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Sweaty has already participated four times in RoboCup soccer competitions (Adult Size) and came second three times. While 2016 Sweaty needed a lot of luck to be finalist, 2017 Sweaty was a serious adversary in the preliminary rounds. In 2018 Sweaty showed up in the final with some lack of experience and room for improvements, but not without any chance. This paper describes the intended improvements of the humanoid adult size robot Sweaty in order to qualify for the RoboCup 2019 adult size competition.
More than 200 years ago, the scientist Alexander von Humboldt noted in his travel diaries that "everything is interconnectedness", when he was fascinated by nature and the phenomena observed. The view of nature has become much more detailed through the knowledge of phenomena and natural processes, which led to a more precise view of nature shaped by Humboldt. Technological progress and the artificial intelligence of highly developed computer systems are upsetting this view and changing the established world view through a new, unprecedented interaction between man and machinery. Thus we need digital axioms and comprehensive rules and laws for such autonomous acting systems that determine human interaction between cybernetic systems and biological individuals. This digital humanism should encompass our relationship to nature, our handling of the complexity and diversity of nature and the technological influences on society in order to avoid technical colonialism through supercomputers.
Process engineering industries are now facing growing economic pressure and societies' demands to improve their production technologies and equipment, making them more efficient and environmentally friendly. However unexpected additional technical and ecological drawbacks may appear as negative side effects of the new environmentally-friendly technologies. Thus, in their efforts to intensify upstream and downstream processes, industrial companies require a systematic aid to avoid compromising of ecological impact. The paper conceptualises a comprehensive approach for eco-innovation and eco- design in process engineering. The approach combines the advantages of Process Intensification as Knowledge-Based Engineering (KBE), inventive tools of Knowledge-Based Innovation (KBI), and main principles and best-practices of Eco-Design and Sustainable Manufacturing. It includes a correlation matrix for identification of eco-engineering contradictions and a process mapping technique for problem definition, database of Process Intensification methods and equipment, as well as a set of strongest inventive operators for eco-ideation.
As engineering graduates and specialists frequently lack the advanced skills and knowledge required to run eco-innovation systematically, the paper proposes a new teaching method and appropriate learning materials in the field of eco-innovation and evaluates the learning experience and outcomes. This programme is aimed at strengthening student’s skills and motivation to identify and creatively overcome secondary eco-contradictions in case if additional environmental problems appears as negative side effects of eco-friendly solutions.
Based on a literature analysis and own investigations, authors propose to introduce a manageable number of eco-innovation tools into a standard one-semester design course in process engineering with particular focus on the identification of eco-problems in existing technologies, selection of the appropriate new process intensification technologies (knowledge-based engineering), and systematic ideation and problem solving (knowledge-based innovation and invention).
The proposed educational approach equips students with the advanced knowledge, skills and competences in the field of eco-innovation. Analysis of the student’s work allows one to recommend simple-to-use tools for a fast application in process engineering, such as process mapping, database of eco-friendly process intensification technologies, and up to 20 strongest inventive operators for solving of environmental problems. For the majority of students in the survey, even the small workload has strengthened their self-confidence and skills in eco-innovation
Growing demands for cleaner production and higher eco-efficiency in process engineering require a comprehensive analysis of technical and environmental outcomes of customers and society. Moreover, unexpected additional technical or ecological drawbacks may appear as negative side effects of new environ-mentally friendly technologies. The paper conceptualizes a comprehensive ap-proach for analysis and ranking of engineering and ecological requirements in process engineering in order to anticipate secondary problems in eco-design and to avoid compromising the environmental or technological goals. For this purpose, the paper presents a method based on integration of the Quality Func-tion Deployment approach with the Importance-Satisfaction Analysis for the requirements ranking. The proposed method identifies and classifies compre-hensively the potential engineering and eco-engineering contradictions through analysis of correlations within requirements groups such as stakehold-er requirements (SRs) and technical requirements (TRs), and additionally through cross-relationship between SRs and TRs.
