TY - JOUR AU - Pimentel, Jean AU - Lukács, Balázs AU - Drotár, István TI - Energy Management Systems in Smart Cities: A Review from the Perspective of Complex Networks Design JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 107 PY - 2023 SP - 679 EP - 684 PG - 6 SN - 1974-9791 DO - 10.3303/CET23107114 UR - https://m2.mtmt.hu/api/publication/34484148 ID - 34484148 LA - English DB - MTMT ER - TY - JOUR AU - Pimentel, Jean AU - Mizsey, Péter TI - Systematic Energy Optimization and Design of Process Alternatives for Separation of Quaternary Azeotropic Mixtures JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 107 PY - 2023 SP - 571 EP - 576 PG - 6 SN - 1974-9791 DO - 10.3303/CET23107096 UR - https://m2.mtmt.hu/api/publication/34473848 ID - 34473848 N1 - Export Date: 9 February 2024 Correspondence Address: Pimentel, J.; Budapest University of Technology and Economics, Műegyetem 1, Hungary; email: jppimentell@edu.bme.hu 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 - 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 - Tóth, Árpád AU - Suta, Alex AU - Pimentel, Jean AU - Argoti, Andres TI - A comprehensive, semi-automated systematic literature review (SLR) design: Application to P-graph research with a focus on sustainability JF - JOURNAL OF CLEANER PRODUCTION J2 - J CLEAN PROD VL - 415 PY - 2023 SN - 0959-6526 DO - 10.1016/j.jclepro.2023.137741 UR - https://m2.mtmt.hu/api/publication/34016282 ID - 34016282 N1 - Cited By :1 Export Date: 16 October 2023 CODEN: JCROE Correspondence Address: Tóth, Á.; Széchenyi István University, Egyetem Sq. 1, IS-201, Hungary; email: totha@ga.sze.hu Funding details: RRF-2.3.1-21-2022-00004 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 - Pimentel, Jean AU - Aboagye, Emmanuel AU - Orosz, Ákos AU - Markót, Mihály Csaba AU - Cabezas, Heriberto AU - Friedler, Ferenc AU - Yenkie, Kirti M. TI - Enabling technology models with nonlinearities in the synthesis of wastewater treatment networks based on the P-graph framework JF - COMPUTERS & CHEMICAL ENGINEERING J2 - COMPUT CHEM ENG VL - 167 PY - 2022 PG - 15 SN - 0098-1354 DO - 10.1016/j.compchemeng.2022.108034 UR - https://m2.mtmt.hu/api/publication/33204707 ID - 33204707 N1 - Funding Agency and Grant Number: project, "National Laboratories 2020 Program - Artificial Intelligence Subprogram - Establishment of the National Artificial Intelligence Laboratory (MILAB) at Szechenyi Istvan University" [NKFIH-870-21/2020]; National Research, Development and Innovation Fund of Hungary under the Thematic Excellence Programme 2020-National Challenges sub-program funding scheme [TKP2020-NKA-10, 2020-4.1.1-TKP2020] Funding text: The research presented in this paper was partially funded by the project, "National Laboratories 2020 Program - Artificial Intelligence Subprogram - Establishment of the National Artificial Intelligence Laboratory (MILAB) at Szechenyi Istvan University (NKFIH-870-21/2020)." Project TKP2020-NKA-10 has been implemented with the support provided by the National Research, Development and Innovation Fund of Hungary, financed under the 2020-4.1.1-TKP2020 Thematic Excellence Programme 2020-National Challenges sub-program funding scheme. AB - Designing effective wastewater treatment networks is challenging because of the large number of treatment options available for performing similar tasks. Each treatment option has variability in cost and contaminant removal efficiency. Moreover, their mathematical models are highly nonlinear, thus rendering them computationally intensive. Such systems yield mixed-integer nonlinear programming models which cannot be solved properly with contemporary optimization tools that may result in local optima or may fail to converge. Herein, the P-graph framework is employed, thus generating all potentially feasible process structures, which results in simpler, smaller mathematical models. All potentially feasible process networks are evaluated by nonlinear programming resulting in guaranteed global optimum; furthermore, the ranked list of the n-best networks is also available. With the proposed tool, better facilities can be designed handling complex waste streams with minimal cost and reasonable environmental impact. The novel method is illustrated with two case studies showing its computational effectiveness. LA - English DB - MTMT ER - TY - JOUR AU - Pimentel, Jean AU - Friedler, Ferenc TI - Synthesis of Integrated Vertical Farming Systems with Multiperiodic Resource Availability JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 94 PY - 2022 SP - 1039 EP - 1044 PG - 6 SN - 1974-9791 DO - 10.3303/CET2294173 UR - https://m2.mtmt.hu/api/publication/33154664 ID - 33154664 N1 - Export Date: 18 October 2022 Correspondence Address: Friedler, F.; Széchenyi István University, Egyetem tér 1., Hungary; email: