Springer
Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (70)
- Fachbereich Elektrotechnik und Informationstechnik (67)
- IfB - Institut für Bioengineering (40)
- Fachbereich Luft- und Raumfahrttechnik (30)
- Fachbereich Chemie und Biotechnologie (24)
- Fachbereich Energietechnik (22)
- Fachbereich Wirtschaftswissenschaften (12)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (12)
- Fachbereich Maschinenbau und Mechatronik (11)
- INB - Institut für Nano- und Biotechnologien (11)
Language
- English (237) (remove)
Document Type
- Article (122)
- Part of a Book (89)
- Conference Proceeding (24)
- Book (2)
Keywords
- MINLP (3)
- Natural language processing (3)
- Seismic design (3)
- Additive manufacturing (2)
- CFD (2)
- Engineering optimization (2)
- Information extraction (2)
- Obstacle avoidance (2)
- Optimization (2)
- Path planning (2)
- Pitching Moment (2)
- Powertrain (2)
- Process engineering (2)
- Tanks (2)
- Telecommunication (2)
- UAV (2)
- Wave Drag (2)
- Wind Tunnel (2)
- 3D printing (1)
- ABE (1)
- Acid crash (1)
- Active learning (1)
- Actuator disk modelling (1)
- Acyl-amino acids (1)
- Acylation (1)
- Advanced driver assistance systems (ADAS/AD) (1)
- Agent-based simulation (1)
- Aircraft sizing (1)
- Algal Turf Scrubber (1)
- Algal–bacterial bioflm (1)
- Aminoacylase (1)
- Analytics (1)
- Annulus Fibrosus (1)
- Autonomous mobile robots (1)
- Autonomy (1)
- BET (1)
- BEV (1)
- Balance (1)
- Balanced hypergraph (1)
- Best practice sharing (1)
- Bio-inspired systems (1)
- Biocatalysis (1)
- Bioeconomy (1)
- Bioethanol (1)
- Biogas (1)
- Biomechanical simulation (1)
- Biomolecular logic gate (1)
- Biorefinery (1)
- Biorefinery definitions (1)
- Biosurfactants (1)
- Bladder (1)
- Bloom’s Taxonomy (1)
- Bone sawing (1)
- Boundary integral equations (1)
- Brake set-up (1)
- Brake test (1)
- Business Models (1)
- Business Process (1)
- Butanol (1)
- C. acetobutylicum (1)
- CFD propeller simulation (1)
- Calorimetric gas sensor (1)
- Capacitive field-effect sensor (1)
- Cardiovascular MRI (1)
- Carsharing (1)
- Centrifugal twisting moment (1)
- Certification Rule (1)
- Change culture (1)
- Chaperone (1)
- Charging station (1)
- Charging stations (1)
- Chemical imaging (1)
- Chondroitin sulfate (1)
- Circular bioeconomy (1)
- Clustering (1)
- Co-managed care (1)
- Coefficient of ocular rigidity (1)
- Cognitive assistance system (1)
- Collaborative robot (1)
- Competence Developing Games (1)
- Complex System (1)
- Components (1)
- Connected Automated Vehicle (1)
- Controller Parameter (1)
- Cooling system (1)
- Corneo-scleral shell (1)
- Coverage probability (1)
- Cryptographic protocols (1)
- Crámer–von-Mises distance (1)
- Customer Orientation (1)
- DNA (1)
- Decentral (1)
- Deep learning (1)
- Design examples (1)
- Dietary supplements (1)
- Differential tonometry (1)
- Digital leadership (1)
- Digital manufacturing (1)
- Disc Degeneration (1)
- Drag Reduction (1)
- Drag estimation (1)
- Dry surfaces (1)
- Duality (1)
- E-carsharing (1)
- E-mobility (1)
- EN 1998-4 (1)
- Efficiency optimization (1)
- Elderly (1)
- Electrical vehicle (1)
- Electromagnetism (1)
- Electronic vehicle (1)
- Elicit (1)
- Energy efficiency (1)
- Energy market design (1)
- Engine Efficiency (1)
- Engineering optimisation (1)
- Enterprise Architecture (1)
- Enterprise architecture (1)
- Enterprise transformation (1)
- Enzyme biosensor (1)
- Equivalence test (1)
- Eurocode 8 (1)
- Evacuation Rule (1)
- Experimental validation (1)
- Extension–twist coupling (1)
- Eyeball (1)
- FGF23 (1)
- Fall prevention (1)
- Field-effect device (1)
- Field-effect sensor (1)
- Flight Test (1)
- Fracture configuration (1)
- Fracture simulation (1)
- Freight rail (1)
- Fully connected car (1)
