G. Papazafeiropoulos, V. Plevris and M. Papadrakakis, "A new energy-based structural design optimization concept under seismic actions", Frontiers in Built Environment: Earthquake Engineering, 2017.

Abstract:
A new optimization concept is introduced which involves the optimization of nonlinear planar shear buildings by using gradients based on equivalent linear structures, instead of the traditional practice of calculating the gradients from the nonlinear objective function. The optimization problem is formulated as an equivalent linear system of equations in which a target fundamental eigenfrequency and equal dissipated energy distribution within the storeys of the building are the components of the objective function. The concept is applied in a modified Newton-Raphson algorithm in order to find the optimum stiffness distribution of two representative linear or nonlinear MDOF shear buildings, so that the distribution of viscously damped and hysteretically dissipated energy respectively over the structural height is uniform. A number of optimization results are presented in which the effect of the earthquake excitation, the critical modal damping ratio and the normalized yield interstorey drift limit on the optimum stiffness distributions is studied. Structural design based on the proposed approach is more rational and technically feasible compared to other optimization strategies (e.g. uniform ductility concept), whereas it is expected to provide increased protection against global collapse and loss of life during strong earthquake events. Finally, it is proven that the new optimization concept not only reduces running times by as much as 91% compared to the classical optimization algorithms, but also it can be applied in other optimization algorithms which use gradient information to proceed to the optimum point.

Keywords:
optimization; nonlinear; Newton-Raphson; Shear building; stiffness distribution; energy dissipation

P.G. Asteris, K. Kolovos, A. Athanasopoulou, V. Plevris and G. Konstantakatos, "Investigation of the mechanical behaviour of metakaolin-based sandcrete mixtures", European Journal of Environmental and Civil Engineering, 23(3), pp. 300-324, 2019.

Abstract:
This paper investigates the mechanical properties of sandcrete mixes with metakaolin (MK) as a mineral additive. Three different types of binders were prepared: one used as reference, based on 100% w/w ordinary Portland cement (PC), and two modified, where MK replaced PC in percentages 10% or 20% by weight of the reference cement content. Experimental tests have been carried out in order to obtain the full stress–strain diagram for the material under uniaxial compressive loading. The results of the tests have been post-processed numerically in order to obtain various mechanical characteristics of the sandcrete material, such as compressive strength, modulus of elasticity and strain at maximum strength. It has been found that, in general, specimens with metakaolin in the binder exhibit enhanced compressive strength compared to the reference samples without metakaolin. The improvement in compressive strength was more pronounced in samples with higher concentration of binder (50% w/w) and low or medium water per binder (W/B) ratio. Samples with higher compressive strength were characterised by higher values for the measured ultrasonic pulse velocity. The strain values, recorded at maximum strength, are considerably higher than the strain value of 2‰ for concrete under uniaxial compressive load.

Keywords:
sandcrete; mineral additives; metakaolin; mechanical properties; ultrasonic pulse velocity

G. Papazafeiropoulos, V. Plevris and M. Papadrakakis, "A generalized algorithm framework for non-linear structural dynamics", Bulletin of Earthquake Engineering, 15(1), pp. 411-441, 2017.

Abstract:
The performance of a family of nonlinear generalized single step-single solve (GSSSS) time integration schemes is assessed by comparison of their results in terms of total energy and the agreement with respective results published in the literature. The nonlinear algorithms have been developed by their linear counterparts using a Newton–Raphson iterative procedure to ensure dynamic equilibrium inside each time step. A literature review of the available time integration schemes used for nonlinear problems and the family of linear GSSSS algorithms are presented along with several commonly used time integration algorithms as special cases. Afterwards, the nonlinear schemes are formulated, and outlined in an explicit flowchart, which describes the nonlinear integration procedure in detail. The nonlinear family of algorithms is applied to six benchmark problems involving the dynamic response of SDOF systems with various stiffness and damping properties, as well as to a 3dof structure representing finite element systems containing rigid connections, penalty factors and other such types of constraints. It is shown that the schemes with Continuous Acceleration formulation (such as the HHT-a method) perform in general better than the others, even with a large time step, which leads to reduced computational effort for the estimation of the nonlinear dynamic response with relatively little loss of accuracy.

Keywords:
Time integration scheme; Newton–Raphson; Single step; Single solve; Energy conservation

P.G. Asteris and V. Plevris, "Anisotropic masonry failure criterion using artificial neural networks", Neural Computing and Applications, pp. 1-23, 2016.

Abstract:
In the last decades, a plethora of advanced computational models and techniques have been proposed on the modeling, assessment and design of masonry structures. The successful application of such sophisticated models necessitates the development of reliable analytical models capable of describing the failure of masonry materials. Nevertheless, there is a lack of analytical models due to the anisotropic and brittle nature exhibited by the masonry materials. In the present paper, the use of neural networks (NNs) is proposed to approximate the failure surface of masonry materials in dimensionless form. The comparison of the derived results with experimental findings as well as analytical results demonstrates the promising potential of using NNs for the reliable and robust approximation of the masonry failure surface under biaxial stress.

