critical failure case. The paper shows the potential for inflight regeneration and addresses the research gaps in the dual role of electric powertrains for propulsion and regeneration of general aviation aircraft.
The replacement of existing spillway crests or gates with labyrinth weirs is a proven techno-economical means to increase the discharge capacity when rehabilitating existing structures. However, additional information is needed regarding energy dissipation of such weirs, since due to the folded weir crest, a three-dimensional flow field is generated, yielding more complex overflow and energy dissipation processes. In this study, CFD simulations of labyrinth weirs were conducted 1) to analyze the discharge coefficients for different discharges to compare the Cd values to literature data and 2) to analyze and improve energy dissipation downstream of the structure. All tests were performed for a structure at laboratory scale with a height of approx. P = 30.5 cm, a ratio of the total crest length to the total width of 4.7, a sidewall angle of 10° and a quarter-round weir crest shape. Tested headwater ratios were 0.089 ≤ HT/P ≤ 0.817. For numerical simulations, FLOW-3D Hydro was employed, solving the RANS equations with use of finite-volume method and RNG k-ε turbulence closure. In terms of discharge capacity, results were compared to data from physical model tests performed at the Utah Water Research Laboratory (Utah State University), emphasizing higher discharge coefficients from CFD than from the physical model. For upstream heads, some discrepancy in the range of ± 1 cm between literature, CFD and physical model tests was identified with a discussion regarding differences included in the manuscript. For downstream energy dissipation, variable tailwater depths were considered to analyze the formation and sweep-out of a hydraulic jump. It was found that even for high discharges, relatively low downstream Froude numbers were obtained due to high energy dissipation involved by the three-dimensional flow between the sidewalls. The effects of some additional energy dissipation devices, e.g. baffle blocks or end sills, were also analyzed. End sills were found to be non-effective. However, baffle blocks with different locations may improve energy dissipation downstream of labyrinth weirs.
Non-intrusive measuring techniques have attained a lot of interest in relation to both hydraulic modeling and prototype applications. Complimenting acoustic techniques, significant progress has been made for the development of new optical methods. Computer vision techniques can help to extract new information, e. g. high-resolution velocity and depth data, from videos captured with relatively inexpensive, consumer-grade cameras. Depth cameras are sensors providing information on the distance between the camera and observed features. Currently, sensors with different working principles are available. Stereoscopic systems reference physical image features (passive system) from two perspectives; in order to enhance the number of features and improve the results, a sensor may also estimate the disparity from a detected light to its original projection (active stereo system). In the current study, the RGB-D camera Intel RealSense D435, working on such stereo vision principle, is used in different, typical hydraulic modeling applications. All tests have been conducted at the Utah Water Research Laboratory. This paper will demonstrate the performance and limitations of the RGB-D sensor, installed as a single camera and as camera arrays, applied to 1) detect the free surface for highly turbulent, aerated hydraulic jumps, for free-falling jets and for an energy dissipation basin downstream of a labyrinth weir and 2) to monitor local scours upstream and downstream of a Piano Key Weir. It is intended to share the authors’ experiences with respect to camera settings, calibration, lightning conditions and other requirements in order to promote this useful, easily accessible device. Results will be compared to data from classical instrumentation and the literature. It will be shown that even in difficult application, e. g. the detection of a highly turbulent, fluctuating free-surface, the RGB-D sensor may yield similar accuracy as classical, intrusive probes.
Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables.
Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer.
Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench.
The industrial revolution IR4.0 era have driven many states of the art technologies to be introduced especially in the automotive industry. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South-East Asia (SEA). Indulging this situation, FH Joanneum, Austria together with European partners from FH Aachen, Germany and Politecnico Di Torino, Italy is taking initiative to close the gap utilizing the Erasmus+ United grant from EU. A consortium was founded to engage with automotive technology transfer using the European ramework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative, and high-quality training courses to increase graduate’s employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing Universityindustry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.
