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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.
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 paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. In comparison with the engineers, the students often demonstrate lower motivation in learning systematic inventive techniques, like for example TRIZ methodology, and prefer random brainstorming for idea generation. The quality of obtained solutions also depends on the level of completeness of the problem analysis, which is more complex and time consuming in the case of interdisciplinary systems. The paper briefly describes one-semester-course of 60 hours in new product development with the Advanced Innovation Design Approach and TRIZ methodology, in which a typical industrial innovation process for one selected interdisciplinary mechatronic product is modelled.
In the course of the last few years, our students are becoming increasingly unhappy. Sometimes they stop attending lectures and even seem not to know how to behave correctly. It feels like they are getting on strike. Consequently, drop-out rates are sky-rocketing. The lecturers/professors are not happy either, adopting an “I-don’t-care” attitude.
An interdisciplinary, international team set in to find out: (1) What are the students unhappy about? Why is it becoming so difficult for them to cope? (2) What does the “I-don’t-care” attitude of professors actually mean? What do they care or not care about? (3) How far do the views of the parties correlate? Could some kind of mutual understanding be achieved?
The findings indicate that, at least at our universities, there is rather a long way to go from “Engineering versus Pedagogy” to “Engineering Pedagogy”.
Viele hochbeanspruchte Bauteile müssen zur Erfüllung ihres konstruktiven Zwecks mit Durchdringungskerben versehen werden. Infolge der gegenseitigen Wechselwirkung gelten für die Kerbwirkung dieser Art von Mehrfachkerben andere Gesetzmäßigkeiten als bei Einzelkerben. Die Weiterentwicklung der Lehre von der Tragfähigkeitsberechnung höchstbeanspruchter Maschinenelemente macht es notwendig, sich mit der Durchdringungskerbwirkung eingehend zu befassen. Thum und Svenson [1] entwickelten im Jahr 1949 ein Näherungsverfahren zur Abschätzung der Formzahl an einem zugbelasteten Stab mit Durchdringungskerben. In vielen Lehrbüchern findet dieses Verfahren Anwendung. Aus heutiger Sicht erscheint die Eignung der aus diesem Ansatz erzielten Ergebnisse als dringend überprüfungswürdig. Das thum’sche Verfahren wird unter die Lupe genommen. Der hier vorliegende Beitrag präsentiert mit Hilfe der Finiten-Elemente-Methode (FEM) neue Untersuchungsergebnisse an zugbeanspruchten Stäben mit Halbkreisnut und überlagerter Querbohrung. Diese ergaben, dass die Berechnung nach [1] Lücken aufweist. Ihr Ansatz stellt für den heutigen Entwicklungsstand eine mit zu großen Abweichungen behaftete Näherungshypothese dar.
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.
For the RoboCup Soccer AdultSize League the humanoid robot Sweaty uses a single fully convolutional neural network to detect and localize the ball, opponents and other features on the field of play. This neural network can be trained from scratch in a few hours and is able to perform in real-time within the constraints of computational resources available on the robot. The time it takes to precess an image is approximately 11 ms. Balls and goal posts are recalled in 99 % of all cases (94.5 % for all objects) accompanied by a false detection rate of 1.2 % (5.2 % for all). The object detection and localization helped Sweaty to become finalist for the RoboCup 2017 in Nagoya.
One of the challenges in humanoid robotics is motion control. Interacting with humans requires impedance control algorithms, as well as tackling the problem of the closed kinematic chains which occur when both feet touch the ground. However, pure impedance control for totally autonomous robots is difficult to realize, as this algorithm needs very precise sensors for force and speed of the actuated parts, as well as very high sampling rates for the controller input signals. Both requirements lead to a complex and heavy weight design, which makes up for heavy machines unusable in RoboCup Soccer competitions.
A lightweight motor controller was developed that can be used for admittance and impedance control as well as for model predictive control algorithms to further improve the gait of the robot.
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.
Wie man die Vorlesung "Technische Mechanik 1 - Statik" für alle Beteiligten dynamisch gestaltet
(2017)
Lehrende nehmen vielfältige Veränderungen, insbesondere bei Studienanfängern wahr: Vorkenntnisse, Aufnahme- und Konzentrationsfähigkeit werden zunehmend heterogener. In der Vorlesung „Technische Mechanik 1“ wurde darauf konstruktiv reagiert, indem der Ablauf und die Struktur verändert wurden. Aufgaben und ihre Lösungen stehen im Mittelpunkt des Unterrichts. Neben der Lehrenden als aktiv Handelnde wird jeder Studierende im Lauf des Semesters in den Ablauf integriert und muss individuelle Lösungen der verteilten Aufgaben präsentieren. Im Vergleich entwickeln die Studierenden durch „Lernen am Modell“ dadurch ihre methodischen und fachlichen Fähigkeiten weiter. Um den Studierenden die Relevanz der behandelten Themenbereiche zu verdeutlichen wurden spezielle Aufgaben mit einem lebensweltlichem Bezug entwickelt. Befragungen zeigen, dass die Studierenden von den vielfältigen interaktiven Lernangeboten profitieren und die entwickelten Kompetenzen auch auf andere Lernsituationen übertragen.
Modelling and Simulation of Microscale Trigeneration Systems Based on Real- Life Experimental Data
(2017)
For the shift of the energy grid towards a smarter decentralised system flexible microscale trigeneration systems will play an important role due to their ability to support the demand side management in buildings. However to harness their potential modern control methods like model predictive control must be implemented for their optimal scheduling and control. To implement such supervisory control methods, first, simple analytical models representing the behaviour of the components need to be developed. At the Institute of Energy System Technologies in Offenburg we have built a real-life microscale trigeneration plant and present in this paper the models based on experimental data. These models are qualitatively validated and their application in the future for the optimal scheduling problem is briefly motivated.
Microscale trigeneration systems are highly flexible in their operation and thus offer the technical possibility for peak load shifting in building demand side management. However to harness their potential modern control methods such as model predictive control must be implemented for their optimal scheduling. In literature the need for experimental investigation of microscale trigeneration systems to identify typical characteristics of the components and their interactions has been identified. On a real-life setup control specific information of the components is collected and lessons learnt during commissioning of the equipment is shared. The data is analysed to draw the vital characteristics of the system and it will be used for creating models of the components that can be utilised for optimal control.