Advanced Computational Methods for Modeling, Prediction and Optimization—A Review

This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intell...

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Published in:Materials Vol. 17; no. 14; p. 3521
Main Authors: Krzywanski, Jaroslaw, Sosnowski, Marcin, Grabowska, Karolina, Zylka, Anna, Lasek, Lukasz, Kijo-Kleczkowska, Agnieszka
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 16.07.2024
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ISSN:1996-1944, 1996-1944
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Abstract This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: “Computational Methods: Modeling, Simulations, and Optimization of Complex Systems”; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions.
AbstractList This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: "Computational Methods: Modeling, Simulations, and Optimization of Complex Systems"; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions.
This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: "Computational Methods: Modeling, Simulations, and Optimization of Complex Systems"; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions.This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in materials engineering, mechanical engineering, and energy systems. We identified key trends and highlighted the integration of artificial intelligence (AI) with traditional computational methods. Some of the cited works were previously published within the topic: "Computational Methods: Modeling, Simulations, and Optimization of Complex Systems"; thus, this article compiles the latest reports from this field. The work presents various contemporary applications of advanced computational algorithms, including AI methods. It also introduces proposals for novel strategies in materials production and optimization methods within the energy systems domain. It is essential to optimize the properties of materials used in energy. Our findings demonstrate significant improvements in accuracy and efficiency, offering valuable insights for researchers and practitioners. This review contributes to the field by synthesizing state-of-the-art developments and suggesting directions for future research, underscoring the critical role of these methods in advancing engineering and technological solutions.
Author Grabowska, Karolina
Krzywanski, Jaroslaw
Zylka, Anna
Lasek, Lukasz
Kijo-Kleczkowska, Agnieszka
Sosnowski, Marcin
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  givenname: Marcin
  orcidid: 0000-0002-1906-9476
  surname: Sosnowski
  fullname: Sosnowski, Marcin
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  givenname: Karolina
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  surname: Grabowska
  fullname: Grabowska, Karolina
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  givenname: Anna
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  surname: Zylka
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  givenname: Lukasz
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  surname: Lasek
  fullname: Lasek, Lukasz
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  surname: Kijo-Kleczkowska
  fullname: Kijo-Kleczkowska, Agnieszka
BackLink https://www.ncbi.nlm.nih.gov/pubmed/39063813$$D View this record in MEDLINE/PubMed
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Cites_doi 10.1038/s43246-021-00209-z
10.1016/j.apenergy.2019.113525
10.1108/HFF-09-2017-0357
10.3390/a16010019
10.1016/j.cep.2021.108397
10.3390/ma16031164
10.3390/en16155674