When confining pressure is low or absent, extensional fractures are typical, with fractures occurring on unloaded planes in rock. These “paradox” fractures can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. But this criterion makes unrealistic strength predictions in biaxial compression and tension. A new extension strain criterion overcomes this limitation by adding a weighted principal shear component. The weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr–Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting failure modes, which are unexpected in the understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak P. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.
In this work, three patent pending calibration methods for heliostat fields of central receiver systems (CRS) developed by the Solar-Institut Jülich (SIJ) of the FH Aachen University of Applied Sciences are presented. The calibration methods can either operate in a combined mode or in stand-alone mode. The first calibration method, method A, foresees that a camera matrix is placed into the receiver plane where it is subjected to concentrated solar irradiance during a measurement process. The second calibration method, method B, uses an unmanned aerial vehicle (UAV) such as a quadrocopter to automatically fly into the reflected solar irradiance cross-section of one or more heliostats (two variants of method B were tested). The third calibration method, method C, foresees a stereo central camera or multiple stereo cameras installed e.g. on the solar tower whereby the orientations of the heliostats are calculated from the location detection of spherical red markers attached to the heliostats. The most accurate method is method A which has a mean accuracy of 0.17 mrad. The mean accuracy of method B variant 1 is 1.36 mrad and of variant 2 is 1.73 mrad. Method C has a mean accuracy of 15.07 mrad. For method B there is great potential regarding improving the measurement accuracy. For method C the collected data was not sufficient for determining whether or not there is potential for improving the accuracy.
This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut Jülich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 % based on the tested days. The result fulfils SIJ’s aim to achieve a reliability of around 70 %, but SIJ aims to still improve the DNI forecast quality.
Recent earthquakes showed that low-rise URM buildings following codecompliant seismic design and details behaved in general very well without substantial damages. Although advances in simulation tools make nonlinear calculation methods more readily accessible to designers, linear analyses will still be the standard design method for years to come. The present paper aims to improve the linear seismic design method by providing a proper definition of the q-factor of URM buildings. Values of q-factors are derived for low-rise URM buildings with rigid diaphragms, with reference to modern structural configurations realized in low to moderate seismic areas of Italy and Germany. The behaviour factor components for deformation and energy dissipation capacity and for overstrength due to the redistribution of forces are derived by means of pushover analyses. As a result of the investigations, rationally based values of the behaviour factor q to be used in linear analyses in the range of 2.0 to 3.0 are proposed.
The Solar-Institut Jülich (SIJ) and the companies Hilger GmbH and Heliokon GmbH from Germany have developed a small-scale cost-effective heliostat, called “micro heliostat”. Micro heliostats can be deployed in small-scale concentrated solar power (CSP) plants to concentrate the sun's radiation for electricity generation, space or domestic water heating or industrial process heat. In contrast to conventional heliostats, the special feature of a micro heliostat is that it consists of dozens of parallel-moving, interconnected, rotatable mirror facets. The mirror facets array is fixed inside a box-shaped module and is protected from weathering and wind forces by a transparent glass cover. The choice of the building materials for the box, tracking mechanism and mirrors is largely dependent on the selected production process and the intended application of the micro heliostat. Special attention was paid to the material of the tracking mechanism as this has a direct influence on the accuracy of the micro heliostat. The choice of materials for the mirror support structure and the tracking mechanism is made in favor of plastic molded parts. A qualification assessment method has been developed by the SIJ in which a 3D laser scanner is used in combination with a coordinate measuring machine (CMM). For the validation of this assessment method, a single mirror facet was scanned and the slope deviation was computed.
Many of today’s factors make software development more and more complex, such as time pressure, new technologies, IT security risks, et cetera. Thus, a good preparation of current as well as future software developers in terms of a good software engineering education becomes progressively important. As current research shows, Competence Developing Games (CDGs) and Serious Games can offer a potential solution.
This paper identifies the necessary requirements for CDGs to be conducive in principle, but especially in software engineering (SE) education. For this purpose, the current state of research was summarized in the context of a literature review. Afterwards, some of the identified requirements as well as some additional requirements were evaluated by a survey in terms of subjective relevance.
