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arXiv 2021年

作者： Hampp, Johannes Düren, Michael Brown, Tom Center for International Development and Environmental Research Justus Liebig University Gießen Hesse Germany Department of Digital Transformation in Energy Systems Technische Universität Berlin Berlin Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Baden-Württemberg Germany

Import and export of fossil energy carriers are cornerstones of energy systems world-wide. If energy systems are to become climate neutral and sustainable, fossil carriers need to be substituted with carbon neutral alternatives or electrified if possible. We investigate synthetic chemical energy carriers, hydrogen, methane, methanol, ammonia and Fischer-Tropsch fuels, produced using electricity from Renewable Energy Source (RES) as fossil substitutes. RES potentials are obtained from GIS-analysis and hourly resolved time-series are derived using reanalysis weather data. We model the sourcing of feedstock chemicals, synthesis and transport along nine different Energy Supply Chains to Germany and compare import options for seven locations around the world against each other and with domestically sourced alternatives on the basis of their respective cost per unit of hydrogen and energy delivered. We find that for each type of chemical energy carrier, there is an import option with lower costs compared to domestic production in Germany. No single exporting country or energy carrier has a unique cost advantage, since for each energy carrier and country there are cost-competitive alternatives. This allows exporter and infrastructure decisions to be made based on other criteria than energy and cost. The lowest cost means for importing of energy and hydrogen are by hydrogen pipeline from Denmark, Spain and Western Asia and Northern Africa starting at 36EUR/MWhLHVto 42EUR/MWhLHVor 1.0EUR/kgH2to 1.3EUR/kgH2(in 2050, assuming 5% p.a. capital cost). For complex energy carriers derived from hydrogen like methane, ammonia, methanol or Fischer-Tropsch fuels, imports from Argentina by ship to Germany are lower cost than closer exporters in the European Union or Western Asia and Northern Africa. For meeting hydrogen demand, direct hydrogen imports are more attractive than indirect routes using methane, methanol or ammonia imports and subsequent decomposition to hydrogen because of h

关键词： Methanol

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Field Experiments with an Automated Utility Platform for Transportation and Work Processes

Field Experiments with an Automated Utility Platform for Tra...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Raimund Edlinger Stefan Dumberger Roman Froschauer Wolfgang Pointner Marcel Zeilinger Andreas Nü chter Smart Automation and Robotics University of Applied Sciences Upper Austria Wels Austria Assistive &#x0026 Autonomous Systems AIT &#x2013 Austrian Institute of Technology Vienna Austria Informatics VII - Robotics and Telematics Julius-Maximilians-University W&#x00FC rzburg W&#x00FC rzburg Germany

The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features; (ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.

关键词： Navigation Transportation Systems architecture Switches Robot sensing systems Software Software reliability

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Computer modeling application of fluid outflow from vessels

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Materials Science Forum 2019年 952卷 250-257页

作者： Kraváriková, Helena Faculty of Materials Science and Technology in Trnava Institute of Applied Informatics Automation and Mechatronics Bottova 26 Trnava917 24 Slovakia

The aim of the paper is to evaluate numerical analysis of the fluid flow during the outflow from vessel orifices at various locations. The problems of the outflow velocities and pressure fields were well-chosen for the given purposes. The selected fluid flow problems were solved by numerical simulation using FEM in ANSYS. For numerical simulation, we used the basic steps to design an abstract model in the ANSYS virtual environment. Numerical simulation requires a geometric model complemented by physical properties of flowing fluids as well as both the initial and boundary conditions. It is then possible to calculate the velocity and pressure fields by numerical simulation for a particular fluid type. The results obtained from the numerical simulation were compared with those of the analytical solution. The results obtained from modeling and numerical simulation correspond to the actual values with minimum deviations. The demonstrated type of the problem solved by numerical simulation and modeling confirmed the advantages and possibilities of flexible solutions for any combination of problems in the field of fluid dynamics. Modeling and numerical simulation of fluid flow can provide results regarding the speed and the pressure fields in vessels and pipelines. © 2019 Trans Tech Publications Ltd, Switzerland.