- Game-based learning (1)
- Gamification (1)
- Gearbox (1)
- Glass powder (1)
- Glaucoma (1)
- Global optimization (1)
- Glucosamine (1)
- Gold nanoparticle (1)
- Goodness-of-fit tests for uniformity (1)
- Ground-level falls (1)
- Growth modelling (1)
- Gust wind response (1)
- Hall’s Theorem (1)
- Helmholtz equation (1)
- High field MRI (1)
- High-field NMR (1)
- Human-Robot interaction (1)
- Human-centered work design (1)
- Human-robot collaboration (1)
- Hydraulic structures (1)
- Hydrogen peroxide (1)
- Hypergraph (1)
- ISO 26262 (1)
- IT Products (1)
- IT security education (1)
- Ice melting probe (1)
- Ice penetration (1)
- Icy moons (1)
- Incident analysis (1)
- Incomplete data (1)
- Inductive charging (1)
- Industrial facilities (1)
- Industrial optimisation (1)
- Industrial units (1)
- Industry 4.0 (1)
- Information and communication technology (1)
- Integrated empirical distribution (survival) function (1)
- Integrated mobility (1)
- Interactive process mining (1)
- Interior Neumann eigenvalues (1)
- Intervertebral Disc (1)
- Intradiscal Pressure (1)
- Introduction (1)
- Keyword analysis (1)
- Klotho (1)
- Koenig’s Theorem (1)
- L-PBF (1)
- Label-free detection (1)
- Laser processing (1)
- Leaderboard (1)
- Leading Edge Vortex (1)
- Lean thinking (1)
- Left ventriular function (1)
- Level Control System (1)
- Lifting propeller (1)
- Light-addressable potentiometric sensor (1)
- Lignocellulose feedstook (1)
- Limit analysis (1)
- Local path planning (1)
- MILP (1)
- MR safety (1)
- MR-stethoscope (1)
- MRI (1)
- Mach Number (1)
- Machine learning (1)
- Magnetic field strength (1)
- Magnetic resonance imaging (MRI) (1)
- Magneto alert sensor (1)
- Malicious model (1)
- Map (eTOM) Process reference model Process design Telecommunications industry (1)
- Marginal homogeneity test (1)
- Market modeling (1)
- Mars (1)
- Matching (1)
- Mechanical (1)
- Mechanical simulation (1)
- Melting (1)
- Metabolic shift (1)
- Methane (1)
- Methodology (1)
- Microbial adhesion (1)
- Minimum Risk Manoeuvre (1)
- Minor chemistry (1)
- Mixed-integer nonlinear black-box optimization (1)
- Mixed-integer nonlinear problem (1)
- Mixed-integer nonlinear programming (1)
- Mixed-integer programming (1)
- Mobility (1)
- Mobility management (1)
- Mobility tests (1)
- Multi-criteria optimization (1)
- Multi-robot systems (1)
- Multi-sensor system (1)
- Multidisciplinary Design Optimization (1)
- Multimode failure (1)
- Multirotor UAS (1)
- Muscle fibers (1)
- Natural language understanding (1)
- Network (1)
- Neural Network (1)
- Noise Exposure (1)
- Non-linear optimization (1)
- Nonlinear Dynamics (1)
- Nucleus Pulposus (1)
- Numerical inversion of Laplace transforms (1)
- Numerics (1)
- OR 2019 (1)
- Objective data (1)
- Ocean worlds (1)
- Ocular blood flow (1)
- On-site (1)
- Open channels (1)
- Operational Design Domain (1)
- Optimal Closed Loop (1)
- Optimal Topology (1)
- PTH (1)
- Paired sample (1)
- Paper recycling (1)
- Parabolized Stability Equation (1)
- Parasitic drag (1)
- Parking (1)
- Passenger compartment (1)
- Passive stretching (1)
- Pelvic floor dysfunction (1)
- Pelvic muscle (1)
- Performance (1)
- Personality (1)
- Phosphate (1)
- Physical chemistry (1)
- Physical chemistry basics (1)
- Physical chemistry starters (1)
- Physical modeling (1)
- Piecewise linearization (1)
- Plant virus (1)
- Polysaccharides (1)
- Potential theory (1)
- Potentiometry (1)
- Pre-culture (1)
- Pre-treatment (1)
- Pressure-volume relationship (1)
- Privacy (1)
- Privacy-enhancing technologies (1)
- Process design (1)
- Process reference model (1)
- Process schemes (1)
- Process virtualization (1)
- Product Management (1)
- Product bundling (1)
- Product family optimization (1)
- Profile extraction (1)
