@article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0}, series = {IEEE Access}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York, NY}, isbn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {1 -- 12}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, number = {Art. 9108222}, publisher = {IEEE}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {111381 -- 111393}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @inproceedings{KreyerEsch2017, author = {Kreyer, J{\"o}rg and Esch, Thomas}, title = {Simulation Tool for Predictive Control Strategies for an ORCSystem in Heavy Duty Vehicles}, series = {European GT Conference 2017}, booktitle = {European GT Conference 2017}, pages = {16 Seiten}, year = {2017}, abstract = {Scientific questions - How can a non-stationary heat offering in the commercial vehicle be used to reduce fuel consumption? - Which potentials offer route and environmental information among with predicted speed and load trajectories to increase the efficiency of a ORC-System? Methods - Desktop bound holistic simulation model for a heavy duty truck incl. an ORC System - Prediction of massflows, temperatures and mixture quality (AFR) of exhaust gas}, language = {en} } @article{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles}, series = {SAE International Journal of Commercial Vehicles}, volume = {13}, journal = {SAE International Journal of Commercial Vehicles}, number = {2}, publisher = {SAE International}, address = {Warrendale, Pa.}, issn = {1946-3928}, doi = {10.4271/02-13-02-0009}, pages = {129 -- 143}, year = {2020}, abstract = {The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.}, language = {en} } @inproceedings{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude}, publisher = {DGLR}, address = {Bonn}, doi = {10.25967/490162}, pages = {13 Seiten}, year = {2020}, abstract = {In addition to very high safety and reliability requirements, the design of internal combustion engines (ICE) in aviation focuses on economic efficiency. The objective must be to design the aircraft powertrain optimized for a specific flight mission with respect to fuel consumption and specific engine power. Against this background, expert tools provide valuable decision-making assistance for the customer. In this paper, a mathematical calculation model for the fuel consumption of aircraft ICE is presented. This model enables the derivation of fuel consumption maps for different engine configurations. Depending on the flight conditions and based on these maps, the current and the integrated fuel consumption for freely definable flight emissions is calculated. For that purpose, an interpolation method is used, that has been optimized for accuracy and calculation time. The mission boundary conditions flight altitude and power requirement of the ICE form the basis for this calculation. The mathematical fuel consumption model is embedded in a parent program. This parent program presents the simulated fuel consumption by means of an example flight mission for a representative airplane. The focus of the work is therefore on reproducing exact consumption data for flight operations. By use of the empirical approaches according to Gagg-Farrar [1] the power and fuel consumption as a function of the flight altitude are determined. To substantiate this approaches, a 1-D ICE model based on the multi-physical simulation tool GT-Suite® has been created. This 1-D engine model offers the possibility to analyze the filling and gas change processes, the internal combustion as well as heat and friction losses for an ICE under altitude environmental conditions. Performance measurements on a dynamometer at sea level for a naturally aspirated ICE with a displacement of 1211 ccm used in an aviation aircraft has been done to validate the 1-D ICE model. To check the plausibility of the empirical approaches with respect to the fuel consumption and performance adjustment for the flight altitude an analysis of the ICE efficiency chain of the 1-D engine model is done. In addition, a comparison of literature and manufacturer data with the simulation results is presented.