Keywords:
Anisotropic behavior; Biaxial stress state; Brittle material; Failure criterion; Failure surface; Masonry; Neural network; NN

P.G. Asteris, M.P. Chronopoulos, C.Z. Chrysostomou, H. Varum, V. Plevris, N. Kyriakides and V. Silva, "Seismic Vulnerability Assessment of Historical Masonry Structural Systems", Engineering Structures, 62-63, pp. 118-134, 2014.

Abstract:
Masonry structures are complex systems that require a thorough and detailed knowledge and information regarding their behavior under seismic loading. Appropriate modeling of a masonry structure is a prerequisite for a reliable earthquake resistant design or assessment. However, modeling a real structure to a robust quantitative (mathematical) representation is a very difficult, complex and computationally demanding task. This paper presents a methodology for earthquake resistant design or assessment of masonry structural systems. The entire process is illustrated using case studies from historical masonry structures in the European area. In particular, the applicability of the proposed method is checked via analyses of existing masonry buildings in three countries, namely Greece, Portugal and Cyprus, with different seismicity levels, influencing the risk impacting the masonry structures. Useful conclusions are drawn regarding the effectiveness of the intervention techniques used for the reduction of the vulnerability of the case-study structures, through the comparison of the results obtained.

Keywords:
Historical structures; Fragility curves; Masonry; Retrofitting; Structural assessment; Structural modeling

V. Plevris and P. Asteris, "Modeling of Masonry Failure Surface under Biaxial Compressive Stress Using Neural Networks", Construction and Building Materials, 55, pp. 447-461, 2014.

Abstract:
Masonry is a brittle anisotropic material that exhibits distinct directional properties because the mortar joints act as planes of weakness. To define failure under biaxial stress, a 3D surface in terms of the two principal stresses and their orientation to the bed joints, is required. In the present study, a novel method is proposed on applying Neural Networks (NNs) to approximate the failure surface for such brittle anisotropic materials. The method comprises a series of NNs that are trained with available experimental data. The results demonstrate the great potential of using NNs for the approximation of masonry failure surface under biaxial compressive stress.

Keywords:
Masonry; Anisotropy; Failure criterion; Failure surface; Biaxial stress; Neural Network; NN; Approximation.

Y. Javadi, V. Plevris and M.A. Najafabadi, "Using L_CR Ultrasonic Method to Evaluate Residual Stressin Dissimilar Welded Pipes", International Journal of Innovation, Management and Technology, 4(1), pp. 170-174, 2013.

Abstract:
The ultrasonic residual stresses measurement is based on the acoustoelastic effect that refers to the change in velocity of the elastic waves when propagating in a stressed media. The experimental method using the longitudinal critically refracted (L_CR) waves requires an acoustoelastic calibration and an accuracy measurement of the time-of-flight on both stressed and unstressed media. This paper evaluates welding residual stresses in dissimilar pipe-pipe joint of AISI stainless steel 304 and Carbon Steel A106-B type. The residual stresses in inner and outer surface of pipes were evaluated by L_CR ultrasonic waves by using 1Mhz, 2Mhz, 4Mhz and 5Mhz transducers. It has been shown that the difference in residual stresses between inner and outer surfaces of pipes and also between Stainless steel and Carbon Steel side can be inspected by L_CR waves.

Keywords:
Ultrasonic stress Measurement; acoustoelastic effect; welding residual stress; L_CR; dissimilar welded joint.

V. Plevris and M. Papadrakakis, "A Hybrid Particle Swarm – Gradient Algorithm for Global Structural Optimization", Computer-Aided Civil and Infrastructure Engineering, 26(1), 48-68, 2011.

Abstract:
The particle swarm optimization (PSO) method is an instance of a successful application of the philosophy of bounded rationality and decentralized decision making for solving global optimization problems. A number of advantages with respect to other evolutionary algorithms are attributed to PSO making it a prospective candidate for optimum structural design. The PSO-based algorithm is robust and well suited to handle nonlinear, nonconvex design spaces with discontinuities, exhibiting fast convergence characteristics. Furthermore, hybrid algorithms can exploit the advantages of the PSO and gradient methods. This article presents in detail the basic concepts and implementation of an enhanced PSO algorithm combined with a gradient-based quasi-Newton sequential quadratic programming (SQP) method for handling structural optimization problems. The proposed PSO is shown to explore the design space thoroughly and to detect the neighborhood of the global optimum. Then the mathematical optimizer, starting from the best estimate of the PSO and using gradient information, accelerates convergence toward the global optimum. A nonlinear weight update rule for PSO and a simple, yet effective, constraint handling technique for structural optimization are also proposed. The performance, the functionality, and the effect of different setting parameters are studied. The effectiveness of the approach is illustrated in some benchmark structural optimization problems. The numerical results confirm the ability of the proposed methodology to find better optimal solutions for structural optimization problems than other optimization algorithms.

