Pub Date : 2023-11-01DOI: 10.1007/s11081-023-09854-4
Isaac Elishakoff, Moshe Eisenberger, Alexander Mercer
{"title":"An interesting project in the “strength of materials” or “machine design” courses","authors":"Isaac Elishakoff, Moshe Eisenberger, Alexander Mercer","doi":"10.1007/s11081-023-09854-4","DOIUrl":"https://doi.org/10.1007/s11081-023-09854-4","url":null,"abstract":"","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135320479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.1007/s11081-023-09857-1
Hua-Ming Huang, Elena Raponi, Fabian Duddeck, Stefan Menzel, Mariusz Bujny
Abstract Assembly complexity and manufacturing costs of engineering structures can be significantly reduced by using periodic mechanical components, which are defined by combining multiple identical unit cells into a global topology. Additionally, the superior energy-absorbing properties of lattice-based periodic structures can potentially enhance the overall performance in crash-related applications. Recent research developments in periodic topology optimization (PTO) have shown its efficacy for tackling new design problems and finding advanced novel structures. However, most of these methods rely on gradient information in the optimization process, which poses difficulties for crash problems where analytical sensitivities are usually not directly applicable. In this paper, we present an effective periodic evolutionary level set method (P-EA-LSM) for the optimization of periodic structures. P-EA-LSM uses a low-dimensional level-set representation based on moving morphable components to parametrize a single unit cell, which is replicated in the design domain according to a predefined pattern. The unit cell is optimized using an evolutionary algorithm and the structural responses are calculated for the entire system. We initially assess the performance of P-EA-LSM using three 2D minimum compliance test cases with varying periodicities. Our results demonstrate that our approach produces solutions comparable to other state-of-the-art methods for PTO while keeping a low dimensionality of the optimization problem. Subsequently, we effectively evaluate the capabilities of P-EA-LSM in a crashworthiness scenario. This particular application highlights the significant potential of the method, which does not rely on analytical sensitivities.
{"title":"Topology optimization of periodic structures for crash and static load cases using the evolutionary level set method","authors":"Hua-Ming Huang, Elena Raponi, Fabian Duddeck, Stefan Menzel, Mariusz Bujny","doi":"10.1007/s11081-023-09857-1","DOIUrl":"https://doi.org/10.1007/s11081-023-09857-1","url":null,"abstract":"Abstract Assembly complexity and manufacturing costs of engineering structures can be significantly reduced by using periodic mechanical components, which are defined by combining multiple identical unit cells into a global topology. Additionally, the superior energy-absorbing properties of lattice-based periodic structures can potentially enhance the overall performance in crash-related applications. Recent research developments in periodic topology optimization (PTO) have shown its efficacy for tackling new design problems and finding advanced novel structures. However, most of these methods rely on gradient information in the optimization process, which poses difficulties for crash problems where analytical sensitivities are usually not directly applicable. In this paper, we present an effective periodic evolutionary level set method (P-EA-LSM) for the optimization of periodic structures. P-EA-LSM uses a low-dimensional level-set representation based on moving morphable components to parametrize a single unit cell, which is replicated in the design domain according to a predefined pattern. The unit cell is optimized using an evolutionary algorithm and the structural responses are calculated for the entire system. We initially assess the performance of P-EA-LSM using three 2D minimum compliance test cases with varying periodicities. Our results demonstrate that our approach produces solutions comparable to other state-of-the-art methods for PTO while keeping a low dimensionality of the optimization problem. Subsequently, we effectively evaluate the capabilities of P-EA-LSM in a crashworthiness scenario. This particular application highlights the significant potential of the method, which does not rely on analytical sensitivities.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-21DOI: 10.1007/s11081-023-09829-5
Nathan Stewart, Bryan Arguello, Matthew Hoffman, Bethany Nicholson, Richard Garrett
Abstract Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.
{"title":"Optimal mitigation and control over power system dynamics for stochastic grid resilience","authors":"Nathan Stewart, Bryan Arguello, Matthew Hoffman, Bethany Nicholson, Richard Garrett","doi":"10.1007/s11081-023-09829-5","DOIUrl":"https://doi.org/10.1007/s11081-023-09829-5","url":null,"abstract":"Abstract Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135513056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-19DOI: 10.1007/s11081-023-09861-5
J. M. Martínez, L. T. Santos
{"title":"Inexact-restoration modelling with monotone interpolation and parameter estimation","authors":"J. M. Martínez, L. T. Santos","doi":"10.1007/s11081-023-09861-5","DOIUrl":"https://doi.org/10.1007/s11081-023-09861-5","url":null,"abstract":"","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-14DOI: 10.1007/s11081-023-09856-2
Sanjula Kammammettu, Shu-Bo Yang, Zukui Li
{"title":"Distributionally robust optimization using optimal transport for Gaussian mixture models","authors":"Sanjula Kammammettu, Shu-Bo Yang, Zukui Li","doi":"10.1007/s11081-023-09856-2","DOIUrl":"https://doi.org/10.1007/s11081-023-09856-2","url":null,"abstract":"","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135800313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-10DOI: 10.1007/s11081-023-09843-7
Jan Kronqvist, Boda Li, Jan Rolfes
Abstract In the present article we propose a mixed-integer approximation of adjustable-robust optimization problems, that have both, continuous and discrete variables on the lowest level. As these trilevel problems are notoriously hard to solve, we restrict ourselves to weakly-connected instances. Our approach allows us to approximate, and in some cases exactly represent, the trilevel problem as a single-level mixed-integer problem. This allows us to leverage the computational efficiency of state-of-the-art mixed-integer programming solvers. We demonstrate the value of this approach by applying it to the optimization of power systems, particularly to the control of smart converters.