10.3390/ma15072511
10.1193/1.1585907
10.3390/ma16165720
10.1016/j.ins.2023.119260
10.1002/app.54883
10.3390/e24050711
10.1016/S0141-0296(02)00038-X
10.1016/j.applthermaleng.2022.119637
10.1080/23311916.2016.1181821
10.3390/e25010013
10.1016/j.msec.2020.110754
10.3390/ma16083213
10.3390/e24030408
10.1038/s41578-020-00260-1
10.3390/ma15072669
10.1016/j.physa.2023.129490
10.1080/01457631003604434
10.1002/adem.202300104
10.1051/matecconf/201824005014
10.3390/ma16175927
10.1016/j.mex.2022.101629
10.1038/s41524-021-00594-6
10.3390/ma14133520
10.3390/ma16041753
10.3390/make5020025
10.3390/e24081025
10.1038/nmat4717
10.3390/e24091213
10.1186/s12544-023-00624-y
10.1021/acs.chemmater.6b02724
10.1016/j.ijsolstr.2023.112545
10.1016/j.energy.2023.130168
10.3390/ma15031138
10.1126/sciadv.aaq1566
10.1016/j.rser.2021.111385
10.3390/ma16247580
10.1002/inf2.12028
10.1002/pro.4841
10.3390/e24040478
10.1038/s41524-023-01185-3
10.1016/S1385-8947(00)00140-6
10.3390/e25010009
10.3390/ma16227238
10.1007/s42114-023-00712-6
10.1002/solr.202000097
10.1007/s11831-021-09699-z
10.1016/j.icheatmasstransfer.2024.107262
10.3390/ma15207076
10.1007/978-981-99-8867-9_34
10.1016/j.compstruc.2023.107214
10.1016/j.iot.2022.100514
10.1007/978-981-99-8479-4_17
10.1016/j.prime.2023.100404
10.1016/j.scib.2021.01.022
10.1002/app.50956
10.3390/computation10040052
10.3390/ma15010045
10.1073/pnas.1607412113
10.3390/ma15113758
10.1016/j.applthermaleng.2023.120200
10.3390/en16248078
10.3390/computation10060088
10.1016/j.ress.2023.109884
10.1680/macr.2008.00068
10.1051/matecconf/201824001010
10.3390/e25010052
10.1007/s42114-023-00799-x
10.3390/ma14247680
10.3390/ma16206794
10.1002/adma.201600377
10.1038/s41598-023-50832-8
10.1016/j.physd.2019.132306
10.3390/en15218095
10.1109/ICIEA.2019.8833686
10.1016/j.jobe.2021.102727
10.3390/en12234441
10.3390/make5020033
10.1109/ACCESS.2019.2947542
10.3390/ma16031286
10.1016/B978-0-323-85484-9.00004-2
10.1016/j.cpc.2023.108994
10.1016/j.actamat.2019.03.010
10.1016/j.padiff.2023.100608
10.3390/ma16051906
10.3390/make4030039
10.3390/min10110958
10.1038/ncomms11241
10.3390/e24040525
10.1109/JSEN.2021.3116937
10.1016/j.matdes.2017.10.002
10.3390/e21111047
10.3390/e24121787
10.1002/advs.201900808
10.3390/en15061966
10.1038/npjcompumats.2016.28
10.3390/ma13030680
10.1002/9780470685853
10.3390/ma13153303
10.3390/en16041620
10.3390/ma15041587
10.1016/j.jpdc.2023.104797
10.1038/s41598-024-51479-9
10.3390/en15207700
10.1111/exsy.13537
10.1038/s41524-019-0221-0
10.3390/en16217311
10.3390/en15196955
10.1109/TII.2015.2500891
10.1038/nature17439
10.1016/j.fuproc.2009.11.008
10.1016/j.compstruct.2018.03.063
10.3390/en16155661
10.3390/en16093713
10.1016/j.compstruct.2012.09.001
10.1016/j.jtice.2020.11.003
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References Krzywanski (ref_58) 2018; 28
ref_94
ref_91
ref_90
You (ref_75) 2020; 116
ref_14
Kalita (ref_70) 2022; 29
Kim (ref_56) 2009; 61
Roussel (ref_125) 2022; 4
ref_98
Jiang (ref_5) 2020; 6
ref_97
Hirzel (ref_82) 2016; 15
ref_95
Krokida (ref_113) 2000; 79
ref_18
Chudasama (ref_25) 2022; 9
ref_15
Ren (ref_87) 2018; 4
Alaei (ref_12) 2024; 16
Calgan (ref_23) 2024; 635
Xu (ref_41) 2021; 21
Gupta (ref_96) 2024; 10
Wei (ref_92) 2019; 1
Yalamanchi (ref_16) 2024; 14
ref_127
Chen (ref_42) 2016; 12
Krzywanski (ref_62) 2023; 225
ref_120
ref_22
ref_122
ref_123
Surmiak (ref_102) 2020; 4
Sobczyk (ref_13) 2024; 291
Grabowska (ref_121) 2018; 240
ref_26
Goswami (ref_124) 2023; 25
ref_72
Sherstinsky (ref_45) 2020; 404
ref_71
Schmidt (ref_9) 2019; 5
Balladini (ref_28) 2024; 185
Krzywanski (ref_77) 2010; 91
