14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control最新文献

{"title":"BRIDGES MONITORING: AN APPLICATION OF AI WITH GAUSSIAN PROCESSES","authors":"R. Asso, R. Cucuzza, M. Rosso, D. Masera, G. Marano","doi":"10.7712/140121.7964.18426","DOIUrl":"https://doi.org/10.7712/140121.7964.18426","url":null,"abstract":". Monitoring and assessment of existing infrastructures is gaining attention in nowadays society as aging degradation reduces the residual structural safety. This work aims at providing a competitive procedure for the monitoring of bearings of bridges, based on data analysis coming from the use of strain gauges. It proposes an unsupervised learning (USL) approach based on a single-valued performance indicator to monitor the global behavior of bearings as critical components in a viaduct. The procedure for data analysis is exploiting the well-known Gaussian Processes to analyze and correlate horizontal bearing displacements and environmental temperature, as primary source of deformation of the deck. With this approach, we combine measurements from twelve sensors to design a robust performance indicator that is only weakly affected by temperature variations. Data exploitation and manipulation is described, from data acquisition and selection to the interpretation of results. Meanwhile the availability of a huge amount of information coming from the monitoring of big structures is no more an issue, the management of such indications is not always clear and efficient. For this reason, the method proposed by this paper can be of support in dealing with real-time monitoring of bridge bearings, maximizing unexpected maintenance and increasing the safety of the bridge.","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115366540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AERODYNAMIC SHAPE OPTIMIZATION OF THE MEXICO WIND TURBINE BLADE USING THE CONTINUOUS ADJOINT METHOD","authors":"E. Papoutsis‐Kiachagias, Mohammaderfan Farhikhteh, T. Skamagkis, K. Giannakoglou","doi":"10.7712/140121.7949.18374","DOIUrl":"https://doi.org/10.7712/140121.7949.18374","url":null,"abstract":". This paper presents the aerodynamic shape optimization of the MEXICO wind turbine (WT) blade, targeting the maximization of the axial moment and, hence, of the produced power. The optimization is conducted using the OpenFOAM-based continuous adjoint solver named adjointOptimisationF oam , developed and made publicly available by the group of authors. This implements and solves the adjoint to the Navier-Stokes system of equations, coupled with the differentiation of the Spalart-Allmaras turbulence model. Herein, this was extended to include the adjoint to the flow equations which are solved for the absolute velocity in the relative reference frame. Challenges in the convergence of the adjoint equations, mostly attributed to flow unsteadiness causing marginal convergence of the steady flow solver, are treated by additionally implementing the Recursive Projection Method (RPM). Assessment of the adjoint sensitivities with finite differences in a similar 2D case is also included. Then, the flow solution for the MEXICO WT case is compared with the outcome of another CFD solvers and experimental data, prior to the application of the expanded optimization software to maximize the axial moment of the WT. The blade and the displacement of the surrounding grid nodes are parameterized using a volumetric B-Splines morphing box. The optimization designed a blade bended in the axial direction axial moment, having a higher by 10.8%.","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128292758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A NEW MODIFIED JAYA ALGORITHM FOR OPTIMUM DESIGN OF TUNED MASS DAMPERS","authors":"S. M. Nigdeli, G. Bekdaş","doi":"10.7712/140121.7948.18388","DOIUrl":"https://doi.org/10.7712/140121.7948.18388","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126249055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SOLVING PESSIMISTIC BILEVEL OPTIMISATION PROBLEMS WITH EVOLUTIONARY ALGORITHMS","authors":"M. Antoniou, G. Papa","doi":"10.7712/140121.7962.18327","DOIUrl":"https://doi.org/10.7712/140121.7962.18327","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125175369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AN OPTIMIZATION ALGORITHM FOR THE DETECTION OF DAMAGE IN FRAME STRUCTURES","authors":"A. Greco, I. Fiore, A. Pluchino","doi":"10.7712/140121.7953.18424","DOIUrl":"https://doi.org/10.7712/140121.7953.18424","url":null,"abstract":"The aim of the study is the formulation of a computational method for the identification of the first damage in planar frames. The damage is considered to be concentrated in some oppor-tune sections of beams and columns and many assume different intensities. In order to identify the location and intensity of the damage when measured frequencies