- Propeller aerodynamics (1)
- Propeller performance (1)
- Proximal humerus fracture (1)
- Pumping systems (1)
- Pushover analysis (1)
- Query learning (1)
- RVA (1)
- Rapid manufacturing (1)
- Rapid prototyping (1)
- Reconstruction (1)
- Reference modelling (1)
- Relation classification (1)
- Reliability analysis (1)
- Renewable resources (1)
- Reproducible research (1)
- Resampling test (1)
- Reservation system (1)
- Resilience (1)
- Resolvent Operator (1)
- Response spectrum (1)
- Responsibility (1)
- RoboCup (1)
- Rotator cuff (1)
- Safety concept (1)
- Safety of the intended functionality (SOTIF) (1)
- Safety-critical systems validation (1)
- Sampling methods (1)
- Secure multi-party computation (1)
- Services (1)
- Severe Accident (1)
- Shakedown analysis (1)
- Silos (1)
- Similitude (1)
- Simulation (1)
- Smart factory (1)
- Software (1)
- Software development (1)
- Software testing (1)
- Sonic Boom (1)
- Specific Fuel Consumption (1)
- Spectral analysis (1)
- Strategic Business Planning (1)
- Structural health monitoring (1)
- Supersonic Flow (1)
- Supersonic Wind Tunnel (1)
- Surface microorganisms (1)
- Swabbing (1)
- TM Forum (1)
- Teamwork (1)
- Technical Operation Research (1)
- Technical Operations Research (1)
- Technology Challenge (1)
- Telecommunication Industry (1)
- Text mining (1)
- Thermal Fatigue Testing (1)
- Thermal comfort (1)
- Thermal management (1)
- Thermodynamics as minor (1)
- Tinetti test (1)
- Tobacco mosaic virus (TMV) (1)
- Train composition (1)
- Transformation (1)
- Transformation Project (1)
- Transiton of Control (1)
- Trapeze effect (1)
- Trustworthy artificial intelligence (1)
- Uktrahigh field MRI (1)
- Unmanned aerial vehicles (1)
- Urban areas (1)
- Ureter (1)
- Utilization improvement (1)
- V2X (1)
- Validation (1)
- Variable Geometry (1)
- Vascular response (1)
- Vertex cover (1)
- Visual field asymmetry (1)
- Vitamin D (1)
- WLTP (1)
- Water (1)
- Water distribution system (1)
- Wind milling (1)
- Wind tunnel experiments (1)
- Wind turbulence (1)
- Workspace monitoring (1)
- Zero-knowledge proofs (1)
- Zeta potential (1)
- business analytics (1)
- decision analytics (1)
- digital economy (1)
- enhanced Telecom Operations Map (eTOM) (1)
- mathematical optimization (1)
- training simulator (1)
- virtual reality (1)
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.
Cardiopulmonary bypass (CPB) is a standard technique for cardiac surgery, but comes with the risk of severe neurological complications (e.g. stroke) caused by embolisms and/or reduced cerebral perfusion. We report on an aortic cannula prototype design (optiCAN) with helical outflow and jet-splitting dispersion tip that could reduce the risk of embolic events and restores cerebral perfusion to 97.5% of physiological flow during CPB in vivo, whereas a commercial curved-tip cannula yields 74.6%. In further in vitro comparison, pressure loss and hemolysis parameters of optiCAN remain unaffected. Results are reproducibly confirmed in silico for an exemplary human aortic anatomy via computational fluid dynamics (CFD) simulations. Based on CFD simulations, we firstly show that optiCAN design improves aortic root washout, which reduces the risk of thromboembolism. Secondly, we identify regions of the aortic intima with increased risk of plaque release by correlating areas of enhanced plaque growth and high wall shear stresses (WSS). From this we propose another easy-to-manufacture cannula design (opti2CAN) that decreases areas burdened by high WSS, while preserving physiological cerebral flow and favorable hemodynamics. With this novel cannula design, we propose a cannulation option to reduce neurological complications and the prevalence of stroke in high-risk patients after CPB.