关键词： Orifices

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions

Digital Twin Definition for Detecting Abnormal Perspiration ...

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Roedunet International Conference (RoEduNet)

作者： Cristian Vizitiu Ioan Turcin Kevin Alexander Dominey Selver Softic Adrian-Cătălin Dinculescu Vlad I. Bocăneţ Cosmin Dugan Sorin-Aurel Moraru The Space Applications and Technologies Laboratory Institute of Space Science -Subsidiary of INFLPR Magurele Romania Department of Automatics and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania Department Automation Technology CAMPUS 02 University of Applied Sciences Graz Austria Department IT & Business Informatics CAMPUS 02 University of Applied Sciences Graz Austria Department of Manufacturing Engineering Faculty of Industrial Engineering Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems Engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation.

关键词： Adaptation models Generative AI Psychology Human factors Machine learning Predictive models Physiology Digital twins Modeling Biomedical monitoring

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Long-term On-line Identification of Time-varying Systems

Long-term On-line Identification of Time-varying Systems

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International Carpathian Control Conference (ICCC)

作者： Ján Vachálek Dana Šišmišová Ivan Fiťka Matej Šimovec Faculty of Mechanical Engineering Institute of Automation Measurement and Applied Informatics Slovak University of Technology in Bratislava Nám. Slobody 17 Bratislava Slovak Republic

This article discusses the possibility of deploying regression recursive continuous identification methods, which are using regularized exponential forgetting, during long-term monitoring of time-varying systems. The emphasis is placed on the long-term deployment since the advantage of this algorithm will only become evident with long-term deployment. These continuous identification algorithms are going to be applied on the mathematical model of the identified system for the needs of adaptive control. The article presents the implemented continuous identification techniques, where the non-informative data, that can possibly destabilize the numerical calculations of the identified system parameters, are weighted by the Dyadic reduction algorithm. These techniques are using an alternative covariance matrix for its “forgetting” in order to maintain the initial system dynamics in the mathematical model of the identified system. The matrix also suppresses the impact of high amounts of non-informative data received from the long-term operation the industrial systems with slow dynamics. The focus is mainly set on the non-informative data, which emerge especially during the long-term run of the tuned systems operating in between the bounds of the selected working point. A “Motor-Flywheel” laboratory model is used for the validation tests of the modified and the standard regression recursive algorithms.

关键词： System dynamics Heuristic algorithms Prediction algorithms Numerical models Mathematical model Reliability Covariance matrices

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WITHDRAWN: Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision

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Fuel 2023年 338卷

作者： Robin Streier Siegmar Wirtz Krasimir Aleksandrov Hans-Joachim Gehrmann Dieter Stapf Miao Zhang Markus Vogelbacher J¨org Matthes Viktor Scherer Department of Energy Plant Technology Ruhr-University Bochum Universit¨atsstrase 150 44780 Bochum Germany Institute for Technical Chemistry Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal ( http://***/locate/withdrawalpolicy ). This article has been withdrawn at the request of the editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. This error bears no reflection on the article or its authors. The publisher apologizes to the authors and the readers for this unfortunate error.

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Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision

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Fuel 2023年 352卷

作者： Robin Streier Siegmar Wirtz Krasimir Aleksandrov Hans-Joachim Gehrmann Dieter Stapf Miao Zhang Markus Vogelbacher Jörg Matthes Viktor Scherer Department of Energy Plant Technology Ruhr-University Bochum Universitätsstraße 150 44780 Bochum Germany Institute for Technical Chemistry Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany

This research investigates the flight behavior of refuse-derived fuel (RDF) in a drop shaft using Computer Vision to obtain statistical data on the aerodynamic properties of the particles. Methods to determine 3D geometry models of complex-shaped particles by photogrammetry and to obtain time resolved particle positions and velocities are described. Furthermore, an approach to obtain the frequency distribution of drag and lift coefficients from photogrammetric analysis and drop shaft experiments is presented. The image evaluation is based on algorithms of the open-source libraries OpenCV, COLMAP as well as MeshLab and Open3D. The precision of the system is validated employing model particles with known geometry. The 3D particle models overestimate the particle surface area by 4.58 %, the position detection works with a mean deviation of 2.73 %. The average sink rate is calculated with an accuracy of 4.87 % and the drag coefficient with an accuracy of 2.08 %. Finally, the frequency distribution of four RDF fractions, namely, textiles, cardboard, 3D plastic particles and 2D plastic foils are presented.