Keywords:
Particle swarm; swarm intelligence; structural optimization; hybrid methods.

N.D. Lagaros, V. Plevris and M. Papadrakakis, "Neurocomputing Strategies for Solving Reliability-Robust Design Optimization Problems", Engineering Computations, 27(7), pp. 819-840, 2010.

Purpose – This paper, by taking randomness and uncertainty of structural systems into account aims to implement a combined reliability-based robust design optimization (RRDO) formulation. The random variables to be considered include the cross section dimensions, modulus of elasticity, yield stress, and applied loading. The RRDO problem is to be formulated as a multi-objective optimization problem where the construction cost and the standard deviation of the structural response are the objectives to be minimized.

Design/methodology/approach – The solution of the optimization problem is performed with the non-dominant cascade evolutionary algorithm with the weighted Tchebycheff metric, while the probabilistic analysis required is carried out with the Monte Carlo simulation method. Despite the computational advances, the solution of a RRDO problem for real-world structures is extremely computationally demanding and for this reason neurocomputing estimations are implemented.

Findings – The obtained estimates with the neural network predictions are shown to be very satisfactory in terms of accuracy for performing this type of computation. Furthermore, the present numerical results manage to achieve a reduction in computational time up to four orders of magnitude, for low probabilities of violation, compared to the conventional procedure making thus feasible the reliability-robust design optimization of realistic structures under probabilistic constraints.

Originality/value – The novel parts of the present work include the implementation of neurocomputing strategies in RRDO problems for reducing the computational cost and the comparison of the results given by RRDO and robust design optimization formulations, where the significance of taking into account probabilistic constraints is emphasized.

Keywords:
Neural nets; Optimization techniques; Structural design; Structural engineering.

N.D. Lagaros, V. Plevris and M. Papadrakakis, "Reliability Based Robust Design Optimization of Steel Structures", International Journal for Simulation and Multidisciplinary Design Optimization, 1(1), pp. 19–29, 2007.

Abstract:
In this work the uncertainty of a structural system is taken into account in the framework of a structural Reliability based Robust Design Optimization (RRDO) formulation where probabilistic constraints are incorporated into the robust design optimization formulation. A robust design optimization problem is formulated as a multi-criteria optimization problem. The Pareto front representing the solution of the RRDO problem is composed by designs with a state of robustness, since their performance is the least sensitive to the variability of the uncertain variables. The cross section dimensions together with other structural parameters, such as the modulus of elasticity, the yield stress and the applied loading, are considered as random variables. For the solution of the RRDO problem, the non-dominant Cascade Evolutionary Algorithm is employed combined with a weighted Tchebycheff metric.

Keywords:
Probabilistic constraints; robust design optimization; cascade evolutionary algorithms; Monte Carlo simulation.

M. Papadrakakis, N.D. Lagaros and V. Plevris, "Design Optimization of Steel Structures Considering Uncertainties", Engineering Structures, 27(9), pp. 1408-1418, 2005.

Abstract:
In real world engineering applications the uncertainties of the structural parameters are inherent and the scatter from their nominal ideal values is in most cases unavoidable. These uncertainties play a dominant role in structural performance and the only way to assess this influence is to perform Reliability-Based Design Optimization (RBDO) and Robust Design Optimization (RDO). Compared to the basic deterministic-based optimization problem, a RBDO problem considers additional non-deterministic constraint functions, while the RDO yields a design with a state of robustness, so that its performance is the least sensitive to the variability of the uncertain parameters. The first part of this study examines the application of Neural Networks (NN) to the RBDO of large-scale structural systems, while the second part investigates the structural RDO problem. The use of NN in the framework of the RBDO problem is motivated by the approximate concepts inherent in reliability analysis and the time-consuming repeated analyses required by Monte Carlo Simulation. On the other hand the RDO is a multi-criteria optimization problem where the aim is to minimize both the weight of the structure and the variance of the structural response.

Keywords:
Structural optimization; Reliability analysis; Robust design; Evolution Strategies; Monte Carlo simulation; Neural Networks.

N.D. Lagaros, V. Plevris and M. Papadrakakis, "Multi-objective Design Optimization Using Cascade Evolutionary Computations", Computer Methods in Applied Mechanics and Engineering, 194(30-33), pp. 3496-3515, 2005.