}, language = {en} } @article{LaarmannThomaMischetal.2023, author = {Laarmann, Lukas and Thoma, Andreas and Misch, Philipp and R{\"o}th, Thilo and Braun, Carsten and Watkins, Simon and Fard, Mohammad}, title = {Automotive safety approach for future eVTOL vehicles}, series = {CEAS Aeronautical Journal}, journal = {CEAS Aeronautical Journal}, publisher = {Springer Nature}, issn = {1869-5590 (Online)}, doi = {10.1007/s13272-023-00655-0}, pages = {11 Seiten}, year = {2023}, abstract = {The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL's crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.}, language = {en} } @inproceedings{LahrsKrisamHerrmann2023, author = {Lahrs, Lennart and Krisam, Pierre and Herrmann, Ulf}, title = {Envisioning a collaborative energy system planning platform for the energy transition at the district level}, series = {ECOS 2023. The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems}, booktitle = {ECOS 2023. The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems}, publisher = {Procedings of ECOS 2023}, doi = {10.52202/069564-0284}, pages = {3163 -- 3170}, year = {2023}, abstract = {Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.}, language = {en} } @inproceedings{LaoBuehrigPolaczekRoeth2011, author = {Lao, B. and B{\"u}hrig-Polaczek, A. and R{\"o}th, Thilo}, title = {Funktionsintegrierte Leichtbaustrukturen in gussintensiver Metall-Hybridbauweise}, series = {Verbundwerkstoffe und Werkstoffverbunde: Tagungsband zum 18. Symposium ; 30.03.2011 bis 01.04.2011, Chemnitz}, booktitle = {Verbundwerkstoffe und Werkstoffverbunde: Tagungsband zum 18. Symposium ; 30.03.2011 bis 01.04.2011, Chemnitz}, editor = {Wielage, Bernhard}, publisher = {Eigenverlag}, address = {Chemnitz}, isbn = {978-3-00-033801-4}, pages = {413 -- 421}, year = {2011}, language = {de} } @misc{MachadoDahmannKeimeretal.2020, author = {Machado, Patricia Almeida and Dahmann, Peter and Keimer, Jona and Saretzki, Charlotte and St{\"u}bing, Felix and K{\"u}pper, Thomas}, title = {Stress profile and individual workload monitoring in general aviation pilots - an experiment's setting}, series = {23. Annual Meeting of the German Society of Travel Medicine, Coburg, 18.-19.9.2020}, journal = {23. Annual Meeting of the German Society of Travel Medicine, Coburg, 18.-19.9.2020}, doi = {10.55225/hppa.156}, year = {2020}, language = {en} } @inproceedings{MahdiDerschSchmitzetal.2022, author = {Mahdi, Zahra and Dersch, J{\"u}rgen and Schmitz, Pascal and Dieckmann, Simon and Caminos, Ricardo Alexander Chico and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf and Schwager, Christian and Schmitz, Mark and Gielen, Hans and Gedle, Yibekal and B{\"u}scher, Rauno}, title = {Technical assessment of Brayton cycle heat pumps for the integration in hybrid PV-CSP power plants}, series = {SOLARPACES 2020}, booktitle = {SOLARPACES 2020}, number = {2445 / 1}, publisher = {AIP conference proceedings / American Institute of Physics}, address = {Melville, NY}, isbn = {978-0-7354-4195-8}, issn = {1551-7616 (online)}, doi = {10.1063/5.0086269}, pages = {11 Seiten}, year = {2022}, abstract = {The hybridization of Concentrated Solar Power (CSP) and Photovoltaics (PV) systems is a promising approach to reduce costs of solar power plants, while increasing dispatchability and flexibility of power generation. High temperature heat pumps (HT HP) can be utilized to boost the salt temperature in the thermal energy storage (TES) of a Parabolic Trough Collector (PTC) system from 385 °C up to 565 °C. A PV field can supply the power for the HT HP, thus effectively storing the PV power as thermal energy. Besides cost-efficiently storing energy from the PV field, the power block efficiency of the overall system is improved due to the higher steam parameters. This paper presents a technical assessment of Brayton cycle heat pumps to be integrated in hybrid PV-CSP power plants. As a first step, a theoretical analysis was carried out to find the most suitable working fluid. The analysis included the fluids Air, Argon (Ar), Nitrogen (N2) and Carbon dioxide (CO2). N2 has been chosen as the optimal working fluid for the system. After the selection of the ideal working medium, different concepts for the arrangement of a HT HP in a PV-CSP hybrid power plant were developed and simulated in EBSILON®Professional. The concepts were evaluated technically by comparing the number of components required, pressure losses and coefficient of performance (COP).}, language = {en} }