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On the Convergence of Artificial Intelligence and Distributed Ledger technology: A Scoping Review and Future Research Agenda

arXiv

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arXiv 2020年

作者： Pandl, Konstantin D. Thiebes, Scott Schmidt-Kraepelin, Manuel Sunyaev, Ali Institute for Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology KarlsruheBaden-Württemberg76131 Germany

Developments in Artificial Intelligence (AI) and Distributed Ledger technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in uncertain environments. In recent research, both technologies are used in similar and even the same systems. Examples include the design of secure distributed ledgers or the creation of allied learning systems distributed across multiple nodes. This can lead to technological convergence, which in the past, has paved the way for major innovations in information technology. Previous work highlights several potential benefits of the convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. We aim to contribute by conducting a systematic literature review on previous work and providing rigorously derived future research opportunities. This work helps researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies. Copyright © 2020, The Authors. All rights reserved.

关键词： Blockchain

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Modeling and simulation of sector-coupled networks: A gas-power benchmark

arXiv

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arXiv 2020年

作者： Fokken, E. Mühlpfordt, T. Faulwasser, T. Göttlich, S. Kolb, O. Department of Mathematics University of Mannheim Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Institute for Energy Systems Energy Efficiency and Energy Economics TU Dortmund University

In this contribution, we aim at presenting a gas-to-power benchmark problem that can be used for the simulation of electricity and gas networks in a time-dependent environment. Based on realistic data from the IEEE database and the GasLib suite, we describe the full set up of the underlying equations and motivate the choice of parameters. The simulation results demonstrate the applicability of the proposed approach and also allow for a clear visualization of gas-power conversion. Copyright © 2020, The Authors. All rights reserved.

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Understanding electricity prices beyond the merit order principle using explainable AI

arXiv

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arXiv 2022年

作者： Trebbien, Julius Gorjão, Leonardo Rydin Praktiknjo, Aaron Schäfer, Benjamin Witthaut, Dirk Jülich52428 Germany University of Cologne Institute for Theoretical Physics Zülpicher Str. 77 Cologne50937 Germany Faculty of Science and Technology Norwegian University of Life Sciences As1432 Norway Department of Computer Science OsloMet – Oslo Metropolitan University Oslo0130 Norway E.ON Energy Research Center RWTH Aachen University Mathieustr. 10 Aachen52074 Germany Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany JARA-ENERGY Aachen52074 Germany

Electricity prices in liberalized markets are determined by the supply and demand for electric power, which are in turn driven by various external influences that vary strongly in time. In perfect competition, the merit order principle describes that dispatchable power plants enter the market in the order of their marginal costs to meet the residual load, i.e. the difference of load and renewable generation. Many market models implement this principle to predict electricity prices but typically require certain assumptions and simplifications. In this article, we present an explainable machine learning model for the prices on the German day-ahead market, which substantially outperforms a benchmark model based on the merit order principle. Our model is designed for the ex-post analysis of prices and thus builds on various external features. Using Shapley Additive exPlanation (SHAP) values, we can disentangle the role of the different features and quantify their importance from empiric data. Load, wind and solar generation are most important, as expected, but wind power appears to affect prices stronger than solar power does. Fuel prices also rank highly and show nontrivial dependencies, including strong interactions with other features revealed by a SHAP interaction analysis. Large generation ramps are correlated with high prices, again with strong feature interactions, due to the limited flexibility of nuclear and lignite plants. Our results further contribute to model development by providing quantitative insights directly from data. Copyright © 2022, The Authors. All rights reserved.

关键词： Wind power

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