TY - JOUR A1 - Weber, Tobias A1 - Arent, Jan-Christoph A1 - Münch, Lukas A1 - Duhovic, Miro A1 - Balvers, Johannes M. T1 - A fast method for the generation of boundary conditions for thermal autoclave simulation JF - Composites Part A N2 - Manufacturing process simulation enables the evaluation and improvement of autoclave mold concepts early in the design phase. To achieve a high part quality at low cycle times, the thermal behavior of the autoclave mold can be investigated by means of simulations. Most challenging for such a simulation is the generation of necessary boundary conditions. Heat-up and temperature distribution in an autoclave mold are governed by flow phenomena, tooling material and shape, position within the autoclave, and the chosen autoclave cycle. This paper identifies and summarizes the most important factors influencing mold heat-up and how they can be introduced into a thermal simulation. Thermal measurements are used to quantify the impact of the various parameters. Finally, the gained knowledge is applied to develop a semi-empirical approach for boundary condition estimation that enables a simple and fast thermal simulation of the autoclave curing process with reasonably high accuracy for tooling optimization. Y1 - 2016 U6 - https://doi.org/10.1016/j.compositesa.2016.05.036 SN - 1359-835X VL - 88 SP - 216 EP - 225 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Götten, Falk A1 - Finger, Felix A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, Matthew A1 - Bil, Cees T1 - A highly automated method for simulating airfoil characteristics at low Reynolds number using a RANS - transition approach T2 - Deutscher Luft- und Raumfahrtkongress - DLRK 2019. Darmstadt, Germany Y1 - 2019 U6 - https://doi.org/10.25967/490026 SP - 1 EP - 14 ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation JF - International Journal of Production Research N2 - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines. KW - Human factors KW - assistance system KW - gamification KW - adaptive systems KW - manufacturing Y1 - 2023 U6 - https://doi.org/10.1080/00207543.2023.2166140 SN - 0020-7543 (Print) SN - 1366-588X (Online) PB - Taylor & Francis ER - TY - JOUR A1 - Konstantinidis, Konstantinos A1 - Flores Martinez, Claudio A1 - Dachwald, Bernd A1 - Ohndorf, Andreas A1 - Dykta, Paul A1 - Bowitz, Pascal A1 - Rudolph, Martin A1 - Digel, Ilya A1 - Kowalski, Julia A1 - Voigt, Konstantin A1 - Förstner, Roger T1 - A lander mission to probe subglacial water on Saturn's moon enceladus for life JF - Acta astronautica Y1 - 2015 SN - 1879-2030 (E-Journal); 0094-5765 (Print) VL - Vol. 106 SP - 63 EP - 89 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude N2 - 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. Y1 - 2020 U6 - https://doi.org/10.25967/490162 N1 - 68. Deutscher Luft- und Raumfahrtkongress 30.09.-02.10.2019, Darmstadt PB - DGLR CY - Bonn ER - TY - JOUR A1 - Dittus, H. A1 - Turyshev, S. G. A1 - Dachwald, Bernd A1 - Blome, Hans-Joachim T1 - A Mission to Explore the Pioneer Anomaly JF - Proceedings of the 39th ESLAB Symposium "Trends in Space Science and Cosmic Vision 2020" : 19 - 21 April 2005, ESTEC, Noordwijk, the Netherlands / European Space Agency. [Comp. by: F. Favata ...] . - (ESA SP ; 588) Y1 - 2005 SN - 9290928999 N1 - ISBN der CD-ROM-Ausg.: 9290928999 ; Symposium Trends in Space Science and Cosmic Vision 2020 <2005, Noordwijk> ; ESLAB symposium <39,2005, Noordwijk> ; European Space Laboratory ; Report Number: LA-UR-05-4907 ; The Pioneer Explorer Collaboration SP - 3 EP - 10 PB - ESA Publ. Div. CY - Noordwijk ER - TY - CHAP A1 - Bagheri, Mohsen A1 - Schleupen, Josef A1 - Dahmann, Peter A1 - Kallweit, Stephan T1 - A multi-functional device applying for the safe maintenance at high-altitude on wind turbines T2 - 20th International Conference on Composite Materials : Copenhagen, 19 - 24th July 2015 Y1 - 2015 SP - 1 EP - 6 ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - 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. Y1 - 2020 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - 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. Y1 - 2020 SN - 2169-3536 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Schirra, Julian A1 - Watmuff, Jon A1 - Bauschat, J.-Michael T1 - A relative assessment of existing potential-methodologies to accurately estimate the induced drag of highly non-planar lifting systems T2 - Advanced aero concepts, design and operations : Applied Aerodynamics Conference : July 22 -24, 2014, Bristol, UK Y1 - 2014 SP - 1 EP - 13 ER -