f.friedler@ga.sze.hu LA - English DB - MTMT ER - TY - JOUR AU - Teng, Sin Yong AU - Orosz, Ákos AU - How, Bing Shen AU - Pimentel, Jean AU - Friedler, Ferenc AU - Jansen, Jeroen J. TI - Framework to Embed Machine Learning Algorithms in P-graph: Communication from the Chemical Process Perspectives JF - CHEMICAL ENGINEERING RESEARCH AND DESIGN J2 - CHEM ENG RES DES VL - 188 PY - 2022 SP - 265 EP - 270 PG - 6 SN - 0263-8762 DO - 10.1016/j.cherd.2022.09.043 UR - https://m2.mtmt.hu/api/publication/33116760 ID - 33116760 N1 - 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 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 Department of Chemical and Environmental Process Engineering, Budapest University of Technology and Economics, Budapest, Hungary Széchenyi István University (University of Győr), National Artificial Intelligence Laboratory (MILAB) & Vehicle Industry Research Center, Egyetem tér 1, Győr, 9026, Hungary CODEN: CERDE Correspondence Address: Teng, S.Y.; Radboud University, P.O. Box 9010, Netherlands; email: sinyong.teng@ru.nl AB - P-graph is a popularly used framework for process network synthesis (PNS) and network topological optimization. This short communication introduces a Python interface for P-graph to serve as a linkage to modern programming ecosystems. This allows for a wider application of the fast and efficient P-graph solver, to provide structural and topological enumeration in numerous fields. The proposed framework allows for more integrative usage in Artificial Intelligence (AI), machine learning, process system engineering, chemical engineering and chemometrics. Large and repetitive topologies can also be automated using the new programming interface, saving time and effort in modelling. This short communication serves as a demonstration of the newly developed open-sourced P-graph interface. LA - English DB - MTMT ER - TY - JOUR AU - Orosz, Ákos AU - Pimentel, Jean AU - Argoti, Andres AU - Friedler, Ferenc TI - General formulation of resilience for designing process networks JF - COMPUTERS & CHEMICAL ENGINEERING J2 - COMPUT CHEM ENG VL - 165 PY - 2022 PG - 12 SN - 0098-1354 DO - 10.1016/j.compchemeng.2022.107932 UR - https://m2.mtmt.hu/api/publication/33034254 ID - 33034254 N1 - University of Pannonia, Egyetem u. 10., Veszprém, H-8200, Hungary Budapest University of Technology and Economics, Budapest, H-1111, Hungary Széchenyi István University, Egyetem tér 1., Győr, H-9026, Hungary Export Date: 12 August 2022 CODEN: CCEND Correspondence Address: Friedler, F.; Széchenyi István University, Egyetem tér 1., Hungary; email: f.friedler@ga.sze.hu AB - Herein, the formula proposed for quantifying the resilience of engineering systems, including processing systems, is general in several aspects. The structure of a system can be highly complex where the numbers of loops, raw materials, and products are not limited. The mathematical models of the operating units can be either linear or nonlinear for simulating the effect of the failures. The damage caused by an unexpected event can result in various levels of operation for the operating units. The proposed formula is also general in the sense that all possible combinations of failures are considered. The problem formulation, the related structure representation, the enumeration and evaluation of possible failures are based on the P-graph framework and its algorithms. The proposed formula for resilience is applicable to any complex engineering system whose behavior is primarily determined by its structure, including supply chains, information systems, municipal infrastructures, and electrical transmission networks. LA - English DB - MTMT ER - TY - JOUR AU - Aboagye, Emmanuel A. AU - Pimentel, Jean AU - Orosz, Ákos AU - Cabezas, Heriberto AU - Friedler, Ferenc AU - Yenkie, Kirti M. TI - Efficient Design and Sustainability Assessment of Wastewater Treatment Networks using the P-graph Approach: A Tannery Waste Case Study JF - CHEMICAL ENGINEERING TRANSACTIONS J2 - CHEM ENG TR VL - 88 PY - 2021 SP - 493 EP - 498 PG - 6 SN - 1974-9791 DO - 10.3303/CET2188082 UR - https://m2.mtmt.hu/api/publication/32519492 ID - 32519492 N1 - Department of Chemical Engineering, Henry M. Rowan College of Engineering, Rowan University, GlassboroNJ, United States Department of Chemical and Environmental Process Engineering, Budapest University of Technology and Economics, Hungary Department of Computer Science and Systems Technology, University of Pannonia, Veszprém, Hungary Research Institute of Applied Earth Sciences, University of Miskolc, Miskolc, Hungary Széchenyi István University, Győr, Hungary Export Date: 29 April 2022 Correspondence Address: Yenkie, K.M.; Department of Chemical Engineering, Glassboro, United States; email: yenkie@rowan.edu LA - English DB - MTMT ER -