TY - JOUR AU - Sahl, Abdulqader Bin AU - Orosz, Ákos AU - How, Bing Shen AU - Friedler, Ferenc AU - Teng, Sin Yong TI - Electrification of oil refineries through multi-objective multi-period graph-theoretical planning: A crude distillation unit case study JF - JOURNAL OF CLEANER PRODUCTION J2 - J CLEAN PROD VL - 434 PY - 2023 IS - 1 January 2024 SN - 0959-6526 DO - 10.1016/j.jclepro.2023.140179 UR - https://m2.mtmt.hu/api/publication/34450618 ID - 34450618 LA - English DB - MTMT ER - TY - JOUR AU - Pimentel, Jean AU - Gerardo, Ruiz-Mercadob AU - Friedler, Ferenc TI - Technoeconomic Assessment of Recycling Routes for Chemicals: A Case Study of n-Hexane JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 103 PY - 2023 SP - 349 EP - 354 PG - 6 SN - 1974-9791 DO - 10.3303/CET23103059 UR - https://m2.mtmt.hu/api/publication/34202437 ID - 34202437 N1 - Export Date: 20 December 2023 Correspondence Address: Friedler, F.; Széchenyi István Egyetem, Egyetem tér 1., Hungary; email: f.friedler@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00004 Funding details: Magyarország Kormánya Funding text 1: The research presented in this paper was supported by the Government of Hungary and the European Union Recovery and Resilience Plan within the framework of the Artificial Intelligence National Laboratory Program (RRF-2.3.1-21-2022-00004). Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. Any mention of trade names, products, or services does not imply an endorsement by the U.S. Government or the EPA. The EPA does not endorse any commercial products, services, or enterprises. AB - The circular economy has become one of the most popular topics in worldwide sustainability research. The imperious necessity of reducing resource consumption and decreasing waste generation has led to reincorporating materials at the end-of-life (EoL) stage into the productive chain. Nonetheless, the presence of hazardous substances in the EoL stage materials poses a significant challenge for the transition toward the production model. The adequate transformation of these materials into feedstocks requires their correct allocation into recovery plants and final destinations. Such an allocation can be decided by resorting to optimisation by generating the best alternative networks, from where the stakeholders may decide the most suitable recycling scheme. In this work, a graph-theoretic approach is introduced to identify the best alternatives to reincorporate industrial EoL chemicals into the productive chain. This contribution presents the initial approach to this problem, demonstrated through a case study considering the data reported on the public-access release inventory data for n-hexane. Different recycling routes are proposed for the case study by optimising the total treatment cost, and their advantages and disadvantages are discussed; moreover, their efficiency concerning the circular economy is measured by comparing the amount of recovered chemicals. By generating plausible recycling alternatives, this work contributes positively to analysing potential alternatives for circular economy and resource conservation in industry. LA - English DB - MTMT ER - TY - JOUR AU - Teng, Sin Yong AU - Orosz, Ákos AU - How, Bing Shen AU - Jansen, Jeroen J. AU - Friedler, Ferenc TI - Retrofit heat exchanger network optimization via graph-theoretical approach: Pinch-bounded N-best solutions allows positional swapping JF - ENERGY J2 - ENERGY VL - 2023 PY - 2023 SP - 129029 SN - 0360-5442 DO - 10.1016/j.energy.2023.129029 UR - https://m2.mtmt.hu/api/publication/34140047 ID - 34140047 N1 - Radboud University, Institute for Molecules and Materials, P.O. Box 9010, GL, Nijmegen, 6500, Netherlands Department of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, Veszprém, 8200, Hungary Biomass Waste-to-Wealth Special Interest Group, Research Centre for Sustainable Technologies, Faculty of Engineering, Computing and Science, Swinburne University of Technology, Jalan Simpang Tiga, Sarawak, Kuching, 93350, Malaysia Széchenyi István University (University of Győr), National Artificial Intelligence Laboratory (MILAB) & Vehicle Industry Research Center, Egyetem tér 1, Győr, 9026, Hungary Export Date: 16 October 2023 CODEN: ENEYD Correspondence Address: Teng, S.Y.; Radboud University, P.O. Box 9010, GL, Netherlands; email: sinyong.teng@ru.nl Funding details: RRF-2.3.1-21-2022-00004 Funding details: H2020 Marie Skłodowska-Curie Actions, MSCA, 101064585 Funding text 1: The research contribution from S.Y. Teng is supported by the European Union's Horizon Europe Research and Innovation Program, under Marie Skłodowska-Curie Actions grant agreement no. 101064585 (MoCEGS). F. Friedler's research contribution was supported