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A German–Brazilian research project investigates sugarcane as an energy plant in anaerobic digestion for biogas production. The aim of the project is a continuous, efficient, and stable biogas process with sugarcane as the substrate. Tests are carried out in a fermenter with a volume of 10 l.
In order to optimize the space–time load to achieve a stable process, a continuous process in laboratory scale has been devised. The daily feed in quantity and the harvest time of the substrate sugarcane has been varied. Analyses of the digester content were conducted twice per week to monitor the process: The ratio of inorganic carbon content to volatile organic acid content (VFA/TAC), the concentration of short-chain fatty acids, the organic dry matter, the pH value, and the total nitrogen, phosphate, and ammonium concentrations were monitored. In addition, the gas quality (the percentages of CO₂, CH₄, and H₂) and the quantity of the produced gas were analyzed.
The investigations have exhibited feasible and economical production of biogas in a continuous process with energy cane as substrate. With a daily feeding rate of 1.68gᵥₛ/l*d the average specific gas formation rate was 0.5 m3/kgᵥₛ. The long-term study demonstrates a surprisingly fast metabolism of short-chain fatty acids. This indicates a stable and less susceptible process compared to other substrates.
This paper covers the use of the magnetic Wiegand effect to design an innovative incremental encoder. First, a theoretical design is given, followed by an estimation of the achievable accuracy and an optimization in open-loop operation.
Finally, a successful experimental verification is presented. For this purpose, a permanent magnet synchronous machine is controlled in a field-oriented manner, using the angle information of the prototype.
In positron emission tomography improving time, energy and spatial detector resolutions and using Compton kinematics introduces the possibility to reconstruct a radioactivity distribution image from scatter coincidences, thereby enhancing image quality. The number of single scattered coincidences alone is in the same order of magnitude as true coincidences. In this work, a compact Compton camera module based on monolithic scintillation material is investigated as a detector ring module. The detector interactions are simulated with Monte Carlo package GATE. The scattering angle inside the tissue is derived from the energy of the scattered photon, which results in a set of possible scattering trajectories or broken line of response. The Compton kinematics collimation reduces the number of solutions. Additionally, the time of flight information helps localize the position of the annihilation. One of the questions of this investigation is related to how the energy, spatial and temporal resolutions help confine the possible annihilation volume. A comparison of currently technically feasible detector resolutions (under laboratory conditions) demonstrates the influence on this annihilation volume and shows that energy and coincidence time resolution have a significant impact. An enhancement of the latter from 400 ps to 100 ps leads to a smaller annihilation volume of around 50%, while a change of the energy resolution in the absorber layer from 12% to 4.5% results in a reduction of 60%. The inclusion of single tissue-scattered data has the potential to increase the sensitivity of a scanner by a factor of 2 to 3 times. The concept can be further optimized and extended for multiple scatter coincidences and subsequently validated by a reconstruction algorithm.
Flight times to the heliopause using a combination of solar and radioisotope electric propulsion
(2011)
We investigate the interplanetary flight of a low-thrust space probe to the heliopause,located at a distance of about 200 AU from the Sun. Our goal was to reach this distance within the 25 years postulated by ESA for such a mission (which is less ambitious than the 15-year goal set by NASA). Contrary to solar sail concepts and combinations of allistic and electrically propelled flight legs, we have investigated whether the set flight time limit could also be kept with a combination of solar-electric propulsion and a second, RTG-powered upper stage. The used ion engine type was the RIT-22 for the first stage and the RIT-10 for the second stage. Trajectory optimization was carried out with the low-thrust optimization program InTrance, which implements the method of Evolutionary Neurocontrol,using Artificial Neural Networks for spacecraft steering and Evolutionary Algorithms to optimize the Neural Networks’ parameter set. Based on a parameter space study, in which the number of thrust units, the unit’s specific impulse, and the relative size of the solar power generator were varied, we have chosen one configuration as reference. The transfer time of this reference configuration was 29.6 years and the fastest one, which is technically
more challenging, still required 28.3 years. As all flight times of this parameter study were longer than 25 years, we further shortened the transfer time by applying a launcher-provided hyperbolic excess energy up to 49 km2/s2. The resulting minimal flight time for the reference configuration was then 27.8 years. The following, more precise optimization to a launch with the European Ariane 5 ECA rocket reduced the transfer time to 27.5 years. This is the fastest mission design of our study that is flexible enough to allow a launch every
year. The inclusion of a fly-by at Jupiter finally resulted in a flight time of 23.8 years,which is below the set transfer-time limit. However, compared to the 27.5-year transfer,this mission design has a significantly reduced launch window and mission flexibility if the
escape direction is restricted to the heliosphere’s “nose".
The absence of a general method for endotoxin removal from liquid interfaces gives an opportunity to find new methods and materials to overcome this gap. Activated nanostructured carbon is a promising material that showed good adsorption properties due to its vast pore network and high surface area. The aim of this study is to find the adsorption rates for a carboneous material produced at different temperatures, as well as to reveal possible differences between the performance of the material for each of the adsorbates used during the study (hemoglobin, serum albumin and lipopolysaccharide, LPS).
An H2O2 sensor for the application in industrial sterilisation processes has been developed. Therefore, automated sterilisation equipment at laboratory scale has been constructed using parts from industrial sterilisation facilities. In addition, a software tool has been developed for the control of the sterilisation equipment at laboratory scale. First measurements with the developed sensor set-up as part of the sterilisation equipment have been performed and the sensor has been physically characterised by optical microscopy and SEM.