The 40 Altshuller Inventive Principles with numerous sub-principles remain over decades the most frequently applied tool of the Theory of Inventive Problem Solving TRIZ for systematic idea generation. However, their application often requires a concentrated, creative and abstract way of thinking that can be fairly challenging for the newcomers to TRIZ. This paper describes an approach to reduce the abstraction level of inventive sub-principles and presents the results of the idea generation experiment conducted with three groups of undergraduate and graduate students from different years of study in mechanical and process engineering. The students were asked to generate and to record their individual ideas for three design problems using a pre-defined set of classical and modified sub-principles within 10 minutes. The overall outcomes of the experiment support the assumption that the less abstract wording of the modified sub-principles leads to higher number of ideas. The distribution of ideas between the fields of MATCHEM-IBD (Mechanical, Acoustic, Thermal, Chemical, Electrical, Magnetic, Intermolecular, Biological and Data processing) differs significantly between groups using modified and abstract sub-principles.
In this article we outline the model development planned within the joint projectModel-based city planningand application in climate change (MOSAIK). The MOSAIK project is funded by the German FederalMinistry of Education and Research (BMBF) within the frameworkUrban Climate Under Change ([UC]2)since 2016. The aim of MOSAIK is to develop a highly-efficient, modern, and high-resolution urban climatemodel that allows to be applied for building-resolving simulations of large cities such as Berlin (Germany).The new urban climate model will be based on the well-established large-eddy simulation code PALM, whichalready has numerous features related to this goal, such as an option for prescribing Cartesian obstacles. Inthis article we will outline those components that will be added or modified in the framework of MOSAIK.Moreover, we will discuss the everlasting issue of acquisition of suitable geographical information as inputdata and the underlying requirements from the model's perspective.
Classification of TRIZ Inventive Principles and Sub-Principles for Process Engineering Problems
(2019)
The paper proposes a classification approach of 40 Inventive Principles with an extended set of 160 sub-principles for process engineering, based on a thorough analysis of 155 process intensification technologies, 200 patent documents, 6 industrial case studies applying TRIZ, and other sources. The authors define problem-specific sub-principles groups as a more precise and productive ideation technique, adaptable for a large diversity of problem situations, and finally, examine the anticipated variety of ideation using 160 sub-principles with the help of MATCEM-IBD fields.
We present a planar chromatographic separation method for the compounds caffeine, artemisinin, and equol, separated on high-performance thin-layer chromatography (HPTLC) silica gel plates. As solvents for separation, methyl t-butyl ether and cyclohexane (1:1, V/V) have been used for equol, cyclohexane and ethyl acetate (7:3, V/V) for artemisinin, and ethyl acetate and acetone (7:3, V/V) for caffeine. After separation, the plate was scanned with a very specific time of flight-direct analysis in real time-mass spectrometry (TOF-DART-MS) system using the (M + 1)+ signals of equol, artemisinin, and caffeine. The (M + 1) peak of artemisinin at 283.13 m/z is clearly detectable, which is the proof that DART-MS is applicable for the quantitative determination of rather instable molecules. The planar set-up of DART source, HPTLC plate and detector inlet in a line showed higher sensitivities compared to desorption at an angle. The optimal detector voltage increases with the molar mass of the analyte, thus an individual determination of optimal detector voltage setting for the different analyte is recommended to achieve the best possible measurement conditions. In conclusion, DART-MS detection in combination with an HPTLC separation allows very specific quantification of all three compounds.
The ability to change aerodynamic parameters of airfoils during flying can potentially save energy as well as reducing the noise made by the unmanned aerial vehicles (UAV) because of sharp edges of the airfoil and its rudders. In this paper, an approach for the design of an adaptive wing using a multi-material 3D printer is shown. In multi-material 3D printing, up to six different materials can be combined in one component. Thus, the user can determine the mixture and the spatial arrangement of this “digital material” in advance in the pre-processing software. First, the theoretical benefits of adaptive wings are shown, and already existing adaptive wings and concepts are explicated within a literature review. Then the additive manufacturing process using photopolymer jetting and its capabilities to print multiple materials in one part are demonstrated. Within the scope of a case study, an adaptive wing is developed and the necessary steps for the product development and their implementation in CAD are presented. This contribution covers the requirements for different components and sections of an adaptive wing designed for additive manufacturing using multiple materials as well as the single steps of development with its different approaches until the final design of the adaptive wing. The developed wing section is simulated, and qualitative tests in a wind tunnel are carried out with the wing segment. Finally, the additively manufactured wing segment is evaluated under technical and economic aspects.