Abstract:
The consideration of uncertainties in conjunction with the probability of violation of the constraints imposed by the design codes is examined in the framework of structural optimization. The optimum design achieved based on a deterministic formulation is compared, in terms of the optimum weight, the probability of violation of the constraints and the probability of failure, with the optimum designs achieved through a robust design formulation where the variance of the response is considered as an additional criterion. The stochastic finite element problem is solved using the Monte Carlo Simulation method, combined with the Latin Hypercube Sampling technique for improving its computational efficiency. A non-dominant cascade evolutionary algorithm-based methodology is adopted for the solution of the multi-objective optimization problem encountered, in order to obtain the global Pareto front curve.

Keywords:
Multi-objective optimization; Latin hypercube; Robust design optimization; Cascade evolutionary algorithms.

M. Papadrakakis, N.D. Lagaros and V. Plevris, "Structural Optimization Considering the Probabilistic System Response", Theoretical and Applied Mechanics, 31(3-4), pp. 361-394, 2004.

Abstract:
In engineering problems, the randomness and uncertainties are inherent and the scatter of structural parameters from their nominal ideal values is unavoidable. In Reliability Based Design Optimization (RBDO) and Robust Design Optimization (RDO) the uncertainties play a dominant role in the formulation of the structural optimization problem. In an RBDO problem additional non deterministic constraint functions are considered while an RDO formulation leads to designs with a state of robustness, so that their performance is the least sensitive to the variability of the uncertain variables. In the first part of this study a metamodel assisted RBDO methodology is examined for large scale structural systems. In the second part an RDO structural problem is considered. The task of robust design optimization of structures is formulated as a multi-criteria optimization problem, in which the design variables of the optimization problem, together with other design parameters such as the modulus of elasticity and the yield stress are considered as random variables with a mean value equal to their nominal value.

Keywords:
Structural optimization; reliability analysis; robust design; Evolution Strategies; Monte Carlo simulation; Neural Networks.

M. Papadrakakis, N.D. Lagaros and V. Plevris, "Multi-objective Optimization of Skeletal Structures under Static and Seismic Loading Conditions", Engineering Optimization, 34(6), pp. 645-669, 2002.

Abstract:
Almost every real world problem involves simultaneous optimization of several incommensurable and often competing objectives which constitutes a multi-objective optimization problem. In multi-objective optimization problems the optimal solution is not unique as in single-objective optimization problems. This paper is concerned with large-scale structural optimization of skeletal structures such as space frames and trusses, under static and/or seismic loading conditions with multiple objectives. Combinatorial optimization methods and in particular algorithms based on evolution strategies are implemented for the solution of this type of problems. In treating seismic loading conditions a number of accelerograms are produced from the elastic design response spectrum of the region. These accelerograms constitute the multiple loading conditions under which the structures are optimally designed. This approach for treating seismic loading is compared with an approximate design approach, based on simplifications adopted by the seismic codes, in the framework of multi-objective optimization.

Keywords:
Multi-objective Structural Optimization; Evolution Strategies; Seismic Loading.

M. Papadrakakis, N.D. Lagaros, Y. Tsompanakis and V. Plevris, "Large Scale Structural Optimization: Computational Methods and Optimization Algorithms", Archives of Computational Methods in Engineering (State of the art reviews), 8(3), pp. 239-301, 2001.

Abstract:
The objective of this paper is to investigate the efficiency of various optimization methods based on mathematical programming and evolutionary algorithms for solving structural optimization problems under static and seismic loading conditions. Particular emphasis is given on modified versions of the basic evolutionary algorithms aiming at improving the performance of the optimization procedure. Modified versions of both genetic algorithms and evolution strategies combined with mathematical programming methods to form hybrid methodologies are also tested and compared and proved particularly promising. Furthermore, the structural analysis phase is replaced by a neural network prediction for the computation of the necessary data required by the evolutionary algorithms. Advanced domain decomposition techniques particularly tailored for parallel solution of large-scale sensitivity analysis problems are also implemented. The efficiency of a rigorous approach for treating seismic loading is investigated and compared with a simplified dynamic analysis adopted by seismic codes in the framework of finding the optimum design of structures with minimum weight. In this context a number of accelerograms are produced from the elastic design response spectrum of the region. These accelerograms constitute the multiple loading conditions under which the structures are optimally designed. The numerical tests presented demonstrate the computational advantages of the discussed methods, which become more pronounced in large-scale optimization problems.

M. Papadrakakis, N.D. Lagaros and V. Plevris, "Optimum Design of Space Frames under Seismic Loading", International Journal of Structural Stability and Dynamics, 1(1), pp. 105-123, 2001.

Abstract:
The objective of this paper is to perform structural optimization under seismic loading. Combinatorial optimization methods and in particular algorithms based on Evolution Strategies are implemented for the solution of large-scale structural optimization problems under seismic loading. In this work the efficiency of a rigorous approach in treating dynamic loading is investigated and compared with a simplified dynamic analysis in the framework of finding the optimum design of structures with minimum weight. In this context a number of accelerograms are produced from the elastic design response spectrum of the region. These accelerograms constitute the multiple loading conditions under which the structures are optimally designed. This approach is compared with an approximate design approach based on simplifications adopted by the seismic codes. The results obtained for a characteristic test problem indicate a substantial improvement in the final design when the proposed optimization procedure is implemented.