Inference on the basis of high-dimensional and functional data are two topics which are discussed frequently in the current statistical literature. A possibility to include both topics in a single approach is working on a very general space for the underlying observations, such as a separable Hilbert space. We propose a general method for consistently hypothesis testing on the basis of random variables with values in separable Hilbert spaces. We avoid concerns with the curse of dimensionality due to a projection idea. We apply well-known test statistics from nonparametric inference to the projected data and integrate over all projections from a specific set and with respect to suitable probability measures. In contrast to classical methods, which are applicable for real-valued random variables or random vectors of dimensions lower than the sample size, the tests can be applied to random vectors of dimensions larger than the sample size or even to functional and high-dimensional data. In general, resampling procedures such as bootstrap or permutation are suitable to determine critical values. The idea can be extended to the case of incomplete observations. Moreover, we develop an efficient algorithm for implementing the method. Examples are given for testing goodness-of-fit in a one-sample situation in [1] or for testing marginal homogeneity on the basis of a paired sample in [2]. Here, the test statistics in use can be seen as generalizations of the well-known Cramérvon-Mises test statistics in the one-sample and two-samples case. The treatment of other testing problems is possible as well. By using the theory of U-statistics, for instance, asymptotic null distributions of the test statistics are obtained as the sample size tends to infinity. Standard continuity assumptions ensure the asymptotic exactness of the tests under the null hypothesis and that the tests detect any alternative in the limit. Simulation studies demonstrate size and power of the tests in the finite sample case, confirm the theoretical findings, and are used for the comparison with concurring procedures. A possible application of the general approach is inference for stock market returns, also in high data frequencies. In the field of empirical finance, statistical inference of stock market prices usually takes place on the basis of related log-returns as data. In the classical models for stock prices, i.e., the exponential Lévy model, Black-Scholes model, and Merton model, properties such as independence and stationarity of the increments ensure an independent and identically structure of the data. Specific trends during certain periods of the stock price processes can cause complications in this regard. In fact, our approach can compensate those effects by the treatment of the log-returns as random vectors or even as functional data.
Cure or blessing? The effect of (non-financial) signals on sustainable venture's funding success
(2022)
Despite the challenges of pioneering molten salt towers (MST), it remains the leading technology in central receiver power plants today, thanks to cost effective storage integration and high cost reduction potential. The limited controllability in volatile solar conditions can cause significant losses, which are difficult to estimate without comprehensive modeling [1]. This paper presents a Methodology to generate predictions of the dynamic behavior of the receiver system as part of an operating assistance system (OAS). Based on this, it delivers proposals if and when to drain and refill the receiver during a cloudy period in order maximize the net yield and quantifies the amount of net electricity gained by this. After prior analysis with a detailed dynamic two-phase model of the entire receiver system, two different reduced modeling approaches where developed and implemented in the OAS. A tailored decision algorithm utilizes both models to deliver the desired predictions efficiently and with appropriate accuracy.
The complex questions of today for a world of tomorrow are characterized by their global impact. Solutions must therefore not only be sustainable in the sense of the three pillars of sustainability (economic, environmental, and social) but must also function globally. This goes hand in hand with the need for intercultural acceptance of developed services and products. To achieve this, engineers, as the problem solvers of the future, must be able to work in intercultural teams on appropriate solutions, and be sensitive to intercultural perspectives. To equip the engineers of the future with the so-called future skills, teaching concepts are needed in which students can acquire these methods and competencies in application-oriented formats. The presented course "Applying Design Thinking - Sustainability, Innovation and Interculturality" was developed to teach future skills from the competency areas Digital Key Competencies, Classical Competencies and Transformative Competencies. The CDIO Standard 3.0, in particular the standards 5, 6, 7 and 8, was used as a guideline. The course aims to prepare engineering students from different disciplines and cultures for their future work in an international environment by combining a digital teaching format with an interdisciplinary, transdisciplinary and intercultural setting for solving sustainability challenges. The innovative moment lies in the digital application of design thinking and the inclusion of intercultural as well as trans- and interdisciplinary perspectives in innovation development processes. In this paper, the concept of the course will be presented in detail and the particularities of a digital implementation of design thinking will be addressed. Subsequently, the potentials and challenges will be reflected and practical advice for integrating design thinking in engineering education will be given.
Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.
In times of social climate protection movements, such as Fridays for Future, the priorities of society, industry and higher education are currently changing. The consideration of sustainability challenges is increasing. In the context of sustainable development, social skills are crucial to achieving the United Nations Sustainable Development Goals (SDGs). In particular, the impact that educational activities have on people, communities and society is therefore coming to the fore. Research has shown that people with high levels of social competence are better able to manage stressful situations, maintain positive relationships and communicate effectively. They are also associated with better academic performance and career success. However, especially in engineering programs, the social pillar is underrepresented compared to the environmental and economic pillars.
In response to these changes, higher education institutions should be more aware of their social impact - from individual forms of teaching to entire modules and degree programs. To specifically determine the potential for improvement and derive resulting change for further development, we present an initial framework for social impact measurement by transferring already established approaches from the business sector to the education sector. To demonstrate the applicability, we measure the key competencies taught in undergraduate engineering programs in Germany.
The aim is to prepare the students for success in the modern world of work and their future contribution to sustainable development. Additionally, the university can include the results in its sustainability report. Our method can be applied to different teaching methods and enables their comparison.
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle’s software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.
In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions.
We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models.
This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.
Rocket engine test facilities and launch pads are typically equipped with a guide tube. Its purpose is to ensure the controlled and safe routing of the hot exhaust gases. In addition, the guide tube induces a suction that effects the nozzle flow, namely the flow separation during transient start-up and shut-down of the engine. A cold flow subscale nozzle in combination with a set of guide tubes was studied experimentally
to determine the main influencing parameters.
Dynamic loads significantly impact the structural design of propeller blades due to fatigue and static strength. Since propellers are elastic structures, deformations and aerodynamic loads are coupled. In the past, propeller manufacturers established procedures to determine unsteady aerodynamic loads and the structural response with analytical steady-state calculations. According to the approach, aeroelastic coupling primarily consists of torsional deformations. They neglect bending deformations, deformation velocities, and inertia terms. This paper validates the assumptions above for a General Aviation propeller and a lift propeller for urban air mobility or large cargo drones. Fully coupled reduced-order simulations determine the dynamic loads in the time domain. A quasi-steady blade element momentum approach transfers loads to one-dimensional finite beam elements. The simulation results are in relatively good agreement with the analytical method for the General Aviation propeller but show increasing errors for the slender lift propeller. The analytical approach is modified to consider the induced velocities. Still, inertia and velocity proportional terms play a significant role for the lift propeller due to increased elasticity. The assumption that only torsional deformations significantly impact the dynamic loads of propellers is not valid. Adequate determination of dynamic loads of such designs requires coupled aeroelastic simulations or advanced analytical procedures.
Due to the increasing complexity of software projects, software development is becoming more and more dependent on teams. The quality of this teamwork can vary depending on the team composition, as teams are always a combination of different skills and personality types. This paper aims to answer the question of how to describe a software development team and what influence the personality of the team members has on the team dynamics. For this purpose, a systematic literature review (n=48) and a literature search with the AI research assistant Elicit (n=20) were conducted. Result: A person’s personality significantly shapes his or her thinking and actions, which in turn influences his or her behavior in software development teams. It has been shown that team performance and satisfaction can be strongly influenced by personality. The quality of communication and the likelihood of conflict can also be attributed to personality.
Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.
The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019.