Modeling and simulation play a key role in analyzing the complex electrochemical behavior of lithium-ion batteries. We present the development of a thermodynamic and kinetic modeling framework for intercalation electrochemistry within the open-source software Cantera. Instead of using equilibrium potentials and single-step Butler-Volmer kinetics, Cantera is based on molar thermodynamic data and mass-action kinetics, providing a physically-based and flexible means for complex reaction pathways. Herein, we introduce a new thermodynamic class for intercalation materials into the open-source software. We discuss the derivation of molar thermodynamic data from experimental half-cell potentials, and provide practical guidelines. We then demonstrate the new class using a single-particle model of a lithium cobalt oxide/graphite lithium-ion cell, implemented in MATLAB. With the present extensions, Cantera provides a platform for the lithium-ion battery modeling community both for consistent thermodynamic and kinetic models and for exchanging the required thermodynamic and kinetic parameters. We provide the full MATLAB code and parameter files as supplementary material to this article.
Model-based analysis of Electrochemical Pressure Impedance Spectroscopy (EPIS) for PEM Fuel Cells
(2019)
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, in particular fuel cells, offer an additional observable, that is, the gas pressure. The dynamic coupling of current or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have previously 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. First EPIS experiments on PEM fuel cells have recently been shown [3].
We present a detailed modeling and simulation analysis of EPIS of a PEM fuel cell. We use a 1D+1D continuum model of a fuel/air channel pair with GDL and MEA. Backpressure is dynamically varied, and the resulting simulated oscillation in cell voltage is evaluated to yield the ▁Z_( V⁄p_ca ) EPIS signal. Results are obtained for different transport situations of the fuel cell, giving rise to very complex EPIS shapes in the Nyquist plot. This complexity shows the necessity of model-based interpretation of the complex EPIS shapes. Based on the simulation results, specific features in the EPIS spectra can be assigned to different transport domains (gas channel, GDL, membrane water transport).
This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics model of a 350 mAh high-power lithium-ion pouch cell with graphite anode and lithium cobalt oxide/lithium nickel cobalt aluminum oxide (LCO/NCA) blend cathode. The model describes transport processes on three different scales: Heat transport on the macroscopic scale (cell), mass and charge transport on the mesoscopic scale (electrode pair), and mass transport on the microscopic scale (active material particles). A generalized description of electrochemistry in blend electrodes is developed, using the open-source software Cantera for calculating species source terms. Very good agreement of model predictions with galvanostatic charge/discharge measurements, electrochemical impedance spectroscopy, and surface temperature measurements is observed over a wide range of operating conditions (0.05C to 10C charge and discharge, 5°C to 35°C). The behavior of internal states (concentrations, potentials, temperatures) is discussed. The blend materials show a complex behavior with both intra-particle and inter-particle non-equilibria during cycling.
