Author
Yiannis Tsompanakis
Bio: Yiannis Tsompanakis is an academic researcher from Technical University of Crete. The author has contributed to research in topics: Seismic analysis & Seismic loading. The author has an hindex of 14, co-authored 68 publications receiving 643 citations.
Papers published on a yearly basis
Papers
More filters
Book•
01 Jan 2008
TL;DR: In this paper, the authors proposed a robust design optimization (RDO) approach to the design of trusses with randomness using semidefinite programming (SDP) and the saddlepoint expansion.
Abstract: Part A. Robust design optimization (RDO) A1. Basic aspects on RDO *1: Evaluation and Maximization of Robustness of Trusses by using Semidefinite Programming Yoshihiro Kanno and Izuru Takewaki. *2: A Taylor expansion approach to the design optimization of structures with randomness Ioannis Doltsinis, Zhan Kang. A2. Theoretical advances on RDO *3: Cost-Benefit Optimization and Risk Acceptability for Maintained Structures R. Rackwitz and A. Joanni. *4: Efficient robust-design optimization involving dynamic reliability problems Alexandros A. Taflanidis and James L. Beck. *5: Robust design optimization using possibility theory Byeng Dong Youn. *6: Bridging the gap between robust and reliability-based design optimization with the saddlepoint expansion Jorge E. Hurtado. A3. Application driven chapters on RDO *7: Info-gap robust design of passively controlled structures with load and model uncertainties Izuru Takewaki and Yakov Ben-Haim. *8: Efficient computing techniques for structural reliability-based robust design optimization Nikos D. Lagaros, Vaggelis Plevris, and Yiannis Tsompanakis. Part B. Reliability-based design optimization (RBDO) B1. Basic aspects on RBDO *9: Reliability-based structural optimization Alaa Chateauneuf. *10: Efficient approaches for system reliability-based design optimization Zissimos P. Mourelatos, Jinghong Liang and Efstratios Nikolaidis. B2. Theoretical advancements and academicapplications of RBDO *11: Numerical and semi-numerical methods for reliability-based design optimization G. Kharmanda. *12: Non-probabilistic design optimization with insufficient data using possibility and evidence theories Zissimos P. Mourelatos and Jun Zhou. *13: Efficient stochastic methods in RBDO Alaa Chateauneuf. *14: Reliability analysis and reliability based design optimization using the moment method Byung Man Kwak, Sang Hoon Lee and Jae Sung Huh. *15: Analytical target cascading in optimal design of decomposed systems under uncertainty M. Kokkolaras and P.Y. Papalambros. *16: Reliability based topology optimization using the hybrid cellular automaton method Neal M. Patel, John E. Renaud, Harish Agarwal and Andres Tovar. *17: Sample average approximations in Reliability-based structural optimization: Theory and applications J.O. Royset, E. Polak. B3. Application-driven chapters on RBDO *18: Design optimization of stochastic dynamic systems by algebraic reduced order models G. Weickum, M. Allen, K. Maute and D. Frangopol. *19: Reliability-based damage tolerance methodology Y-T. Wu. 20: Overview of reliability analysis and design capabilities in DAKOTA with Application to Shape Optimization of MEMS *M.S. Eldred, S.A. Mitchell, B. J. Bichon and B. M. Adams.
93 citations
TL;DR: In this paper, two types of ANN are implemented into a Monte Carlo simulation-based vulnerability analysis framework of geostructures, where the randomness of material properties, geometry and of the pseudostatically imposed seismic loading is considered.
68 citations
TL;DR: In this paper, the authors focus on the stability of tailings dams and propose a method to detect tailings dam failures using the invariances of the dams' dams' generators.
Abstract: The stability of tailings dams has drawn much attention over the past few decades as a significant number of tailings dam failures have been recorded worldwide. The present study focuses on the inv...
51 citations
TL;DR: In this paper, the authors evaluate seismic design procedures for three-dimensional (3D) frame structures using structural optimization methodologies, where procedures based on both linear and nonlinear time-history analysis are adopted.
48 citations
TL;DR: In this paper, a structural health monitoring approach that integrates both electromechanical admittance (EMA) and guided wave (GW) techniques is presented, which is used for local damage identification, by employing a piezoelectric transducer (PZT) as admittance sensor.
Abstract: In this study, a structural health monitoring approach that integrates both electromechanical admittance (EMA) and guided wave (GW) techniques is presented. More specifically, the EMA technique is used for local damage identification, by employing a piezoelectric transducer (PZT) as admittance sensor. Simultaneously, the same admittance sensor is disturbed by selected elastic GWs launched by another PZT to monitor the damages located beyond the sensing area of the admittance sensor. The validation of the integrated approach is achieved by identifying the changes in electrical admittance signatures as measured on the surface electrodes of PZTs. These changes occur when damage alters the mechanical impedance of the examined concrete structure and when propagating GWs encounter structural damage. Finite element models of damages occurring in conventional unreinforced, steel-reinforced or fiber reinforced plastics-reinforced concrete specimens are investigated. Results illustrate that the proposed integrated ...
45 citations
Cited by
More filters
TL;DR: The main focus will be on the different approaches to perform robust optimization in practice including the methods of mathematical programming, deterministic nonlinear optimization, and direct search methods such as stochastic approximation and evolutionary computation.
1,435 citations
TL;DR: In this article, the authors present a brief survey on some of the most relevant developments in the field of optimization under uncertainty, including reliability-based optimization, robust design optimization and model updating.
487 citations
TL;DR: The aim of the present paper is to develop a strategy for solving reliability-based design optimization (RBDO) problems that remains applicable when the performance models are expensive to evaluate.
Abstract: The aim of the present paper is to develop a strategy for solving reliability-based design optimization (RBDO) problems that remains applicable when the performance models are expensive to evaluate. Starting with the premise that simulation-based approaches are not affordable for such problems, and that the most-probable-failure-point-based approaches do not permit to quantify the error on the estimation of the failure probability, an approach based on both metamodels and advanced simulation techniques is explored. The kriging metamodeling technique is chosen in order to surrogate the performance functions because it allows one to genuinely quantify the surrogate error. The surrogate error onto the limit-state surfaces is propagated to the failure probabilities estimates in order to provide an empirical error measure. This error is then sequentially reduced by means of a population-based adaptive refinement technique until the kriging surrogates are accurate enough for reliability analysis. This original refinement strategy makes it possible to add several observations in the design of experiments at the same time. Reliability and reliability sensitivity analyses are performed by means of the subset simulation technique for the sake of numerical efficiency. The adaptive surrogate-based strategy for reliability estimation is finally involved into a classical gradient-based optimization algorithm in order to solve the RBDO problem. The kriging surrogates are built in a so-called augmented reliability space thus making them reusable from one nested RBDO iteration to the other. The strategy is compared to other approaches available in the literature on three academic examples in the field of structural mechanics.
354 citations
TL;DR: In this article, the authors deal with the dynamic response of road pavements to moving loads on their surface, where the loads are concentrated or distributed of finite extent, may vary with time and move with constant or variable speed.
190 citations
TL;DR: The state-of-the-art review indicates to what extent ML has been applied in four topic areas of earthquake engineering, including seismic hazard analysis, system identification and damage detection, seismic fragility assessment, and structural control for earthquake mitigation.
Abstract: Machine learning (ML) has evolved rapidly over recent years with the promise to substantially alter and enhance the role of data science in a variety of disciplines. Compared with traditional appro...
185 citations