Tariq (ref_53) 2021; 41
ref_79
ref_78
Abdulkareem (ref_2) 2019; 7
ref_76
ref_73
Krzywanski (ref_100) 2024; 152
Arora (ref_21) 2024; 844
Huchet (ref_46) 2023; 221
Algarni (ref_126) 2023; 5
Liu (ref_4) 2023; 6
Nikbakt (ref_69) 2018; 195
ref_80
Yue (ref_20) 2024; 14
Ming (ref_48) 2023; 643
Oliynyk (ref_84) 2016; 28
Kheiri (ref_104) 2020; 111
Hegger (ref_54) 2003; 100
ref_89
Chen (ref_19) 2024; 33
Chen (ref_110) 2020; 7
Kalantari (ref_29) 2024; 7
Krzywanski (ref_59) 2018; 240
Wang (ref_103) 2021; 66
ref_50
Bakir (ref_55) 2002; 24
ref_52
ref_51
Stanev (ref_10) 2021; 2
Scapino (ref_119) 2019; 253
Tang (ref_49) 2018; 137
ref_61
Modi (ref_6) 2022; 20
Raccuglia (ref_93) 2016; 533
Alasfar (ref_66) 2024; 141
Zhang (ref_112) 2021; 164
ref_67
ref_65
ref_64
ref_63
Xue (ref_85) 2016; 7
Huber (ref_105) 2021; 7
Gnatowski (ref_60) 2024; 290
Ward (ref_37) 2016; 2
Lynn (ref_57) 1996; 12
Gill (ref_1) 2022; 19
Padhi (ref_111) 2016; 3
ref_115
ref_114
ref_117
ref_116
ref_118
Ongar (ref_128) 2023; 55
ref_36
ref_35
ref_34
ref_33
ref_32
Wang (ref_74) 2021; 138
ref_31
ref_30
Xue (ref_86) 2016; 113
ref_39
ref_38
Deng (ref_24) 2024; 243
Xiong (ref_27) 2024; 295
Jha (ref_68) 2013; 96
Treich (ref_83) 2016; 28
Vivekanandan (ref_99) 2023; 5
ref_108
ref_107
Tarragona (ref_109) 2021; 149
ref_47
ref_44
ref_43
ref_40
ref_101
Oliveira (ref_106) 2010; 31
Wen (ref_88) 2019; 170
Ganie (ref_11) 2024; 9
Krokos (ref_17) 2024; 286–287
ref_8
Hao (ref_3) 2023; 6
ref_7
Himanen (ref_81) 2019; 6
References_xml – volume: 2
  start-page: 105
  year: 2021
  ident: ref_10
  article-title: Artificial Intelligence for Search and Discovery of Quantum Materials
  publication-title: Commun. Mater.
  doi: 10.1038/s43246-021-00209-z
– volume: 253
  start-page: 113525
  year: 2019
  ident: ref_119
  article-title: Modeling the Performance of a Sorption Thermal Energy Storage Reactor Using Artificial Neural Networks
  publication-title: Appl. Energy
  doi: 10.1016/j.apenergy.2019.113525
– volume: 28
  start-page: 254
  year: 2018
  ident: ref_58
  article-title: Fuzzy Logic and Bed-to-Wall Heat Transfer in a Large-Scale CFBC
  publication-title: Int. J. Numer. Methods Heat Fluid Flow
  doi: 10.1108/HFF-09-2017-0357
– ident: ref_33
  doi: 10.3390/a16010019
– volume: 164
  start-page: 108397
  year: 2021
  ident: ref_112
  article-title: Process Intensification in Micro-Fluidized Bed Systems: A Review
  publication-title: Chem. Eng. Process.-Process Intensif.
  doi: 10.1016/j.cep.2021.108397
– ident: ref_122
  doi: 10.3390/ma16031164
– ident: ref_117
  doi: 10.3390/en16155674
– ident: ref_123
  doi: 10.3390/ma15072511
– volume: 12
  start-page: 715
  year: 1996
  ident: ref_57
  article-title: Seismic Evaluation of Existing Reinforced Concrete Building Columns
  publication-title: Earthq. Spectra
  doi: 10.1193/1.1585907
– ident: ref_73
  doi: 10.3390/ma16165720
– volume: 643
  start-page: 119260
  year: 2023
  ident: ref_48
  article-title: Handling Constrained Many-Objective Optimization Problems via Determinantal Point Processes
  publication-title: Inf. Sci.
  doi: 10.1016/j.ins.2023.119260
– volume: 141
  start-page: e54883
  year: 2024
  ident: ref_66
  article-title: Optimization of the Elastic Modulus for Polymeric Nanocomposite Membranes
  publication-title: J. Appl. Polym. Sci.
  doi: 10.1002/app.54883
– ident: ref_38
  doi: 10.3390/e24050711
– volume: 24
  start-page: 1105
  year: 2002
  ident: ref_55
  article-title: A New Design Equation for Predicting the Joint Shear Strength of Monotonically Loaded Exterior Beam-Column Joints
  publication-title: Eng. Struct.