Tryptamines can occur naturally in plants, mushrooms, microbes, and amphibians. Synthetic tryptamines are sold as new psychoactive substances (NPS) because of their hallucinogenic effects. When it comes to NPS, metabolism studies are of crucial importance, due to the lack of pharmacological and toxicological data. Different approaches can be taken to study in vitro and in vivo metabolism of xenobiotica. The zygomycete fungus Cunninghamella elegans (C. elegans) can be used as a microbial model for the study of drug metabolism. The current study investigated the biotransformation of four naturally occurring and synthetic tryptamines [N,N‐Dimethyltryptamine (DMT), 4‐hydroxy‐N‐methyl‐N‐ethyltryptamine (4‐HO‐MET), N,N‐di allyl‐5‐methoxy tryptamine (5‐MeO‐DALT) and 5‐methoxy‐N‐methyl‐N‐isoporpoyltryptamine (5‐MeO‐MiPT)] in C. elegans after incubation for 72 hours. Metabolites were identified using liquid chromatography–high resolution–tandem mass spectrometry (LC–HR–MS/MS) with a quadrupole time‐of‐flight (QqTOF) instrument. Results were compared to already published data on these substances. C. elegans was capable of producing all major biotransformation steps: hydroxylation, N‐oxide formation, carboxylation, deamination, and demethylation. On average 63% of phase I metabolites found in the literature could also be detected in C. elegans. Additionally, metabolites specific for C. elegans were identified. Therefore, C. elegans is a suitable complementary model to other in vitro or in vivo methods to study the metabolism of naturally occurring or synthetic tryptamines.
The development of new processes and materials for additive manufacturing is currently progressing rapidly. In order to use the advantages of additive manufacturing, however, product development and design must also be adapted to these new processes. Therefore it is suitable to use structural optimization. To achieve the best results in lightweight design, it is important to have an approach that reduces the volume in the unloaded regions and considers the restrictions and characteristics of the additive manufacturing process. In this contribution, a case study using a humanoid robot is presented. Thus, the pelvis module of a humanoid robot is optimized regarding its weight and stiffness. Furthermore, an integrated design is implemented in order to reduce the number of parts and the screw connections. The manufacturing uses a new aluminum-based material that has been specially developed for use in additive manufacturing and lightweight construction. For the additive manufacturing by means of the Selective Laser Melting (SLM) process, different restrictions and the assembly concepts of the humanoid robot have to be taken into account. These restrictions have to be considered in the setting of the individual parameters and target functions of the structural optimization. As a result, a framework is presented that shows the steps of the redesign and the optimization of the pelvis module. In order to achieve high accuracy with the product, the redesign of the pelvis module is demonstrated with regard to mechanical and thermal postprocessing. Finally, the redesigned part and the different assembly concepts are compared to analyze the economic and technical effects of the optimization.
With the growing share of renewable energies in the electricity supply, transmission and distribution grids have to be adapted. A profound understanding of the structural characteristics of distribution grids is essential to define suitable strategies for grid expansion. Many countries have a large number of distribution system operators (DSOs) whose standards vary widely, which contributes to coordination problems during peak load hours. This study contributes to targeted distribution grid development by classifying DSOs according to their remuneration requirement. To examine the amendment potential, structural and grid development data from 109 distribution grids in South-Western Germany, are collected, referring to publications of the respective DSOs. The resulting data base is assessed statistically to identify clusters of DSOs according to the fit of demographic requirements and grid-construction status and thus identify development needs to enable a broader use of regenerative energy resources. Three alternative algorithms are explored to manage this task. The study finds the novel Gauss-Newton algorithm optimal to analyse the fit of grid conditions to regional requirements and successfully identifies grids with remuneration needs. It is superior to the so far used K-Means algorithm. The method developed here is transferable to other areas for grid analysis and targeted, cost-efficient development.
As part of the design education at Offenburg University, the teaching in technical documentation is continuously optimised. In this study, numerous mechanical engineering students, ages 19 to 29, are observed using the eye tracking technology and a video camera while performing various design exercises. The aim of the study is to enhance the students’ ability to read, understand and analyse complex engineering drawings. In one experiment, the students are asked to perform the “cube perspective test” after Stumpf and Fay to assess their ability for mental rotation as part of spatial visualization ability. Furthermore, the students are asked to prepare and give micro presentations on a topic related to their studies. Students have a maximum of 100 s time for these presentations. Thus, they can practise presenting important information in a short amount of time, show their rhetorical skills and demonstrate their acquisition of basic knowledge. During the presentation, the eye movement of a few selected students is recorded to analyse their information acquisition. In a further test, the students’ eye movements are analysed while reading an engineering drawing that consists of multiple views. All the spatial connections have to be included based on the different component views. Including these and their acquired knowledge, the students are asked to identify the correct representation of a component view. Furthermore the subjects are describing the function of an assembly, a parallel gripper and then they are to mentally disassemble the assembly to replace a damaged cylindrical pin. Simultaneously, they are filmed using a video camera to see which terms the students use for the individual technical terms. The evaluation of the eye movements shows that the increasing digitalisation of society and the use of electronic devices in everyday life lead to fast and only selective perceptual behaviour and that students feel insecure when dealing with technical drawings. The analysis of the videos shows a mostly non-technical and inaccurate manner of expression and a poor use of technical terms. The transferability of the achieved results to other technical tasks is part of further investigations.
