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In this TDP we describe a new tool created for testing the strategy layer of our soccer playing agents. It is a complete 2D simulator that simulates the games based on the decisions of 22 agents. With this tool, debugging the decision and strategy layer of our agents is much more efficient than before due to various interaction methods and complete control over the simulation.
In the future, the tool could also serve as a measure to run simulations of game series much faster than with the 3D simulator. This way, the impact of different play strategies could be evaluated much faster than before.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
Process engineering focuses on the design, operation, control and optimization of chemical, physical and biological processes and has applications in many industries. Process Intensification is the key development approach in the modern process engineering. The proposed Advanced Innovation Design Approach (AIDA) combines the holistic innovation process with the systematic analytical and problem solving tools of the theory of inventive problem solving TRIZ. The present paper conceptualizes the AIDA application in the field of process engineering and especially in combination with the Process Intensification. It defines the AIDA innovation algorithm for process engineering and describes process mapping, problem ranking, and concept design techniques. The approach has been validated in several industrial case studies. The presented research work is a part of the European project “Intensified by Design® platform for the intensification of processes involving solids handling”.
The growing complexity in RF front-ends, which support carrier aggregation and a growing number of frequency bands, leads to tightened nonlinearity requirements in all sub-components. The generation of third order intermodulation products (IMD3) are typical problems caused by the non-linearity of SAW devices. In the present work, we investigate temperature compensating (TC) SAW devices on Lithium Niobate-rot128YX. An accurate FEM simulation model [1] is employed, which allows to better understand the origin of nonlinearities in such acoustic devices.
In the present work, nonlinearities in temperature compensating (TC) SAW devices are investigated. The materials used are LiNbO₃-rot128YX as the substrate and Copper electrodes covered with a SiO₂-layer as the compensating layer. In order to understand the role of these materials for the nonlinearities in such acoustic devices, a FEM simulation model in combination with a perturbation approach is applied. The nonlinear tensor data of the different materials involved in TC-SAW devices have been taken from literature, but were partially modified to fit experimental data by introducing scaling factors. An effective nonlinearity constant is determined by comparison of nonlinear P-matrix simulations to IMD3 measurements of test filters. By employing these constants in nonlinear periodic P-matrix simulations a direct comparison to nonlinear periodic FEM-simulations yields the scaling factors for the material used. Thus, the contribution of different materials to the nonlinear behavior of TC-SAW devices is obtained and the role of metal electrodes is discussed in detail.
Our university carries out various research projects. Among others, the project Schluckspecht is an interdisciplinary work on different ultra-efficient car concepts for international contests. Besides the engineering work, one part of the project deals with real-time data visualization. In order to increase the efficiency of the vehicle, an online monitoring of the runtime parameters is necessary. The driving parameters of the vehicle are transmitted to a processing station via a wireless network connection. We plan to use an augmented reality (AR) application to visualize different data on top of the view of the real car. By utilizing a mobile Android or iOS device a user can interactively view various real-time and statistical data. The car and its components are meant to be augmented by various additional information, whereby that information should appear at the correct position of the components. An engine e.g. could show the current rpm and consumption values. A battery on the other hand could show the current charge level. The goal of this paper is to evaluate different possible approaches, their suitability and to expand our application to other projects at our university.
Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
Gaps in basic math knowledge are among the biggest obstacles to a successful start in university. Students starting their studies in STEM disciplines display significant diversity, “math anxiety” is a widespread phenomenon, and the transition to a self-determined way of studying presents a huge challenge. Universities offer support measures such as preparatory courses. Over the years, Offenburg University realized that with increased diversity, traditional ways of teaching in front of the class have become inefficient. The majority of the students remained inactive and just listened to the teachers’ explanations and the few active participants’ answers.
Since 2013 our new course concept fosters a shift from teaching to active learning on a large scale, involving several hundred participants of our on-site preparatory math courses. This switch to broad active practicing, however, must go hand in hand with providing individual support for an increasingly diverse student body. Meanwhile students bring along their mobile devices, and the training App TeachMatics serves as a facilitator. The course concept has been very well received by both students and teachers.
This paper describes the Sweaty II humanoid adult size robot trying to qualify for the RoboCup 2017 adult size humanoid competition. Sweaty came 2nd in RoboCup 2016 adult size league. The paper describes the main characteristics of Sweaty that made this success possible, and improvements that have been made or are planned to be implemented for RoboCup 2017.
Technology and computer applications influence our daily lives and questions arise concerning the role of artificial intelligence and decision-making algorithms. There are warning voices, that computers can, in theory, emulate human intelligence-and exceed it. This paper points out that a replacement of humans by computers is unlikely, because human thinking is characterized by cognitive heuristics and emotions, which cannot simply be implemented in machines operating with algorithms, procedural data processing or artificial neural networks. However, we are going to share our responsibilities with superior computer systems, which are tracking and surveying all of our digital activities, whereas we have no idea of the decision-making processes inside the machines. It is shown that we need a new digital humanism defining rules of computer responsibilities to avoid digital totalism and comprehensive monitoring and controlling of individuals within the planet Earth.
In this paper we show that a model-free approach to learn behaviors in joint space can be successfully used to utilize toes of a humanoid robot. Keeping the approach model-free makes it applicable to any kind of humanoid robot, or robot in general. Here we focus on the benefit on robots with toes which is otherwise more difficult to exploit. The task has been to learn different kick behaviors on simulated Nao robots with toes in the RoboCup 3D soccer simulator. As a result, the robot learned to step on its toe for a kick that performs 30% better than learning the same kick without toes.
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products (e.g., fuel cells, metal/air cells, electrolyzers) offer an additional observable, that is, the gas pressure. The dynamic coupling of current and/or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. This sensitivity can be exploited for model parameterization and validation. A general analysis of EPIS is presented, which shows the necessity of model-based interpretation of the complex EPIS shapes in the Nyquist plot (cf. Figure). We then present EPIS simulations for two different electrochemical cells: (1) a sodium/oxygen battery cell and (2) a hydrogen/air fuel cell. We use 1D or 2D electrochemical and transport models to simulate current excitation/pressure detection or pressure excitation/voltage detection. The results are compared to first EPIS experimental data available in literature [2,3].
Background: Cardiac resynchronization therapy (CRT) with biventricular (BV) pacing is an established therapy for heart failure (HF) patients (P) with sinus rhythm, reduced left ventricular (LV) ejection fraction (EF) and electrical ventricular desynchronization. The aim of the study was to evaluate electrical interventricular delay (IVD) and left ventricular delay (LVD) in right ventricular (RV) pacemaker pacing before upgrading to CRT BV pacing.
Methods: HF P (n=11, age 69.0 ± 7.9 years, 1 female, 10 males) with DDD pacemaker (n=10), DDD defibrillator (n=1), RV pacing, New York Heart Association (NYHA) class 3.0 ± 0.2 and 24.5 ± 4.9 % LVEF were measured by surface ECG and transesophageal bipolar LV ECG before upgrading to CRT defibrillator (n=8) and CRT pacemaker (n=3). IVD was measured between onset of QRS in the surface ECG and onset of LV signal in the transesophageal ECG. LVD was measured between onset and offset of LV signal in the transesophageal ECG. CRT atrioventricular (AV) and BV pacing delay were optimized by impedance cardiography.
Results: Interventricular and intraventricular desynchronization in RV pacemaker pacing were 228.2 ± 44.8 ms QRS duration, 86.5 ± 32.8ms IVD, 94.4 ± 23.8ms LVD, 2.6 ± 0.8 QRS-IVD-ratio with correlation between IVD and QRS-IVD-ratio (r=-0.668 P=0.0248) and 2.3 ± 0.7 QRS-LVD-ratio. The LVEF-IVD-ratio was 0.3 ± 0.1 with correlation between IVD and LVEF-IVD-ratio (r=-0.8063 P=0.00272) and with correlation between QRS duration and LVEF-IVD-ratio (r=-0.7251 P=0.01157). Optimal sensing and pacing AV delay were 128.3 ± 24.8 ms AV delay after atrial sensing (n=6) and 173.3 ± 40.4 ms AV delay after atrial pacing (n=3). Optimal BV pacing delay was -4.3 ± 11.3 ms between LV and RV pacing (n=7). During 30.4 ± 29.6 month CRT follow-up, the NYHA class improved from 3.1 ± 0.2 to 2.2 ± 0.3.
Conclusions: Transesophageal electrical IVD and LVD in RV pacemaker pacing may be additional useful ventricular desynchronization parameters to improve P selection for upgrading RV pacemaker pacing to CRT BV pacing.
The need to measure basic aerosol parameters has increased dramatically in the last decade. This is due mainly to their harmful effect on the environment and on public health. Legislation requires that particle emissions and ambient levels, workplace particle concentrations and exposure to them are measured to confirm that the defined limits are met and the public is not exposed to harmful concentrations of aerosols.