  doi: 10.1016/S0141-0296(02)00038-X
– volume: 221
  start-page: 119637
  year: 2023
  ident: ref_46
  article-title: Rotary Kiln Process: An Overview of Physical Mechanisms, Models and Applications
  publication-title: Appl. Therm. Eng.
  doi: 10.1016/j.applthermaleng.2022.119637
– volume: 3
  start-page: 1181821
  year: 2016
  ident: ref_111
  article-title: Prediction of Bed Pressure Drop, Fluctuation and Expansion Ratios for Three-Phase Fluidization of Ternary Mixtures of Dolomite in a Conical Conduit
  publication-title: Cogent Eng.
  doi: 10.1080/23311916.2016.1181821
– ident: ref_47
  doi: 10.3390/e25010013
– volume: 111
  start-page: 110754
  year: 2020
  ident: ref_104
  article-title: Antibacterial Efficiency Assessment of Polymer-Nanoparticle Composites Using a High-Throughput Microfluidic Platform
  publication-title: Mater. Sci. Eng. C
  doi: 10.1016/j.msec.2020.110754
– ident: ref_80
  doi: 10.3390/ma16083213
– ident: ref_39
  doi: 10.3390/e24030408
– volume: 6
  start-page: 679
  year: 2020
  ident: ref_5
  article-title: Deep Neural Networks for the Evaluation and Design of Photonic Devices
  publication-title: Nat. Rev. Mater.
  doi: 10.1038/s41578-020-00260-1
– ident: ref_71
  doi: 10.3390/ma15072669
– volume: 635
  start-page: 129490
  year: 2024
  ident: ref_23
  article-title: Incommensurate Fractional-Order Analysis of a Chaotic System Based on Interaction between Dark Matter and Dark Energy with Engineering Applications
  publication-title: Phys. A Stat. Mech. Its Appl.
  doi: 10.1016/j.physa.2023.129490
– volume: 31
  start-page: 941
  year: 2010
  ident: ref_106
  article-title: Solar-Powered Adsorption Icemaker with Double-Stage Mass Recovery Cycle
  publication-title: Heat Transf. Eng.
  doi: 10.1080/01457631003604434
– volume: 25
  start-page: 2300104
  year: 2023
  ident: ref_124
  article-title: Artificial Intelligence in Material Engineering: A Review on Applications of Artificial Intelligence in Material Engineering
  publication-title: Adv. Eng. Mater.
  doi: 10.1002/adem.202300104
– volume: 240
  start-page: 05014
  year: 2018
  ident: ref_59
  article-title: Modeling of a Re-Heat Two-Stage Adsorption Chiller by AI Approach
  publication-title: MATEC Web Conf.
  doi: 10.1051/matecconf/201824005014
– ident: ref_36
  doi: 10.3390/ma16175927
– volume: 9
  start-page: 101629
  year: 2022
  ident: ref_25
  article-title: Fuzzy Inference Systems for Mineral Prospectivity Modeling-Optimized Using Monte Carlo Simulations
  publication-title: MethodsX
  doi: 10.1016/j.mex.2022.101629
– volume: 7
  start-page: 136
  year: 2021
  ident: ref_105
  article-title: Common Workflows for Computing Material Properties Using Different Quantum Engines
  publication-title: Npj Comput Mater
  doi: 10.1038/s41524-021-00594-6
– ident: ref_79
  doi: 10.3390/ma14133520
– ident: ref_67
  doi: 10.3390/ma16041753
– volume: 5
  start-page: 418
  year: 2023
  ident: ref_99
  article-title: A Reinforcement Learning Approach for Scheduling Problems with Improved Generalization through Order Swapping
  publication-title: Mach. Learn. Knowl. Extr.
  doi: 10.3390/make5020025
– ident: ref_8
  doi: 10.3390/e24081025
– volume: 15
  start-page: 1120
  year: 2016
  ident: ref_82
  article-title: Design of Efficient Molecular Organic Light-Emitting Diodes by a High-Throughput Virtual Screening and Experimental Approach
  publication-title: Nat. Mater
  doi: 10.1038/nmat4717
– ident: ref_95
  doi: 10.3390/e24091213
– volume: 16
  start-page: 1
  year: 2024
  ident: ref_12
  article-title: Synchromodal Transport Re-Planning: An Agent-Based Simulation Approach
  publication-title: Eur. Transp. Res. Rev.
  doi: 10.1186/s12544-023-00624-y
– volume: 28
  start-page: 7324
  year: 2016
  ident: ref_84
  article-title: High-Throughput Machine-Learning-Driven Synthesis of Full-Heusler Compounds
  publication-title: Chem. Mater.