The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle’s drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems
The integration of high temperature thermal energy storages into existing conventional power plants can help to reduce the CO2 emissions of those plants and lead to lower capital expenditures for building energy storage systems, due to the use of synergy effects [1]. One possibility to implement that, is a molten salt storage system with a powerful power-to-heat unit. This paper presents two possible control concepts for the startup of the charging system of such a facility. The procedures are implemented in a detailed dynamic process model. The performance and safety regarding the film temperatures at heat transmitting surfaces are investigated in the process simulations. To improve the accuracy in predicting the film temperatures, CFD simulations of the electrical heater are carried out and the results are merged with the dynamic model. The results show that both investigated control concepts are safe regarding the temperature limits. The gradient controlled startup performed better than the temperature-controlled startup. Nevertheless, there are several uncertainties that need to be investigated further.
The major advantage of labyrinth weirs over linear weirs is hydraulic efficiency. In hydraulic modeling efforts, this strength contrasts with limited pump capacity as well as limited computational power for CFD simulations. For the latter, reducing the number of investigated cycles can significantly reduce necessary computational time. In this study, a labyrinth weir with different cycle numbers was investigated. The simulations were conducted in FLOW-3D HYDRO as a Large Eddy Simulation. With a mean deviation of 1.75 % between simulated discharge coefficients and literature design equations, a reasonable agreement was found. For downstream conditions, overall consistent results were observed as well. However, the orientation of labyrinth weirs with a single cycle should be chosen carefully under consideration of the individual research purpose.
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
This paper describes the potential for developing a digital twin of society- a dynamic model that can be used to observe, analyze, and predict the evolution of various societal aspects. Such a digital twin can help governmental agencies and policy makers in interpreting trends, understanding challenges, and making decisions regarding investments or policies necessary to support societal development and ensure future prosperity. The paper reviews related work regarding the digital twin paradigm and its applications. The paper presents a motivating case study- an analysis of opportunities and challenges faced by the German federal employment agency, Bundesagentur f¨ur Arbeit (BA), proposes solutions using digital twins, and describes initial proofs of concept for such solutions.
In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
Research on robotic lunar exploration has seen a broad revival, especially since the Google Lunar X-Prize increasingly brought private endeavors into play. This development is supported by national agencies with the aim of enabling long-term lunar infrastructure for in-situ operations and the establishment of a moon village. One challenge for effective exploration missions is developing a compact and lightweight robotic rover to reduce launch costs and open the possibility for secondary payload options. Existing micro rovers for exploration missions are clearly limited by their design for one day of sunlight and their low level of autonomy. For expanding the potential mission applications and range of use, an extension of lifetime could be reached by surviving the lunar night and providing a higher level of autonomy. To address this objective, the paper presents a system design concept for a lightweight micro rover with long-term mission duration capabilities, derived from a multi-day lunar mission scenario at equatorial regions. Technical solution approaches are described, analyzed, and evaluated, with emphasis put on the harmonization of hardware selection due to a strictly limited budget in dimensions and power.
In Europe, efforts are underway to develop key technologies that can be used to explore the Moon and to exploit the resources available. This includes technologies for in-situ resource utilization (ISRU), facilitating the possibility of a future Moon Village. The Moon is the next step for humans and robots to exploit the use of available resources for longer term missions, but also for further exploration of the solar system. A challenge for effective exploration missions is to achieve a compact and lightweight robot to reduce launch costs and open up the possibility of secondary payload options. Current micro rover concepts are primarily designed to last for one day of solar illumination and show a low level of autonomy. Extending the lifetime of the system by enabling survival of the lunar night and implementing a high level of autonomy will significantly increase potential mission applications and the operational range. As a reference mission, the deployment of a micro rover in the equatorial region of the Moon is being considered. An overview of mission parameters and a detailed example mission sequence is given in this paper. The mission parameters are based on an in-depth study of current space agency roadmaps, scientific goals, and upcoming flight opportunities. Furthermore, concepts of the ongoing international micro rover developments are analyzed along with technology solutions identified for survival of lunar nights and a high system autonomy. The results provide a basis of a concise requirements set-up to allow dedicated system developments and qualification measures in the future.