by the Government of Hungary and funded by the European Union Recovery and Resilience Plan within the framework of the Artificial Intelligence National Laboratory Program ( RRF-2.3.1-21-2022-00004 ). LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Szauter, Ferenc AU - Friedler, Ferenc TI - Energy Efficient Drive Management of Lightweight Urban Vehicle JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 103 PY - 2023 SP - 253 EP - 258 PG - 6 SN - 1974-9791 DO - 10.3303/CET23103043 UR - https://m2.mtmt.hu/api/publication/34126562 ID - 34126562 LA - English DB - MTMT ER - TY - JOUR AU - Pimentel, Jean AU - Balázs, László AU - Friedler, Ferenc TI - Optimization of vertical farms energy efficiency via multiperiodic graph-theoretical approach JF - JOURNAL OF CLEANER PRODUCTION J2 - J CLEAN PROD VL - 416 PY - 2023 SN - 0959-6526 DO - 10.1016/j.jclepro.2023.137938 UR - https://m2.mtmt.hu/api/publication/34064369 ID - 34064369 N1 - Széchenyi István University, Egyetem tér 1, Győr, H-9026, Hungary Hungarian University of Agriculture and Life Sciences, Páter Károly utca 1, Gödöllő2100, Hungary Cited By :2 Export Date: 16 October 2023 CODEN: JCROE Correspondence Address: Friedler, F.; Széchenyi István University, Egyetem tér 1, Hungary; email: f.friedler@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00004 Funding text 1: The research presented in this paper was supported by the Government of Hungary and funded by the European Union Recovery and Resilience Plan within the framework of the Artificial Intelligence National Laboratory Program ( RRF-2.3.1-21-2022-00004 ). LA - English DB - MTMT ER - TY - JOUR AU - Istenes, György AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Horváth, Zoltán AU - Friedler, Ferenc TI - Kriging-Assisted Multi-Objective Optimization Framework for Electric Motors Using Predetermined Driving Strategy JF - ENERGIES J2 - ENERGIES VL - 16 PY - 2023 IS - 12 SN - 1996-1073 DO - 10.3390/en16124713 UR - https://m2.mtmt.hu/api/publication/34018990 ID - 34018990 N1 - Vehicle Industry Research Center, Széchenyi István University, Egyetem Tér 1, Győr, 9026, Hungary Department of Mathematics and Computational Sciences, Széchenyi István University, Egyetem Tér 1, Győr, 9026, Hungary Cited By :1 Export Date: 16 October 2023 Correspondence Address: Friedler, F.; Vehicle Industry Research Center, Egyetem Tér 1, Hungary; email: f.friedler@ga.sze.hu Funding details: European Commission, EC Funding text 1: The research was supported by the European Union within the framework of the National Laboratory for Artificial Intelligence (RRF-2.3.1-21-2022-00004). AB - In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB R2019b and Ansys Maxwell 2019 R3 software. The framework is capable of managing a wide range of objective functions due to its modular structure. The optimization can also be easily parallelized and enhanced with surrogate models to reduce the runtime. The framework is validated by manufacturing and measuring the optimized electric motor. The method’s applicability for solving electric motor design problems is demonstrated via the validation process. A test application is also presented, in which the operating points of a predetermined driving strategy provide the input for the optimization. The kriging surrogate model is used in the framework to reduce the runtime. The results of the optimization and the framework’s benefits and drawbacks are discussed through the provided examples, in addition to displaying the properly applicable design processes. The optimization framework provides a ready-to-use tool for optimizing electric motors based on the driving strategy for single- or multi-objective purposes. The applicability of the framework is demonstrated by optimizing the electric motor of a world recorder energy-efficient race vehicle. In this application, the optimization framework achieved a 2% improvement in energy consumption and a 9% increase in speed at a rated DC voltage, allowing the motor to operate at desired working points even with low battery voltage. LA - English DB - MTMT ER - TY - JOUR AU - Orosz, Ákos AU - Varbanov, Petar AU - Klemeš, Jiri Jaromir AU - Friedler, Ferenc TI - Process synthesis considering sustainability for both normal and non-normal operations: P-graph approach JF - JOURNAL OF CLEANER PRODUCTION J2 - J CLEAN PROD VL - 414 PY - 2023 SN - 0959-6526 DO - 10.1016/j.jclepro.2023.137696 UR - https://m2.mtmt.hu/api/publication/34009769 ID - 34009769 N1 - Department of Computer Science and Systems Technology, Faculty of Information Technology, University of Pannonia, Egytem u. 10, Veszprém, 8200, Hungary Sustainable Process Integration Laboratory – SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology – VUT