  doi: 10.1021/acs.chemmater.6b02724
– volume: 286–287
  start-page: 112545
  year: 2024
  ident: ref_17
  article-title: A Graph-Based Probabilistic Geometric Deep Learning Framework with Online Enforcement of Physical Constraints to Predict the Criticality of Defects in Porous Materials
  publication-title: Int. J. Solids Struct.
  doi: 10.1016/j.ijsolstr.2023.112545
– volume: 290
  start-page: 130168
  year: 2024
  ident: ref_60
  article-title: Experimental Research and Prediction of Heat Generation during Plastics, Coal and Biomass Waste Combustion Using Thermal Analysis Methods
  publication-title: Energy
  doi: 10.1016/j.energy.2023.130168
– ident: ref_127
  doi: 10.3390/ma15031138
– volume: 4
  start-page: eaaq1566
  year: 2018
  ident: ref_87
  article-title: Accelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experiments
  publication-title: Sci. Adv.
  doi: 10.1126/sciadv.aaq1566
– volume: 149
  start-page: 111385
  year: 2021
  ident: ref_109
  article-title: Systematic Review on Model Predictive Control Strategies Applied to Active Thermal Energy Storage Systems
  publication-title: Renew. Sustain. Energy Rev.
  doi: 10.1016/j.rser.2021.111385
– ident: ref_115
– ident: ref_65
  doi: 10.3390/ma16247580
– volume: 1
  start-page: 338
  year: 2019
  ident: ref_92
  article-title: Machine Learning in Materials Science
  publication-title: InfoMat
  doi: 10.1002/inf2.12028
– volume: 33
  start-page: e4841
  year: 2024
  ident: ref_19
  article-title: TEPCAM: Prediction of T-Cell Receptor–Epitope Binding Specificity via Interpretable Deep Learning
  publication-title: Protein Sci.
  doi: 10.1002/pro.4841
– ident: ref_30
  doi: 10.3390/e24040478
– volume: 10
  start-page: 1
  year: 2024
  ident: ref_96
  article-title: Structure-Aware Graph Neural Network Based Deep Transfer Learning Framework for Enhanced Predictive Analytics on Diverse Materials Datasets
  publication-title: npj Comput. Mater.
  doi: 10.1038/s41524-023-01185-3
– volume: 79
  start-page: 1
  year: 2000
  ident: ref_113
  article-title: Pareto Design of Fluidized Bed Dryers
  publication-title: Chem. Eng. J.
  doi: 10.1016/S1385-8947(00)00140-6
– ident: ref_34
  doi: 10.3390/e25010009
– volume: 20
  start-page: 25
  year: 2022
  ident: ref_6
  article-title: Role of Artificial Intelligence in Detecting Colonic Polyps during Intestinal Endoscopy
  publication-title: Eng. Sci.
– ident: ref_76
  doi: 10.3390/ma16227238
– volume: 6
  start-page: 129
  year: 2023
  ident: ref_3
  article-title: Artificial Optoelectronic Synaptic Devices Based on Vertical Organic Field-Effect Transistors with Low Energy Consumption
  publication-title: Adv. Compos. Hybrid. Mater.
  doi: 10.1007/s42114-023-00712-6
– volume: 4
  start-page: 2000097
  year: 2020
  ident: ref_102
  article-title: High-Throughput Characterization of Perovskite Solar Cells for Rapid Combinatorial Screening
  publication-title: Sol. RRL
  doi: 10.1002/solr.202000097
– volume: 29
  start-page: 3305
  year: 2022
  ident: ref_70
  article-title: A Comprehensive Review on High-Fidelity and Metamodel-Based Optimization of Composite Laminates
  publication-title: Arch. Comput. Methods Eng.
  doi: 10.1007/s11831-021-09699-z
– volume: 152
  start-page: 107262
  year: 2024
  ident: ref_100
  article-title: Towards Enhanced Heat and Mass Exchange in Adsorption Systems: The Role of AutoML and Fluidized Bed Innovations
  publication-title: Int. Commun. Heat Mass Transf.
  doi: 10.1016/j.icheatmasstransfer.2024.107262
– volume: 55
  start-page: 2023
  year: 2023
  ident: ref_128
  article-title: Optimization of the Design and Operating Characteristics of a Boiler Based on Three- Dimensional Mathematical Modeling
  publication-title: Bulg. Chem. Commun.