Keywords:
Structural optimization; evolution strategies; seismic loading.

V. Plevris, Postgraduate Thesis "Multi-objective Optimum Design of Structures with use of Evolution Strategies", Institute of Structural Analysis and Seismic Research, School of Civil Engineering, National Technical University of Athens (NTUA), 2001.

Abstract
The Postgraduate Thesis deals with the problem of Multi-Objective optimum design of structures with use of Evolution Strategies (ES). It consists of 6 chapters, the first five dealing with the theoretical background; Optimum design of structures in general, Multi-Objective optimization, the Evolution Strategies method, dynamics of structures and the Direct Time Integration method. The sixth chapter deals with the practical part, the application of the methods and the corresponding results.
The structure that is examined is a six-storey steel space frame. The applied optimization method is a multi-membered ES scheme (M-ES). The objective in every case is finding the Pareto optimal solution of the multi-objective optimization problem, which in the special case of two objective functions can be represented in a diagram as a curve. The design variables of the optimization problem concern the geometry of the cross sections of the columns and beams and specifically the height and width of the W-shape cross sections. The two objective functions are the weight and the maximum horizontal displacement of the structure. The constraints concern the allowable stresses of the members and the maximum allowable inter-storey drift. The applied ES scheme is a scheme of 5 parents and 5 offsprings (5+5 ES). The dynamic analyses are performed with the Direct Time Integration method, using three artificial accelerogramms compatible with the response spectrum of the Greek seismic code EAK 2000. The loads applied are both static and static + dynamic. The examined Multi-Objective Optimization methods are the Linear Weighting Method, the Constraints Method and the Distance Method.

Plevris, V. and G. Papazafeiropoulos, "Design of RC Sections with Single Reinforcement According to EC2-1-1 and the Rectangular Stress Distribution", in Computational Methods in Earthquake Engineering, Vol. 3, M. Papadrakakis, V. Plevris and N.D. Lagaros (Eds.), Springer International Publishing, pp. 205-259, 2016.

Abstract:
Nowadays, the design of concrete structures in Europe is governed by the application of Eurocode 2 (EC2). In particular, EC2—Part 1-1 deals with the general rules and the rules for concrete buildings. An important aspect of the design is specifying the necessary tensile (and compressive, if needed) steel reinforcement required for a Reinforced Concrete (RC) section. In this study we take into account the equivalent rectangular stress distribution for concrete and the bilinear stress-strain relation with a horizontal top branch for steel. This chapter presents three detailed methodologies for the design of rectangular cross sections with tensile reinforcement, covering all concrete classes, from C12/15 up to C90/105. The purpose of the design is to calculate the necessary tensile steel reinforcement. The first methodology provides analytic formulas and an algorithmic procedure that can be easily implemented in any programming language. The second methodology is based on design tables that are provided in Appendix A, requiring less calculations. The third methodology provides again analytic formulas that can replace the use of tables and even be used to reproduce the design tables. Apart from the direct problem, the inverse problem is also addressed, where the steel reinforcement is given and the purpose is to find the maximum bending moment that the section can withstand, given also the value and position of the axial force. For each case analytic relations are extracted in detail with a step-by-step procedure, the relevant assumptions are highlighted and results for four different cross section design examples are presented.

Book: "Computational Methods in Earthquake Engineering: Volume 3", Eds: M. Papadrakakis, V. Plevris, N.D. Lagaros, Springer International Publishing, 2016.

Description

This is the third book in a series on Computational Methods in Earthquake Engineering. The purpose of this volume is to bring together the scientific communities of Computational Mechanics and Structural Dynamics, offering a wide coverage of timely issues on contemporary Earthquake Engineering.

This volume will facilitate the exchange of ideas in topics of mutual interest and can serve as a platform for establishing links between research groups with complementary activities. The computational aspects are emphasized in order to address difficult engineering problems of great social and economic importance.

V. Plevris, Doctoral Dissertation (PhD) "Innovative Computational Techniques for the Optimum Structural Design Considering Uncertainties", Institute of Structural Analysis and Seismic Research, School of Civil Engineering, National Technical University of Athens (NTUA), 2009.