In addition to the technical content, modern courses at university should also teach professional skills to enhance the competencies of students towards their future work. The competency driven approach including technical as well as professional skills makes it necessary to find a suitable way for the integration into the corresponding module in a scalable and flexible manner. Agile development, for example, is essential for the development of modern systems and applications and makes use of dedicated professional skills of the team members, like structured group dynamics and communication, to enable the fast and reliable development. This paper presents an easy to integrate and flexible approach to integrate Scrum, an agile development method, into the lab of an existing module. Due to the different role models of Scrum the students have an individual learning success, gain valuable insight into modern system development and strengthen their communication and organization skills. The approach is implemented and evaluated in the module Vehicle Systems, but it can be transferred easily to other technical courses as well. The evaluation of the implementation considers feedback of all stakeholders, students, supervisor and lecturers, and monitors the observations during project lifetime.
The feasibility study presents results of a hydrogen combustor integration for a Medium-Range aircraft engine using the Dry-Low-NOₓ Micromix combustion principle. Based on a simplified Airbus A320-type flight mission, a thermodynamic performance model of a kerosene and a hydrogen-powered V2530-A5 engine is used to derive the thermodynamic combustor boundary conditions. A new combustor design using the Dry-Low NOx Micromix principle is investigated by slice model CFD simulations of a single Micromix injector for design and off-design operation of the engine. Combustion characteristics show typical Micromix flame shapes and good combustion efficiencies for all flight mission operating points. Nitric oxide emissions are significant below ICAO CAEP/8 limits. For comparison of the Emission Index (EI) for NOₓ emissions between kerosene and hydrogen operation, an energy (kerosene) equivalent Emission Index is used.
A full 15° sector model CFD simulation of the combustion chamber with multiple Micromix injectors including inflow homogenization and dilution and cooling air flows investigates the combustor integration effects, resulting NOₓ emission and radial temperature distributions at the combustor outlet. The results show that the integration of a Micromix hydrogen combustor in actual aircraft engines is feasible and offers, besides CO₂ free combustion, a significant reduction of NOₓ emissions compared to kerosene operation.
Achieving the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) in 2015 requires global collaboration between different stakeholders. Industry, and in particular engineers who shape industrial developments, have a special role to play as they are confronted with the responsibility to holistically reflect sustainability in industrial processes. This means that, in addition to the technical specifications, engineers must also question the effects of their own actions on an ecological, economic and social level in order to ensure sustainable action and contribute to the achievement of the SDGs. However, this requires competencies that enable engineers to apply all three pillars of sustainability to their own field of activity and to understand the global impact of industrial processes. In this context, it is relevant to understand how industry already reflects sustainability and to identify competences needed for sustainable development.
The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
KNX is a protocol for smart building automation, e.g., for automated heating, air conditioning, or lighting. This paper analyses and evaluates state-of-the-art KNX devices from manufacturers Merten, Gira and Siemens with respect to security. On the one hand, it is investigated if publicly known vulnerabilities like insecure storage of passwords in software, unencrypted communication, or denialof-service attacks, can be reproduced in new devices. On the other hand, the security is analyzed in general, leading to the discovery of a previously unknown and high risk vulnerability related to so-called BCU (authentication) keys.
The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores.
Market abstraction of energy markets and policies - application in an agent-based modeling toolbox
(2023)
In light of emerging challenges in energy systems, markets are prone to changing dynamics and market design. Simulation models are commonly used to understand the changing dynamics of future electricity markets. However, existing market models were often created with specific use cases in mind, which limits their flexibility and usability. This can impose challenges for using a single model to compare different market designs. This paper introduces a new method of defining market designs for energy market simulations. The proposed concept makes it easy to incorporate different market designs into electricity market models by using relevant parameters derived from analyzing existing simulation tools, morphological categorization and ontologies. These parameters are then used to derive a market abstraction and integrate it into an agent-based simulation framework, allowing for a unified analysis of diverse market designs. Furthermore, we showcase the usability of integrating new types of long-term contracts and over-the-counter trading. To validate this approach, two case studies are demonstrated: a pay-as-clear market and a pay-as-bid long-term market. These examples demonstrate the capabilities of the proposed framework.