– ident: ref_52
  doi: 10.3390/ma15207076
– ident: ref_18
  doi: 10.1007/978-981-99-8867-9_34
– volume: 291
  start-page: 107214
  year: 2024
  ident: ref_13
  article-title: Computational Modelling of Historic Masonry Railroad Arch Bridges
  publication-title: Comput. Struct.
  doi: 10.1016/j.compstruc.2023.107214
– volume: 19
  start-page: 100514
  year: 2022
  ident: ref_1
  article-title: AI for next Generation Computing: Emerging Trends and Future Directions
  publication-title: Internet Things
  doi: 10.1016/j.iot.2022.100514
– volume: 844
  start-page: 229
  year: 2024
  ident: ref_21
  article-title: Data-Driven Decision Support Systems in E-Governance: Leveraging AI for Policymaking
  publication-title: Lect. Notes Netw. Syst.
  doi: 10.1007/978-981-99-8479-4_17
– volume: 7
  start-page: 100404
  year: 2024
  ident: ref_29
  article-title: GPU-Based Transient Analysis of Modern Grids Deploying a Hybrid DDM Algorithm
  publication-title: e-Prime—Adv. Electr. Eng. Electron. Energy
  doi: 10.1016/j.prime.2023.100404
– volume: 66
  start-page: 958
  year: 2021
  ident: ref_103
  article-title: Towards Enhanced Strength-Ductility Synergy via Hierarchical Design in Steels: From the Material Genome Perspective
  publication-title: Sci. Bull.
  doi: 10.1016/j.scib.2021.01.022
– volume: 138
  start-page: 50956
  year: 2021
  ident: ref_74
  article-title: Correlating the 3D Melt Electrospun Polycaprolactone Fiber Diameter and Process Parameters Using Neural Networks
  publication-title: J Appl. Polym. Sci
  doi: 10.1002/app.50956
– ident: ref_107
  doi: 10.3390/computation10040052
– ident: ref_91
  doi: 10.3390/ma15010045
– volume: 113
  start-page: 13301
  year: 2016
  ident: ref_86
  article-title: Accelerated Search for BaTiO3 -Based Piezoelectrics with Vertical Morphotropic Phase Boundary Using Bayesian Learning
  publication-title: Proc. Natl. Acad. Sci. USA
  doi: 10.1073/pnas.1607412113
– ident: ref_51
  doi: 10.3390/ma15113758
– volume: 225
  start-page: 120200
  year: 2023
  ident: ref_62
  article-title: Heat and Mass Transfer Prediction in Fluidized Beds of Cooling and Desalination Systems by AI Approach
  publication-title: Appl. Therm. Eng.
  doi: 10.1016/j.applthermaleng.2023.120200
– ident: ref_63
  doi: 10.3390/en16248078
– ident: ref_7
  doi: 10.3390/computation10060088
– volume: 243
  start-page: 109884
  year: 2024
  ident: ref_24
  article-title: A Novel Methodology to Quantify the Impact of Safety Barriers on Maritime Operational Risk Based on a Probabilistic Network
  publication-title: Reliab. Eng. Syst. Saf.
  doi: 10.1016/j.ress.2023.109884
– volume: 61
  start-page: 119
  year: 2009
  ident: ref_56
  article-title: Joint Shear Behaviour of Reinforced Concrete Beam–Column Connections
  publication-title: Mag. Concr. Res.
  doi: 10.1680/macr.2008.00068
– volume: 240
  start-page: 01010
  year: 2018
  ident: ref_121
  article-title: Analysis of Heat Transfer in a Coated Bed of an Adsorption Chiller
  publication-title: MATEC Web Conf.
  doi: 10.1051/matecconf/201824001010
– volume: 100
  start-page: 654
  year: 2003
  ident: ref_54
  article-title: Nonseismic Design of Beam-Column Joints
  publication-title: Struct. J.