Abstract

Uncertainties in structural mechanics, and in particular in the phase of analysis and design, can play an extremely important role, affecting not only the safety and reliability of structures and their mechanical components, but also the quality of their performance. The response of a structural system may be very sensitive to uncertainties in the material properties, manufacturing conditions, external loading and analytical or numerical modeling. In order to account for these issues, stochastic analysis methods have been developed over the last decades. The optimum result obtained by a deterministic optimization formulation that ignores scatter of any kind of the parameters affecting its response has limited value and reliability, as it can be severely affected by the uncertainties that are inherent in the model. The deterministic optimum can be associated with unaccepted probabilities of failure, or it can be vulnerable to slight variations of some uncertain parameters. The development of probabilistic analysis methods over the last two decades has stimulated the interest for considering also randomness and uncertainty in the formulation of structural design optimization problems. In order to account for uncertainties in a structural optimization framework, probabilistic-based formulations of the optimization problem have to be used, utilizing stochastic simulation and probabilistic analysis.

The goal of the thesis is to unify the concepts of probability-based safety analysis and structural optimization and provide the necessary numerical tools to deal with optimization problems considering uncertainties. This goal is addressed by developing algorithms for solving the probabilistic structural optimization problems encountered. In order to deal with these problems efficiently, various algorithms and methodologies have to be used, such as efficient single- and multi-objective optimizers and efficient stochastic problems formulations for the stochastic analysis process. Despite the advances on these issues, the computational cost for considering the uncertainties in a structural design optimization problem remains extremely large, especially for real-world large-scale problems with many design and/or random variables. To alleviate the computational burden, the implementation of Neural Network (NN) metamodels is also proposed in this thesis for further reducing the computational cost, providing acceptable numerical results at an affordable computational time.

The dissertation consists of nine chapters in total, plus the bibliography and three ap-pendices. It is organized as follows: following the introduction of Chapter 1, Chapter 2 deals with the concept of uncertainty in structural engineering in general. Chapter 3 presents the formulation of single objective optimization problems, while Chapter 4 discusses the multi-objective optimization problem. The basics of Neural Networks and their implementation in structural engineering are presented in Chapter 5. Chapter 6 discusses the problem of structural optimization considering uncertainties, where the basic problems of this kind, namely the Reliability-Based Design Optimization (RBDO), the Robust Design Optimization (RDO) and the combination Reliability-based Robust Design Optimization (RRDO) problems are presented, among others.

The numerical applications of the dissertation are divided into two parts, A and B, pre-sented in Chapters 7 and 8, respectively. Part A (Chapter 7) contains the deterministic optimization test examples, where uncertainties are not taken into account. In Part B (Chapter 8), the probabilistic optimization test examples are discussed, where uncertainties play a significant role.

Chapter 9 contains the conclusions, the original contribution of the thesis, and direc-tions for future research. Finally, the bibliography is presented followed by three appendices: Appendix A, containing the notation and symbols used in the dissertation; Appendix B with the acronyms and abbreviations used; and Appendix C with a listing of publications by the author.

Β. Πλεύρης, Μεταπτυχιακή Εργασία "Τα Μικροοικονομικά Θεμέλια της Ανταγωνιστικότητας και της Ευημερίας", Εργαστήριο Στρατηγικής και Επιχειρηματικότητας του Τμήματος Διοικητικής Επιστήμης και Τεχνολογίας του Οικονομικού Πανεπιστημίου Αθηνών (ΟΠΑ), 2003.

Περίληψη
Οι αλλαγές των τελευταίων ετών όπως εκφράζονται από την εντατικοποίηση του παγκόσμιου εμπορίου, την απελευθέρωση των διεθνών αγορών, τη δημιουργία ενιαίων ζωνών οικονομικής δραστηριότητας με κοινούς κανόνες και την παγκοσμιοποίηση, διαμόρφωσαν ένα νέο τοπίο ανταγωνισμού για τα κράτη και τις επιχειρήσεις τους. Μέσα σε ένα τέτοιο περιβάλλον, ο ανταγωνισμός είναι αμεσότερος, εντονότερος και δείχνει πλέον περισσότερο βασισμένος στις ικανότητες των επιχειρήσεων και στην ποιότητα του τοπικού ανταγωνισμού παρά στο μακροοικονομικό, πολιτικό, νομικό και κοινωνικό περιβάλλον και τους χειρισμούς των κυβερνήσεων, οι οποίες καλούνται να διαμορφώσουν τις αναγκαίες συνθήκες για την ανάπτυξη, που δεν είναι όμως πλέον καθ’ εαυτές και ικανές. Η εργασία αυτή αφορά ακριβώς στη διερεύνηση της επιρροής του μικροοικονομικού περιβάλλοντος στη διαμόρφωση της ανταγωνιστικότητας ενός έθνους και κατ’ επέκταση στη διαμόρφωση του επιπέδου ευημερίας των πολιτών του, με έμφαση στην Ελληνική πραγματικότητα. Τα αντικείμενα και οι υποθέσεις που θα διερευνηθούν παρουσιάζονται συνοπτικά παρακάτω:

Α. Σε παγκόσμια κλίμακα
Η ανταγωνιστικότητα ενός έθνους είναι πλέον περισσότερο βασισμένη στις ικανότητες των επιχειρήσεων που δρουν στη χώρα παρά στους μακροοικονομικούς χειρισμούς των κυβερνήσεων. Η ανταγωνιστικότητα και επάρκεια των επιχειρήσεων που δραστηριοποιούνται σε μία χώρα είναι εκείνη που οδηγεί το μακροοικονομικό περιβάλλον να προσαρμοστεί βελτιούμενο και όχι το αντίθετο.