Brno, Technická 2896/2, Brno, 616 69, Czech Republic Széchenyi István University, Egyetem tér 1, Győr, 9026, Hungary Cited By :1 Export Date: 16 October 2023 CODEN: JCROE Correspondence Address: Friedler, F.; Széchenyi István University, Egyetem tér 1, Hungary; email: f.friedler@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00004 Funding details: CZ.02.1.01/0.0/0.0/15_003/0000456 Funding details: European Commission, EC Funding details: Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT Funding text 1: The research presented in this paper was supported by the Government of Hungary and funded by the European Union Recovery and Resilience Plan within the framework of the Artificial Intelligence National Laboratory Program (RRF-2.3.1-21-2022-00004). The contribution of Petar Sabev Varbanov and Jiří Jaromír Klemeš has been supported by EU project Sustainable Process Integration Laboratory – SPIL, funded as project No. CZ.02.1.01/0.0/0.0/15_003/0000456, the Operational Programme Research, Development and Education of the Czech Ministry of Education , Youth and Sports by EU European Structural and Investment Funds. Funding text 2: The research presented in this paper was supported by the Government of Hungary and funded by the European Union Recovery and Resilience Plan within the framework of the Artificial Intelligence National Laboratory Program (RRF-2.3.1-21-2022-00004). The contribution of Petar Sabev Varbanov and Jiří Jaromír Klemeš has been supported by EU project Sustainable Process Integration Laboratory – SPIL, funded as project No. CZ.02.1.01/0.0/0.0/15_003/0000456, the Operational Programme Research, Development and Education of the Czech Ministry of Education, Youth and Sports by EU European Structural and Investment Funds. LA - English DB - MTMT ER - TY - JOUR AU - Piglerné, Lakner Rozália AU - Orosz, Ákos AU - How, Bing Shen AU - Friedler, Ferenc TI - Synthesis of multiperiod heat exchanger networks: n-best networks with variable approach temperature JF - THERMAL SCIENCE AND ENGINEERING PROGRESS J2 - TSEP VL - 42 PY - 2023 SN - 2451-9049 DO - 10.1016/j.tsep.2023.101912 UR - https://m2.mtmt.hu/api/publication/33870068 ID - 33870068 N1 - Cited By :2 Export Date: 16 October 2023 Correspondence Address: Friedler, F.; Széchenyi István University, 9026 Győr, Egyetem tér 1, Hungary; email: f.friedler@ga.sze.hu Funding details: European Commission, EC Funding text 1: The research was supported by the European Union within the framework of the National Laboratory for Artificial Intelligence. (RRF-2.3.1-21-2022-00004). LA - English DB - MTMT ER - TY - JOUR AU - Pusztai, Zoltán AU - Kőrös, Péter AU - Szauter, Ferenc AU - Friedler, Ferenc TI - Implementation of Optimized Regenerative Braking in Energy Efficient Driving Strategies JF - ENERGIES J2 - ENERGIES VL - 16 PY - 2023 IS - 6 SN - 1996-1073 DO - 10.3390/en16062682 UR - https://m2.mtmt.hu/api/publication/33700166 ID - 33700166 N1 - Cited By :1 Export Date: 16 October 2023 Correspondence Address: Pusztai, Z.; Vehicle Industry Research Center, Hungary; email: pusztai.zoltan@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00002 Funding details: European Commission, EC Funding text 1: The research was supported by the European Union within the framework of the National Laboratory for Autonomous Systems (RRF-2.3.1-21-2022-00002). AB - In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model. LA - English DB - MTMT ER - TY - JOUR AU - How, Bing Shen AU - Teng, Sin Yong AU - Orosz, Ákos AU - Sunarso, Jaka AU - Friedler, Ferenc TI - Enabling in-depth analysis in heat exchanger network synthesis via graph-theoretic tool: Experiences in Swinburne University of Technology Sarawak Campus JF - EDUCATION FOR CHEMICAL ENGINEERS J2 - EDU CHEM ENGIN VL - 2023 PY - 2023 SN - 1749-7728 DO - 10.1016/j.ece.2022.12.003 UR - https://m2.mtmt.hu/api/publication/33695776 ID - 33695776 N1 - Research Centre for Sustainable Technologies, Faculty of Engineering, Computing and Science, Swinburne University of Technology, Jalan Simpang Tiga, Sarawak, Kuching, 93350, Malaysia Radboud University, Institute for Molecules and Materials, P.O. Box 9010, Nijmegen, 6500 GL, Netherlands Department of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, Veszprém, 8200, Hungary Széchenyi István University, Egyetem tér 1, Győr, 9026, Hungary Cited By :1 Export Date: 16 October 2023 Correspondence Address: How, B.S.; Research Centre for Sustainable Technologies, Jalan Simpang Tiga, Sarawak, Malaysia; email: bshow@swinburne.edu.my Funding text 1: The authors would like to acknowledge the support from Swinburne University of Technology Sarawak Campus . This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. LA - English DB - MTMT ER -