– ident: ref_40
  doi: 10.3390/e25010052
– volume: 6
  start-page: 217
  year: 2023
  ident: ref_4
  article-title: Flexible Cementite/Ferroferric Oxide/Silicon Dioxide/Carbon Nanofibers Composite Membrane with Low-Frequency Dispersion Weakly Negative Permittivity
  publication-title: Adv. Compos. Hybrid. Mater.
  doi: 10.1007/s42114-023-00799-x
– ident: ref_94
  doi: 10.3390/ma14247680
– ident: ref_61
  doi: 10.3390/ma16206794
– volume: 28
  start-page: 6277
  year: 2016
  ident: ref_83
  article-title: Rational Co-Design of Polymer Dielectrics for Energy Storage
  publication-title: Adv. Mater.
  doi: 10.1002/adma.201600377
– volume: 14
  start-page: 947
  year: 2024
  ident: ref_20
  article-title: Machine Learning Assisted Rational Design of Antimicrobial Peptides Based on Human Endogenous Proteins and Their Applications for Cosmetic Preservative System Optimization
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-023-50832-8
– volume: 404
  start-page: 132306
  year: 2020
  ident: ref_45
  article-title: Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
  publication-title: Phys. D Nonlinear Phenom.
  doi: 10.1016/j.physd.2019.132306
– ident: ref_116
  doi: 10.3390/en15218095
– ident: ref_43
  doi: 10.1109/ICIEA.2019.8833686
– volume: 41
  start-page: 102727
  year: 2021
  ident: ref_53
  article-title: A Regression Model for Predicting the Shear Strength of RC Knee Joint Subjected to Opening and Closing Moment
  publication-title: J. Build. Eng.
  doi: 10.1016/j.jobe.2021.102727
– ident: ref_120
  doi: 10.3390/en12234441
– volume: 5
  start-page: 560
  year: 2023
  ident: ref_126
  article-title: Systematic Review of Recommendation Systems for Course Selection
  publication-title: Mach. Learn. Knowl. Extr.
  doi: 10.3390/make5020033
– volume: 7
  start-page: 153123
  year: 2019
  ident: ref_2
  article-title: A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2947542
– ident: ref_50
  doi: 10.3390/ma16031286
– ident: ref_72
  doi: 10.1016/B978-0-323-85484-9.00004-2
– volume: 295
  start-page: 108994
  year: 2024
  ident: ref_27
  article-title: GPIC: A Set of High-Efficiency CUDA Fortran Code Using Gpu for Particle-in-Cell Simulation in Space Physics
  publication-title: Comput. Phys. Commun.
  doi: 10.1016/j.cpc.2023.108994
– volume: 170
  start-page: 109
  year: 2019
  ident: ref_88
  article-title: Machine Learning Assisted Design of High Entropy Alloys with Desired Property
  publication-title: Acta Mater.
  doi: 10.1016/j.actamat.2019.03.010
– volume: 9
  start-page: 100608
  year: 2024
  ident: ref_11
  article-title: New Investigation of the Analytical Behaviors for Some Nonlinear PDEs in Mathematical Physics and Modern Engineering
  publication-title: Partial Differ. Equ. Appl. Math.
  doi: 10.1016/j.padiff.2023.100608
– ident: ref_101
  doi: 10.3390/ma16051906
– volume: 4
  start-page: 803
  year: 2022
  ident: ref_125
  article-title: Sensor Fusion for Occupancy Estimation: A Study Using Multiple Lecture Rooms in a Complex Building
  publication-title: Mach. Learn. Knowl. Extr.
  doi: 10.3390/make4030039
– ident: ref_44
  doi: 10.3390/min10110958
– volume: 7
  start-page: 11241
  year: 2016
  ident: ref_85
  article-title: Accelerated Search for Materials with Targeted Properties by Adaptive Design
  publication-title: Nat. Commun.
  doi: 10.1038/ncomms11241
– ident: ref_31
  doi: 10.3390/e24040525
– volume: 21
  start-page: 27632
  year: 2021
  ident: ref_41
  article-title: A Soft Sensor Modeling of Cement Rotary Kiln Temperature Field Based on Model-Driven and Data-Driven Methods
  publication-title: IEEE Sens. J.
  doi: 10.1109/JSEN.2021.3116937
– volume: 137
  start-page: 214
  year: 2018
  ident: ref_49
  article-title: Development of High-Performance Energy Absorption Component Based on the Structural Design and Nanocrystallization
  publication-title: Mater. Des.
  doi: 10.1016/j.matdes.2017.10.002
– ident: ref_14
  doi: 10.3390/e21111047
– ident: ref_32
  doi: 10.3390/e24121787
– volume: 6
  start-page: 1900808
  year: 2019
  ident: ref_81
  article-title: Data-Driven Materials Science: Status, Challenges, and Perspectives
  publication-title: Adv. Sci.
  doi: 10.1002/advs.201900808
– volume: 7
  start-page: 329
  year: 2020
  ident: ref_110
  article-title: A Model Predictive Control Method for Hybrid Energy Storage Systems
  publication-title: CSEE J. Power Energy Syst.