Β. Ειδικά για την Ελλάδα
Η αιτία για την υστέρηση σε ανταγωνιστικότητα της χώρας σήμερα είναι η μη επάρκεια του μικροοικονομικού περιβάλλοντος ανάπτυξης των επιχειρήσεων και όχι η μη επάρκεια σε μακροοικονομικές κυβερνητικές πολιτικές και παρεμβάσεις.

Τελικός σκοπός είναι να διαφανεί ότι σε μεγάλο ποσοστό η αιτία για την υστέρηση σε ανταγωνιστικότητα κάποιων χωρών, συμπεριλαμβανομένης και της Ελλάδας, είναι η μη επάρκεια του μικροοικονομικού περιβάλλοντος ανάπτυξης των επιχειρήσεων και όχι η μη επάρκεια σε μακροοικονομικές κυβερνητικές πολιτικές και παρεμβάσεις.

Β. Πλεύρης, Διπλωματική εργασία "Βέλτιστος Σχεδιασμός Κατασκευών υπό Δυναμικές Φορτίσεις με Στρατηγικές Εξέλιξης", Εργαστήριο Στατικής και Αντισεισμικών Ερευνών, Τομέας Δομοστατικής, Σχολή Πολιτικών Μηχανικών, Εθνικό Μετσόβιο Πολυτεχνείο, 1999.

Περίληψη
Η διπλωματική εργασία πραγματεύεται το αντικείμενο του βέλτιστου σχεδιασμού των κατασκευών υπό στατικές και δυναμικές φορτίσεις με τη χρήση εξελικτικών μεθόδων και συγκεκριμένα των Στρατηγικών Εξέλιξης (ES). Αποτελείται από πέντε κεφάλαια συνολικά, εκ των οποίων τα τέσσερα πρώτα αναφέρονται στο θεωρητικό υπόβαθρο. Σε αυτά γίνεται λόγος για το αντικείμενο της βελτιστοποίησης γενικά, για τη μέθοδο των Στρατηγικών Εξέλιξης που εφαρμόστηκε, για τη δυναμική των κατασκευών καθώς και για δύο μεθόδους δυναμικής ανάλυσης, τη μέθοδο των ιδιομορφών και τη μέθοδο της άμεσης ολοκλήρωσης. Το πέμπτο κεφάλαιο καλύπτει το πρακτικό μέρος, με τις εφαρμογές που πραγματοποιήθηκαν και τα αποτελέσματα που προέκυψαν.
Ο φορέας που εξετάστηκε στα πλαίσια των εφαρμογών είναι ένα εξαώροφο χωρικό πλαίσιο από χάλυβα. Οι μεταβλητές σχεδιασμού του προβλήματος αφορούν τη γεωμετρία των διατομών υποστυλωμάτων και δοκών και συγκεκριμένα το ύψος και το πλάτος των διπλών Ταυ. Οι περιορισμοί που τίθενται αφορούν τις τάσεις των μελών και τις σχετικές μετατοπίσεις μεταξύ των ορόφων, ενώ σκοπός ήταν σε κάθε περίπτωση η εύρεση της βέλτιστης λύσεως του προβλήματος ελαχιστοποίησης του βάρους. Πραγματοποιήθηκαν αναλύσεις με στατικά και στατικά + δυναμικά φορτία. Οι δυναμικές αναλύσεις έγιναν σύμφωνα με τις απαιτήσεις του Αντισεισμικού Κανονισμού ΕΑΚ 2000, με δύο μεθόδους: Τη μέθοδο των ιδιομορφών με βάση το φάσμα σχεδιασμού και τη μέθοδο της Άμεσης Ολοκλήρωσης με χρήση 3 συνθετικών επιταχυνσιογραφημάτων σύμφωνων με το φάσμα του κανονισμού. Έγιναν διάφορες παραμετρικές διερευνήσεις, οι οποίες αποσκοπούσαν τόσο στη μελέτη και “αποκρυπτογράφηση” των εφαρμοζόμενων μεθόδων βελτιστοποίησης και της αποτελεσματικότητας των διαφόρων σχημάτων ES, όσο και στη σύγκριση των δύο μεθόδων δυναμικής ανάλυσης μεταξύ τους, όσον αφορά το αποτέλεσμα που δίνει η κάθε μία στο πρόβλημα της βελτιστοποίησης.