Hot working tools are subjected to complex thermal and mechanical loads during service. Locally, the stresses can exceed the material’s yield strength in highly loaded areas. During production, this causes cyclic plastic deformation and thus thermomechanical fatigue, which can significantly shorten the lifetime of hot working tools. To sustain this high loads, the hot working tools are typically made of tempered martensitic hot work tool steels. While the annealing temperatures of the tool steels usually lie in the range of 400 to 600 °C, the steels may experience even higher temperatures during hot working, resulting in softening of the material due to changes in microstructure. Therefore, the temperature-dependent cyclic mechanical properties of the frequently used hot work tool steel 1.2367 (X38CrMoV5-3) after tempering are investigated in this work. To this end, hardness measurements are performed. Furthermore, the Institute of Forming Technology and Machines (IFUM) provides test results from cyclic tests at temperatures ranging from 20 °C (room temperature) to 650 °C. To describe the observed time- and temperature-dependent softening during tempering, a kinetic model for the evolution of the mean size of secondary carbides based on Ostwald ripening is developed. In addition, both mechanism-based and phenomenological relationships for the cyclic mechanical properties of the Ramberg- Osgood model depending on carbide size and temperature are proposed. The stress-strain hysteresis loops measured at different temperatures and after different heat treatments can be well described with the proposed kinetic and mechanical model. Furthermore, the model is suitable for integration in advanced mechanism-based lifetime models. However, since the Ramberg-Osgood model is not suitable for finite element implementation, a temperature-dependent incremental cyclic plasticity model is presented as well. Thus, softening due to particle coarsening can be applied in the finite element method (FEM). Therefore, a kinetic model is coupled with a cyclic plasticity model including kinematic hardening. The plasticity model is implemented via subroutines in the finite element program ABAQUS for implicit integration (subroutine called UMAT) and explicit integration (subroutine called VUMAT). The implemented model is used for the simulation of an exemplary hot working process to assess the effects of softening due to particle coarsening. It shows that the thermal softening at high temperatures, which occur over a long time at a mechanically highly loaded area, has a great influence. If this influence is not considered in tool design, an unexpected tool failure might occur bringing the production to a standstill.
Cast aluminum alloys are frequently used as materials for cylinder head applications in internal combustion gasoline engines. These components must withstand severe cyclic mechanical and thermal loads throughout their lifetime. Reliable computational methods allow for accurate estimation of stresses, strains, and temperature fields and lead to more realistic Thermomechanical Fatigue (TMF) lifetime predictions. With accurate numerical methods, the components could be optimized via computer simulations and the number of required bench tests could be reduced significantly. These types of alloys are normally optimized for peak hardness from a quenched state that maximizes the strength of the material. However due to high temperature exposure, in service or under test conditions, the material would experience an over-ageing effect that leads to a significant reduction in the strength of the material. To numerically account for ageing effects, the Shercliff & Ashby ageing model is combined with a Chaboche-type viscoplasticity model available in the finite-element program ABAQUS by defining field variables. The constitutive model with ageing effects is correlated with uniaxial cyclic isothermal tests in the T6 state, the overaged state, as well as thermomechanical tests. On the other hand, the mechanism-based TMF damage model (DTMF) is calibrated for both T6 and over-aged state. Both the constitutive and the damage model are applied to a cylinder head component simulating several cycles on an engine dynamometer test. The effects of including ageing for both models are shown.