{"title":"A mixed-integer approximation of robust optimization problems with mixed-integer adjustments","authors":"Jan Kronqvist, Boda Li, Jan Rolfes","doi":"10.1007/s11081-023-09843-7","DOIUrl":"https://doi.org/10.1007/s11081-023-09843-7","url":null,"abstract":"Abstract In the present article we propose a mixed-integer approximation of adjustable-robust optimization problems, that have both, continuous and discrete variables on the lowest level. As these trilevel problems are notoriously hard to solve, we restrict ourselves to weakly-connected instances. Our approach allows us to approximate, and in some cases exactly represent, the trilevel problem as a single-level mixed-integer problem. This allows us to leverage the computational efficiency of state-of-the-art mixed-integer programming solvers. We demonstrate the value of this approach by applying it to the optimization of power systems, particularly to the control of smart converters.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136294693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.1007/s11081-023-09853-5
Tim Diller, Anton Soppelsa, Himanshu Nagpal, Roberto Fedrizzi, Gregor Henze
Abstract The residential heating and cooling sector has been increasingly electrifying, predominantly using electrically driven heat pumps (HP) in combination with thermal/electrical energy storage systems. While these developments contribute to increased renewable and low carbon energy shares in the sector, exploiting the full potential of the technology requires a smart control of these systems that can account for predicted renewable energy availability in the future and the corresponding HP system performance. However, modelling a system featuring complex internal dynamics, in a way that is suitable for smart control, is challenging. Models need to be sophisticated enough to accurately capture the system's nonlinearities and intricacies while at the same time fast enough to enable a thorough search of the solutions space, in suitable computational time. Dynamic programming (DP) is a promising approach to smart controls, as it combines the ability to use complex, non-linear models while being an exhaustive search algorithm, guaranteeing that the global optimum is found. This paper presents an innovative modelling framework that entails reduced order models (ROM) of an HP substation's main components (i.e., HP and thermal energy storage—TES), elaborated in a fashion suitable for use in DP; these have been shaped as to include significant physical operating constraints (e.g., HP compressor variable speed, non-linear coefficient of performance—COP—dependency on outdoor and distribution temperature) affecting the system performance, while at the same time minimising the amount of state variables (i.e., TES temperatures, HP thermal and electric capacity) the optimizer needs to handle. In an application to an exemplary HP system, our system models compare remarkably well to detailed TRNSYS counterparts, used as a reference ground truth. The system achieves significant cost-saving enabled by the dynamic programming optimization approach, facilitating a 13% decrease in power consumption compared to conventional rule-based control.
{"title":"A dynamic programming based method for optimal control of a cascaded heat pump system with thermal energy storage","authors":"Tim Diller, Anton Soppelsa, Himanshu Nagpal, Roberto Fedrizzi, Gregor Henze","doi":"10.1007/s11081-023-09853-5","DOIUrl":"https://doi.org/10.1007/s11081-023-09853-5","url":null,"abstract":"Abstract The residential heating and cooling sector has been increasingly electrifying, predominantly using electrically driven heat pumps (HP) in combination with thermal/electrical energy storage systems. While these developments contribute to increased renewable and low carbon energy shares in the sector, exploiting the full potential of the technology requires a smart control of these systems that can account for predicted renewable energy availability in the future and the corresponding HP system performance. However, modelling a system featuring complex internal dynamics, in a way that is suitable for smart control, is challenging. Models need to be sophisticated enough to accurately capture the system's nonlinearities and intricacies while at the same time fast enough to enable a thorough search of the solutions space, in suitable computational time. Dynamic programming (DP) is a promising approach to smart controls, as it combines the ability to use complex, non-linear models while being an exhaustive search algorithm, guaranteeing that the global optimum is found. This paper presents an innovative modelling framework that entails reduced order models (ROM) of an HP substation's main components (i.e., HP and thermal energy storage—TES), elaborated in a fashion suitable for use in DP; these have been shaped as to include significant physical operating constraints (e.g., HP compressor variable speed, non-linear coefficient of performance—COP—dependency on outdoor and distribution temperature) affecting the system performance, while at the same time minimising the amount of state variables (i.e., TES temperatures, HP thermal and electric capacity) the optimizer needs to handle. In an application to an exemplary HP system, our system models compare remarkably well to detailed TRNSYS counterparts, used as a reference ground truth. The system achieves significant cost-saving enabled by the dynamic programming optimization approach, facilitating a 13% decrease in power consumption compared to conventional rule-based control.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-07DOI: 10.1007/s11081-023-09855-3
Jörg Lampe, Steffen Menz
{"title":"Optimized operational strategy of a solar reactor for thermochemical hydrogen generation","authors":"Jörg Lampe, Steffen Menz","doi":"10.1007/s11081-023-09855-3","DOIUrl":"https://doi.org/10.1007/s11081-023-09855-3","url":null,"abstract":"","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135254747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1007/s11081-023-09845-5
Dustin Kenefake, Efstratios N. Pistikopolous
{"title":"A novel parallel combinatorial algorithm for multiparametric programming","authors":"Dustin Kenefake, Efstratios N. Pistikopolous","doi":"10.1007/s11081-023-09845-5","DOIUrl":"https://doi.org/10.1007/s11081-023-09845-5","url":null,"abstract":"","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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