Pulmonary arterial cannulation is a common and effective method for percutaneous mechanical circulatory support for concurrent right heart and respiratory failure [1]. However, limited data exists to what effect the positioning of the cannula has on the oxygen perfusion throughout the pulmonary artery (PA). This study aims to evaluate, using computational fluid dynamics (CFD), the effect of different cannula positions in the PA with respect to the oxygenation of the different branching vessels in order for an optimal cannula position to be determined. The four chosen different positions (see Fig. 1) of the cannulas are, in the lower part of the main pulmonary artery (MPA), in the MPA at the junction between the right pulmonary artery (RPA) and the left pulmonary artery (LPA), in the RPA at the first branch of the RPA and in the LPA at the first branch of the LPA.
Magnetic nanoparticles (MNP) are investigated with great interest for biomedical applications in diagnostics (e.g. imaging: magnetic particle imaging (MPI)), therapeutics (e.g. hyperthermia: magnetic fluid hyperthermia (MFH)) and multi-purpose biosensing (e.g. magnetic immunoassays (MIA)). What all of these applications have in common is that they are based on the unique magnetic relaxation mechanisms of MNP in an alternating magnetic field (AMF). While MFH and MPI are currently the most prominent examples of biomedical applications, here we present results on the relatively new biosensing application of frequency mixing magnetic detection (FMMD) from a simulation perspective. In general, we ask how the key parameters of MNP (core size and magnetic anisotropy) affect the FMMD signal: by varying the core size, we investigate the effect of the magnetic volume per MNP; and by changing the effective magnetic anisotropy, we study the MNPs’ flexibility to leave its preferred magnetization direction. From this, we predict the most effective combination of MNP core size and magnetic anisotropy for maximum signal generation.
In this paper, the use of reinforcement learning (RL) in control systems is investigated using a rotatory inverted pendulum as an example. The control behavior of an RL controller is compared to that of traditional LQR and MPC controllers. This is done by evaluating their behavior under optimal conditions, their disturbance behavior, their robustness and their development process. All the investigated controllers are developed using MATLAB and the Simulink simulation environment and later deployed to a real pendulum model powered by a Raspberry Pi. The RL algorithm used is Proximal Policy Optimization (PPO). The LQR controller exhibits an easy development process, an average to good control behavior and average to good robustness. A linear MPC controller could show excellent results under optimal operating conditions. However, when subjected to disturbances or deviations from the equilibrium point, it showed poor performance and sometimes instable behavior. Employing a nonlinear MPC Controller in real time was not possible due to the high computational effort involved. The RL controller exhibits by far the most versatile and robust control behavior. When operated in the simulation environment, it achieved a high control accuracy. When employed in the real system, however, it only shows average accuracy and a significantly greater performance loss compared to the simulation than the traditional controllers. With MATLAB, it is not yet possible to directly post-train the RL controller on the Raspberry Pi, which is an obstacle to the practical application of RL in a prototyping or teaching setting. Nevertheless, RL in general proves to be a flexible and powerful control method, which is well suited for complex or nonlinear systems where traditional controllers struggle.
This paper serves as an introduction to the ECTS monitoring system and its potential applications in higher education. It also emphasizes the potential for ECTS monitoring to become a proactive system, supporting students by predicting academic success and identifying groups of potential dropouts for tailored support services. The use of the nearest neighbor analysis is suggested for improving data analysis and prediction accuracy.
Humic substances possess distinctive chemical features enabling their use in many advanced applications, including biomedical fields. No chemicals in nature have the same combination of specific chemical and biological properties as humic substances. Traditional medicine and modern research have demonstrated that humic substances from different sources possess immunomodulatory and anti-inflammatory properties, which makes them suitable for the prevention and treatment of chronic dermatoses, allergic rhinitis, atopic dermatitis, and other conditions characterized by inflammatory and allergic responses [1-4]. The use of humic compounds as agentswith antifungal and antiviral properties shows great potential [5-7].