Development of a subject-oriented reference process model for the telecommunications industry
(2016)
Generally the usage of reference models can be structured top-down or bottom-up. The practical need of agile change and flexible organizational implementation requires a consistent mapping to an operational level. In this context, well-established reference process models are typically structured top-down. The subject-oriented Business Process Management (sBPM) offers a modeling concept that is structured bottom-up and concentrates on the process actors on an
operational level. This paper applies sBPM to the enhanced Telecom Operations Map (eTOM), a well-accepted reference process model in the telecommunications industry. The resulting design artifact is a concrete example for a combination of a bottom-up and top-down developed reference model. The results are evaluated and confirmed in practical context through the involvement of the industry body TMForum.
In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.
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.
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.
With autonomous mobile robots receiving increased
attention in industrial contexts, the need for benchmarks
becomes more and more an urgent matter. The RoboCup
Logistics League (RCLL) is one specific industry-inspired scenario
focusing on production logistics within a Smart Factory.
In this paper, we describe how the RCLL allows to assess the
performance of a group of robots within the scenario as a
whole, focusing specifically on the coordination and cooperation
strategies and the methods and components to achieve them.
We report on recent efforts to analyze performance of teams in
2014 to understand the implications of the current grading
scheme, and derived criteria and metrics for performance
assessment based on Key Performance Indicators (KPI) adapted
from classic factory evaluation. We reflect on differences and
compatibility towards RoCKIn, a recent major benchmarking
European project.
New materials often lead to innovations and advantages in technical applications. This also applies to the particle receiver proposed in this work that deploys high-temperature and scratch resistant transparent ceramics. With this receiver design, particles are heated through direct-contact concentrated solar irradiance while flowing downwards through tubular transparent ceramics from top to bottom. In this paper, the developed particle receiver as well as advantages and disadvantages are described. Investigations on the particle heat-up characteristics from solar irradiance were carried out with DEM simulations which indicate that particle temperatures can reach up to 1200 K. Additionally, a simulation model was set up for investigating the dynamic behavior. A test receiver at laboratory scale has been designed and is currently being built. In upcoming tests, the receiver test rig will be used to validate the simulation results. The design and the measurement equipment is described in this work.
Development of open educational resources for renewable energy and the energy transition process
(2021)
The dissemination of knowledge about renewable energies is understood as a social task with the highest topicality. The transfer of teaching content on renewable energies into digital open educational resources offers the opportunity to significantly accelerate the implementation of the energy transition. Thus, in the here presented project six German universities create open educational resources for the energy transition. These materials are available to the public on the internet under a free license. So far there has been no publicly accessible, editable media that cover entire learning units about renewable energies extensively and in high technical quality. Thus, in this project, the content that remains up-to-date for a longer period is appropriately prepared in terms of media didactics. The materials enable lecturers to provide students with in-depth training about technologies for the energy transition. In a particular way, the created material is also suitable for making the general public knowledgeable about the energy transition with scientifically based material.
The problem of fair and privacy-preserving ordered set reconciliation arises in a variety of applications like auctions, e-voting, and appointment reconciliation. While several multi-party protocols have been proposed that solve this problem in the semi-honest model, there are no multi-party protocols that are secure in the malicious model so far. In this paper, we close this gap. Our newly proposed protocols are shown to be secure in the malicious model based on a variety of novel non-interactive zero-knowledge-proofs. We describe the implementation of our protocols and evaluate their performance in comparison to protocols solving the problem in the semi-honest case.
This work presents a methodology for automated
damage-sensitive feature extraction and anomaly
detection under multivariate operational variability
for in-flight assessment of wings. The
method uses a passive excitation approach, i. e.
without the need for artificial actuation. The
modal system properties (natural frequencies and
damping ratios) are used as damage-sensitive
features. Special emphasis is placed on the use
of Fiber Bragg Grating (FBG) sensing technology
and the consideration of Operational and
Environmental Variability (OEV). Measurements
from a wind tunnel investigation with a composite
cantilever equipped with FBG and piezoelectric
sensors are used to successfully detect an impact
damage. In addition, the feasibility of damage
localisation and severity estimation is evaluated
based on the coupling found between damageand
OEV-induced feature changes.
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.
Unsteady flow measurements in the wake behind a wind-tunnel car model by using high-speed planar PIV
(2015)
This study investigates unsteady characteristics of the wake behind a 28%-scale car model in a wind tunnel using highspeed planar particle image velocimetry (PIV). The car model is based on a hatchback passenger car that is known to have relatively high fluctuations in its aerodynamic loads. This study primarily focuses on the lateral motion of the flow on the horizontal plane to determine the effect of the flow motion on the straight-line stability and the initial steering response of the actual car on a track. This paper first compares the flow fields in the wake behind the above mentioned model obtained using conventional and high-speed planar PIV, with sampling frequencies of 8 Hz and 1 kHz, respectively. Large asymmetrically coherent flow structures, which fluctuate at frequencies below 2 Hz, are observed in the results of highspeed PIV measurements, whereas conventional PIV is unable to capture these features of the flow owing to aliasing. This flow pattern with a laterally swaying motion is represented by opposite signs of cross-correlation coefficients of streamwise velocity fluctuations for the two sides of the car model. Effects of two aerodynamic devices that are known to reduce the
fluctuation levels of the aerodynamic loads are then extensively investigated. The correlation analyses reveal that these devices indeed reduce the fluctuation levels of the flow and the correlation values around the rear combination-lamp, but it is found that the effects of these devices are different around the c-pillar.