on the damaged frame are available, an original algorithm has been implemented assigning to each critical section an appropriate fitness function. This function indicates the difference be-tween the measured frequencies of vibration and those obtained, by means of opportune numerical models, assuming that the damage is located in the considered critical section. The exact location will then be individuated seeking the optimal fitness function. An iterative procedure which allows reducing the computational effort is also presented with reference to a case study.","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DESIGN OF REINFORCED CONCRETE ISOLATED FOOTINGS UNDER AXIAL LOADING WITH ARTIFICIAL NEURAL NETWORKS","authors":"G. Solorzano, V. Plevris","doi":"10.7712/140121.7955.18448","DOIUrl":"https://doi.org/10.7712/140121.7955.18448","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"39 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134260237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COMPUTATIONAL DESIGN OF COMPARATIVE MODELS AND GEOMETRICALLY CONSTRAINED OPTIMIZATION OF A MULTI DOMAIN VARIABLE SECTION BEAM BASED ON TIMOSHENKO MODEL","authors":"L. Sardone, M. Rosso, R. Cucuzza, R. Greco, G. Marano","doi":"10.7712/140121.7961.18535","DOIUrl":"https://doi.org/10.7712/140121.7961.18535","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132036289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"THE EFFECT OF THE ASSUMED INHERENT DAMPING IN THE TUNING OF TUNED MASS DAMPERS","authors":"Ayla Ocak, G. Bekdaş, S. M. Nigdeli","doi":"10.7712/140121.7947.18387","DOIUrl":"https://doi.org/10.7712/140121.7947.18387","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126879307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SOFTWARE PACKAGE FOR THE NUMERICAL SOLUTION OF NONLOCAL OPTIMIZATION PROBLEMS","authors":"P. Sorokovikov, A. Gornov","doi":"10.7712/140121.7965.18340","DOIUrl":"https://doi.org/10.7712/140121.7965.18340","url":null,"abstract":"","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115410974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASSESSMENT OF MULTI-OBJECTIVE AND COEVOLUTIONARY GENETIC PROGRAMMING FOR PREDICTING THE STOKES FLOW AROUND A SPHERE","authors":"Heiner Zille, F. Evrard, Julia Reuter, Sanaz Mostaghim, B. van Wachem","doi":"10.7712/140121.7959.18341","DOIUrl":"https://doi.org/10.7712/140121.7959.18341","url":null,"abstract":"Genetic Programming (GP) has been used in a variety of fields to learn the relationships between physical measurements of real-world problems. In this article, we combine different techniques from the area of evolutionary optimization and, particularly, GP to solve a fluid-dynamics problem: the Stokes flow around a rigid sphere. This serves as the starting point to explore the potential of applying different GP techniques to such complex physical problems. From the definition of the considered fluid-dynamics problem, six benchmark instances with different lengths and complexities are derived. We use singleand multi-objective GP methods and compare their performance using different objective functions. More precisely, we study how model complexity, correlation and the consistency with physical laws (i.e. physical units of measurement) can be included as different objective functions, and whether their inclusion is beneficial to the overall search process. In addition, we include the concept of Cooperative Coevolution, which maintains multiple independent populations of solutions, into our GP implementations and explore the capabilities and limitations of such coevolution-based optimization. We further propose a novel multi-phase approach, which alternates in the GP process between phases of traditional optimization and a mutation-only phase to reduce the model complexity. The results indicate that using multi-objective optimization is beneficial to the search process and can help finding numerically correct solutions to the problems, especially when including a transformed Spearman correlation as an additional optimization goal. Furthermore, the inclusion of the physical units of measurement also helps guide the GP toward numerically correct and physically meaningful equations. While the concept of coevolution did not lead to a superior performance in all cases, the precomputation of additional features, and the resulting reduction of the function set of the GP, leads to a drastic increase in performance and enables the algorithms to solve even the most complex of our benchmark instances. In the future, we aim to extend this research to more complex flows with multiple spheres and at higher Reynolds numbers, which involve a large number of input features.","PeriodicalId":309238,"journal":{"name":"14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124373779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}