This study presents the concept of AstroBioLab, an autonomous astrobiological field laboratory tailored for the exploration of (sub)glacial habitats. AstroBioLab is an integral component of the TRIPLE (Technologies for Rapid Ice Penetration and subglacial Lake Exploration) DLR-funded project, aimed at advancing astrobiology research through the development and deployment of innovative technologies. AstroBioLab integrates diverse measurement techniques such as fluorescence microscopy, DNA sequencing and fluorescence spectrometry, while leveraging microfluidics for efficient sample delivery and preparation.
Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or infimum with respect to an order over the tonal range in a certain section of the image. The tonal ordering can easily be realised in grey-scale morphology, and some morphological methods have been proposed for colour morphology. However, all of these have certain limitations.
In this paper we present a novel approach to colour morphology extending upon previous work in the field based on the Loewner order. We propose to consider an approximation of the supremum by means of a log-sum exponentiation introduced by Maslov. We apply this to the embedding of an RGB image in a field of symmetric 2x2 matrices. In this way we obtain nearly isotropic matrices representing colours and the structural advantage of transitivity. In numerical experiments we highlight some remarkable properties of the proposed approach.
The Inverted Rotary Pendulum: Facilitating Practical Teaching in Advanced Control Engineering
(2024)
This paper outlines a practical approach to teach control engineering principles, with an inverted rotary pendulum, serving as an illustrative example. It shows how the pendulum is embedded in an advanced course of control engineering. This approach is incorporated into a flipped-classroom concept, as well as classical teaching concepts, offering students practical experience in control engineering. In addition, the design of the pendulum is shown, using a Raspberry Pi as the target platform for Matlab Simulink. This pendulum can be used in the classroom to evaluate the controller design mentioned above. It is analysed if the use of the pendulum generates a deeper understanding of the learning contents.
After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.
In recent years, more and more digital startups have been founded and many of them work remotely by applying enterprise collaboration systems (ECS). The study investigates the functional affordances of ECS, particularly Slack, and examines its potential as a virtual office environment for cultural development in digital startups. Through a case study and based on affordance theoretical considerations, the paper explores how ECS facilitates remote collaboration, communication, and socialization within digital startups. The findings comprise material properties of ECS (synchrony and asynchrony communication), functional affordances (virtual office and culture development affordances) as well as its realization (through communication practices, openness, and inter-company accessibility) and are conceptualized as a model for ECS affordances in digital startups.
Due to the transition to renewable energies, electricity markets need to be made fit for purpose. To enable the comparison of different energy market designs, modeling tools covering market actors and their heterogeneous behavior are needed. Agent-based models are ideally suited for this task. Such models can be used to simulate and analyze changes to market design or market mechanisms and their impact on market dynamics. In this paper, we conduct an evaluation and comparison of two actively developed open-source energy market simulation models. The two models, namely AMIRIS and ASSUME, are both designed to simulate future energy markets using an agent-based approach. The assessment encompasses modelling features and techniques, model performance, as well as a comparison of model results, which can serve as a blueprint for future comparative studies of simulation models. The main comparison dataset includes data of Germany in 2019 and simulates the Day-Ahead market and participating actors as individual agents. Both models are comparable close to the benchmark dataset with a MAE between 5.6 and 6.4 €/MWh while also modeling the actual dispatch realistically.
In the research domain of energy informatics, the importance of open datais rising rapidly. This can be seen as various new public datasets are created andpublished. Unfortunately, in many cases, the data is not available under a permissivelicense corresponding to the FAIR principles, often lacking accessibility or reusability.Furthermore, the source format often differs from the desired data format or does notmeet the demands to be queried in an efficient way. To solve this on a small scale atoolbox for ETL-processes is provided to create a local energy data server with openaccess data from different valuable sources in a structured format. So while the sourcesitself do not fully comply with the FAIR principles, the provided unique toolbox allows foran efficient processing of the data as if the FAIR principles would be met. The energydata server currently includes information of power systems, weather data, networkfrequency data, European energy and gas data for demand and generation and more.However, a solution to the core problem - missing alignment to the FAIR principles - isstill needed for the National Research Data Infrastructure.