Previous studies optimized the dimensions of coaxial heat exchangers using constant mass fow rates as a boundary condition. They show a thermal optimal circular ring width of nearly zero. Hydraulically optimal is an inner to outer pipe radius ratio of 0.65 for turbulent and 0.68 for laminar fow types. In contrast, in this study, fow conditions in the circular ring are kept constant (a set of fxed Reynolds numbers) during optimization. This approach ensures fxed fow conditions and prevents inappropriately high or low mass fow rates. The optimization is carried out for three objectives: Maximum energy gain, minimum hydraulic efort and eventually optimum net-exergy balance. The optimization changes the inner pipe radius and mass fow rate but not the Reynolds number of the circular ring. The thermal calculations base on Hellström’s borehole resistance and the hydraulic optimization on individually calculated linear loss of head coefcients. Increasing the inner pipe radius results in decreased hydraulic losses in the inner pipe but increased losses in the circular ring. The net-exergy diference is a key performance indicator and combines thermal and hydraulic calculations. It is the difference between thermal exergy fux and hydraulic efort. The Reynolds number in the circular ring is instead of the mass fow rate constant during all optimizations. The result from a thermal perspective is an optimal width of the circular ring of nearly zero. The hydraulically optimal inner pipe radius is 54% of the outer pipe radius for laminar fow and 60% for turbulent fow scenarios. Net-exergetic optimization shows a predominant infuence of hydraulic losses, especially for small temperature gains. The exact result depends on the earth’s thermal properties and the fow type. Conclusively, coaxial geothermal probes’ design should focus on the hydraulic optimum and take the thermal optimum as a secondary criterion due to the dominating hydraulics.
In the study, the process chain of additive manufacturing by means of powder bed fusion will be presented based on the material glass. In order to reliably process components additively, new concepts with different solutions were developed and investigated.
Compared to established metallic materials, the properties of glass materials differ significantly. Therefore, the process control was adapted to the material glass in the investigations. With extensive parameter studies based on various glass powders such as borosilicate glass and quartz glass, scientifically proven results on powder bed fusion of glass are presented. Based on the determination of the particle properties with different methods, extensive investigations are made regarding the melting behavior of glass by means of laser beams. Furthermore, the experimental setup was steadily expanded. In addition to the integration of coaxial temperature measurement and regulation, preheating of the building platform is of major importance. This offers the possibility to perform 3D printing at the transformation temperatures of the glass materials. To improve the component’s properties, the influence of a subsequent heat treatment was also investigated.
The experience gained was incorporated into a new experimental system, which allows a much better exploration of the 3D printing of glass. Currently, studies are being conducted to improve surface texture, building accuracy, and geometrical capabilities using three-dimensional specimen.
The contribution shows the development of research in the field of 3D printing of glass, gives an insight into the machine and process engineering as well as an outlook on the possibilities and applications.
The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.
The Robot Operating System (ROS) is the current de-facto standard in robot middlewares. The steadily increasing size of the user base results in a greater demand for training as well. User groups range from students in academia to industry professionals with a broad spectrum of developers in between. To deliver high quality training and education to any of these audiences, educators need to tailor individual curricula for any such training. In this paper, we present an approach to ease compiling curricula for ROS trainings based on a taxonomy of the teaching contents. The instructor can select a set of dedicated learning units and the system will automatically compile the teaching material based on the dependencies of the units selected and a set of parameters for a particular training. We walk through an example training to illustrate our work.
Game-based learning is a promising approach to anti-phishing education, as it fosters motivation and can help reduce the perceived difficulty of the educational material. Over the years, several prototypes for game-based applications have been proposed, that follow different approaches in content selection, presentation, and game mechanics. In this paper, a literature and product review of existing learning games is presented. Based on research papers and accessible applications, an in-depth analysis was conducted, encompassing target groups, educational contexts, learning goals based on Bloom’s Revised Taxonomy, and learning content. As a result of this review, we created the publications on games (POG) data set for the domain of anti-phishing education. While there are games that can convey factual and conceptual knowledge, we find that most games are either unavailable, fail to convey procedural knowledge or lack technical depth. Thus, we identify potential areas of improvement for games suitable for end-users in informal learning contexts.
Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed.