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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”.
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.
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.
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.
Additive manufacturing processes have evolved rapidly in recent years and now offer a wide range of manufacturing technologies and workable materials. This range from plastics and metals to paper and even polymer plaster composites. Due to the layer by layer structure of the components the additive processes have in comparison with conventional manufacturing processes the advantage of freedom of design, that means the simple implementation of complex geometries. Moreover, the additive processes provide the advantage of reduced consumption of resources, since essentially only the material is consumed, which is required for the actual component, since no waste in the form of chips is produced. In order to use these advantages, the potentials of additive manufacturing and the requirements of sustainable design must already be observed in the product development process. So the design of the components and products must be made so as little as possible construction and supporting material is required for the generative production and therefore little resources are consumed. Also, all steps of the additive manufacturing process must be considered properly, that includes the post processing. This allows components be designed so that for instance the effort for removing the support structure is considerably reduced. This leads to a significant reduction in manufacturing time and thus energy consumption. The implementation of these potentials in product development can be demonstrated by means of a multiple-stages model. A case study shows how this model is applied in the training of Master students in the field of product development. In a workshop the students work as a group while implementing the task of developing a miniature racing car under the rules of sustainable design in compliance with the boundary conditions for an additive manufacturing. In this case, Fused Deposition Modelling FDM using plastics as a building material is applied. The results show how the students have dealt with the different requirements and how they have implemented them in product development and in the subsequent additive manufacturing.
The present-day methods of numerical simulation offer a great variety of options for optimizing metal forming processes. Although it is possible to simulate complex forming processes, the results are typically available only as 2D projections on screens. Some forming processes have reached a level of complexity beyond the level of spatial sense, which makes it necessary to use physical 3D representations to develop a deeper understanding of the material flow, microstructural processes, process and design limits, or to design the required tooling. Physical 3D models can be produced in a short amount of time using 3D printing, and indexed with a wide range of colors. In this paper, the additive manufacturing of 3D color models based on simulation results are explored by means of examples from metal forming. Different 3D-printing processes are compared on the basis of quality as well as technical and economic criteria. Other examples from the fields joining by upset-bulging of tubes and microstructure simulation are also analyzed. This paper discusses the possibilities offered by the rapid progress and wide availability of 3D printers for the design and optimization of complex metal forming processes.
Architecture models are an essential component of the development process and enable a physical representation of virtual designs. In addition to the conventional methods of model production using the machining of models made of wood, metal, plastic or glass, a number of additive manufacturing processes are now available. These new processes enable the additive manufacturing of architectural models directly from CAAD or BIM data. However, the boundary conditions applicable to the ability to manufacture models with additive manufacturing processes must also be considered. Such conditions include the minimum wall thickness, which depends on the applied additive manufacturing process and the materials used. Moreover, the need for the removal of support structures after the additive manufacturing process must also be considered. In general, a change in the scale of these models is only possible at very high effort. In order to allow these restrictions to be adequately incorporated into the CAAD model, this contribution develops a parametrized CAAD model that allows such boundary conditions to be modified and adapted while complying with the scale. Usability of this new method is illustrated and explained in detail in a case study. In addition, this article addresses the additive manufacturing processes including subsequent post-processing.
Implementation of lightweight design in the product development process of unmanned aerial vehicles
(2017)
The development and manufacturing of unmanned aerial vehicles (UAVs) require a multitude of design rules. Thereby, additive manufacturing (AM) processes provide a number of significant advantages over conventional production methods, particularly for implementing requirements with regard to lightweight construction and sustainability. A new, promising approach is presented, with which, through the combination of very light structural elements with a ribbed construction, an attached covering by means of foil is used. This contribution develops and presents a development process that is based on various development cycles. Such cycles differ in their effort and scope within the overall development, and may only comprise one part of the development process, or the entire development process. The applicability of this development process is demonstrated within the framework of a comprehensive case study. The aim is to develop an additively manufactured product that is as light as possible in the form of a UAV, along with a sustainable manufacturing process for such product. Finally, the results of this case study are analyzed with regard to the improvement of lightweight construction.
In this paper we present the implementation of a model-predictive controller (MPC) for real-time control of a cable-robot-based motion simulator. The controller computes control inputs such that a desired acceleration and angular velocity at a defined point in simulator’s cabin are tracked while satisfying constraints imposed by working space and allowed cable forces of the robot. In order to fully use the simulator capabilities, we propose an approach that includes the motion platform actuation in the MPC model. The tracking performance and computation time of the algorithm are investigated in computer simulations. Furthermore, for motion simulation scenarios where the reference trajectories are not known beforehand, we derive an estimate on how much motion simulation fidelity can maximally be improved by any reference prediction scheme compared to the case when no prediction scheme is applied.
Applications helping us to maintain the focus on work are called “Zenware” (from concentration and Zen). While form factors, use cases and functionality vary, all these applications have a common goal: creating uninterrupted, focused attention on the task at hand. The rise of such tools exemplifies the users’ desire to control their attention within the context of omnipresent distraction. In expert interviews we investigate approaches in the context of attention-management at the workplace of knowledge workers. To gain a broad understanding, we use judgement sampling in interviews with experts from several disciplines. We especially explore how focus and flow can be stimulated. Our contribution has four components: a brief overview on the state of the art (1), a presentation of the results (2), strategies for coping with digital distractions and design guidelines for future Zenware (3) and an outlook on the overall potential in digital work environments (4).
We present the design outline of a context-aware interactive system for smart learning in the STEM curriculum (science, technology, engineering, and mathematics). It is based on a gameful design approach and enables "playful coached learning" (PCL): a learning process enriched by gamification but also close to the learner's activities and emotional setting. After a brief introduction on related work, we describe the technological setup, the integration of projected visual feedback and the use of object and motion recognition to interpret the learner's actions. We explain how this combination enables rapid feedback and why this is particularly important for correct habit formation in practical skills training. In a second step, we discuss gamification methods and analyze which are best suited for the PCL system. Finally, emotion recognition, a major element of the final PCL design not yet implemented, is briefly outlined.
Designing Authentic Emotions for Non-Human Characters. A Study Evaluating Virtual Affective Behavior
(2017)
While human emotions have been researched for decades, designing authentic emotional behavior for non-human characters has received less attention. However, virtual behavior not only affects game design, but also allows creating authentic avatars or robotic companions. After a discussion of methods to model and recognize emotions, we present three characters with a decreasing level of human features and describe how established design techniques can be adapted for such characters. In a study, 220 participants assess these characters' emotional behavior, focusing on the emotion "anger". We want to determine how reliable users can recognize emotional behavior, if characters increasingly do not look and behave like humans. A secondary aim is determining if gender has an impact on the competence in emotion recognition. The findings indicate that there is an area of insecure attribution of virtual affective behavior not distant but close to human behavior. We also found that at least for anger, men and women assess emotional behavior equally well.
Gamifying rehabilitation is an efficient way to improve motivation and exercise frequency. However, between flow theory, self-determination theory or Bartle's player types there is much room for speculation regarding the mechanics required for successful gamification, which in turn leads to increased motivation. For our study, we selected a gamified solution for motion training (an exergame) where the playful design elements are extremely simple. The contribution is three-fold: we show best practices from the state of the art, present a study analyzing the effects of simple gamification mechanics on a quantitative and on a qualitative level and discuss strategies for playful design in therapeutic movement games.