– ident: ref_97
  doi: 10.3390/en15061966
– volume: 2
  start-page: 16028
  year: 2016
  ident: ref_37
  article-title: A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials
  publication-title: npj Comput. Mater.
  doi: 10.1038/npjcompumats.2016.28
– ident: ref_89
  doi: 10.3390/ma13030680
– ident: ref_26
  doi: 10.1002/9780470685853
– ident: ref_90
  doi: 10.3390/ma13153303
– ident: ref_35
  doi: 10.3390/en16041620
– ident: ref_78
  doi: 10.3390/ma15041587
– volume: 185
  start-page: 104797
  year: 2024
  ident: ref_28
  article-title: Exploring Energy Saving Opportunities in Fault Tolerant HPC Systems
  publication-title: J. Parallel Distrib. Comput.
  doi: 10.1016/j.jpdc.2023.104797
– volume: 14
  start-page: 930
  year: 2024
  ident: ref_16
  article-title: Estimation of Pore Structure and Permeability in Tight Carbonate Reservoir Based on Machine Learning (ML) Algorithm Using SEM Images of Jaisalmer Sub-Basin, India
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-024-51479-9
– ident: ref_114
  doi: 10.3390/en15207700
– ident: ref_22
  doi: 10.1111/exsy.13537
– volume: 5
  start-page: 83
  year: 2019
  ident: ref_9
  article-title: Recent Advances and Applications of Machine Learning in Solid-State Materials Science
  publication-title: npj Comput. Mater.
  doi: 10.1038/s41524-019-0221-0
– ident: ref_64
  doi: 10.3390/en16217311
– ident: ref_98
  doi: 10.3390/en15196955
– ident: ref_15
– volume: 12
  start-page: 148
  year: 2016
  ident: ref_42
  article-title: Recognition of the Temperature Condition of a Rotary Kiln Using Dynamic Features of a Series of Blurry Flame Images
  publication-title: IEEE Trans. Ind. Inf.
  doi: 10.1109/TII.2015.2500891
– volume: 533
  start-page: 73
  year: 2016
  ident: ref_93
  article-title: Machine-Learning-Assisted Materials Discovery Using Failed Experiments
  publication-title: Nature
  doi: 10.1038/nature17439
– volume: 91
  start-page: 364
  year: 2010
  ident: ref_77
  article-title: Modeling of Solid Fuel Combustion in Oxygen-Enriched Atmosphere in Circulating Fluidized Bed Boiler. Part 2. Numerical simulations of heat transfer and gaseous pollutant emissions associated with coal combustion in O2/CO2 and O2/N2 atmospheres enriched with oxygen under circulating fluidized bed conditions
  publication-title: Fuel Process. Technol.
  doi: 10.1016/j.fuproc.2009.11.008
– volume: 195
  start-page: 158
  year: 2018
  ident: ref_69
  article-title: A Review on Optimization of Composite Structures Part I: Laminated Composites
  publication-title: Compos. Struct.
  doi: 10.1016/j.compstruct.2018.03.063
– ident: ref_108
  doi: 10.3390/en16155661
– ident: ref_118
  doi: 10.3390/en16093713
– volume: 96
  start-page: 833
  year: 2013
  ident: ref_68
  article-title: A Critical Review of Recent Research on Functionally Graded Plates
  publication-title: Compos. Struct.
  doi: 10.1016/j.compstruct.2012.09.001
– volume: 116
  start-page: 238
  year: 2020
  ident: ref_75
  article-title: Deep Learning Techniques for Polycaprolactone Molecular Weight Prediction via Enzymatic Polymerization Process
  publication-title: J. Taiwan Inst. Chem. Eng.
  doi: 10.1016/j.jtice.2020.11.003
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SecondaryResourceType review_article
Snippet This paper provides a comprehensive review of recent advancements in computational methods for modeling, simulation, and optimization of complex systems in...
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SubjectTerms Algorithms
Artificial intelligence
Cloud computing
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Title Advanced Computational Methods for Modeling, Prediction and Optimization—A Review
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Volume 17
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