N.D. Lagaros, M. Papadrakakis and V. Plevris, "Multi-objective Optimization of Space Structures under Static and Seismic Loading Conditions", Chapter 12 in Evolutionary Multiobjective Optimization, A. Abraham, L. Jain and R. Goldberg (Eds.), Springer Verlag, CRC Press, 2005 (ISBN: 1-85233-787-7).

Abstract:
This chapter presents a evolution strategies approach for multiobjective design optimization of structural problems such as space frames and multi-layered space trusses under static and seismic loading conditions. A rigorous approach and a simplified one with respect to the loading condition are implemented for finding optimal design of a structure under multiple objectives.

N.D. Lagaros, Y. Tsompanakis, M. Fragiadakis, V. Plevris and M. Papadrakakis, "Metamodel-based Computational Techniques for Solving Structural Optimization Problems Considering Uncertainties", Chapter 21 in Structural Design Optimization Considering Uncertainties, Y. Tsompanakis, N.D. Lagaros and M. Papadrakakis (Eds.), Taylor and Francis, 2008 (ISBN: 978-0-415-45260-1).

Abstract:
Uncertainties are inherent in engineering problems due to various numerical modeling "imperfections" and due to the inevitable scattering of the design parameters from their nominal values. Under this perspective, there are two main optimal design formulations that account for the probabilistic response of structural systems: Reliability-based Design Optimization (RBDO) and Robust Design Optimization (RDO). In this work both type of problems are briefly addressed and realistic engineering applications are presented. The optimization part of the proposed probabilistic formulations is solved utilizing efficient evolutionary methods. In both types of problems the probabilistic analysis is carried out with the Monte Carlo Simulation (MCS) method incorporating the Latin Hypercube Sampling (LHS) technique for the reduction of the sample size. In order to achieve further improvement of the computational efficiency a Neural Network (NN) is used to replace the time-consuming FE analyses required by the MCS. Moreover, various sources of randomness that arise in structural systems are taken into account in a "holistic" probabilistic perception by implementing a Reliability-based Robust Design Optimization (RRDO) formulation, where additional probabilistic constraints are incorporated into the standard RDO formulation. The proposed RRDO problem is formulated as a multi-criteria optimization problem using the non-dominant Cascade Evolutionary Algorithm (CEA) combined with the weighted Tchebycheff metric.

Ch.Ch. Mitropoulou, V. Plevris and N.D. Lagaros, "Metaheuristic Optimization in Seismic Structural Design and Inspection Scheduling of Buildings", Chapter 7 in Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications, V. Plevris, Ch.Ch. Mitropoulou, N.D. Lagaros (Eds.), IGI Global, 2012 (ISBN: 978-1-4666-1640-0).

Abstract:
Optimization is a field where extensive research has been conducted over the last decades. Many types of problems have been addressed and many types of algorithms have been developed, while their range of applications is continuously growing. The chapter is divided into two parts; in the first part, the life-cycle cost analysis is used as an assessment tool for designs obtained by means of prescriptive and performance-based optimum design methodologies. The prescriptive designs are obtained through a single-objective formulation, where the initial construction cost is the objective to be minimized, while the performance-based designs are obtained through a two-objective formulation where the life-cycle cost is considered as an additional objective also to be minimized. In the second part of the chapter, the problem of inspection of structures and routing of the inspection crews following an earthquake in densely populated metropolitan areas is studied. A model is proposed and a decision support system is developed to aid local authorities in optimally assigning inspectors to critical infrastructures. A combined particle swarm – ant colony optimization based framework is implemented which proves to be an instance of a successful application of the philosophy of bounded rationality and decentralized decision-making for solving global optimization problems.

V. Plevris, M.G. Karlaftis, N.D. Lagaros, "A Swarm Intelligence Approach For Emergency Infrastructure Inspection Scheduling", Chapter 8 in Sustainable and Resilient Critical Infrastructure Systems: Simulation, Modeling, and Intelligent Engineering, K. Gopalakrishnan, S. Peeta (Eds.), Springer, 2010 (ISBN: 978-3-642-11404-5).

Abstract:
Natural hazards such as earthquakes, floods and tornadoes can cause extensive failure of critical infrastructures including bridges, water and sewer systems, gas and electricity supply systems, and hospital and communication systems. Following a natural hazard, the condition of structures and critical infrastructures must be assessed and damages have to be identified; inspections are therefore necessary since failure to rapidly inspect and subsequently repair infra-structure elements will delay search and rescue operations and relief efforts. The objective of this work is scheduling structure and infrastructure inspection crews following an earthquake in densely populated metropolitan areas. A model is proposed and a decision support system is designed to aid local authorities in optimally assigning inspectors to critical infrastructures. A combined Particle Swarm – Ant Colony Optimization based framework is developed which proves an instance of a successful application of the philosophy of bounded rationality and decentralized decision-making for solving global optimization problems.

Asteris, P. G., V. Sarhosis, A. Mohebkhah, V. Plevris, L. Papaloizou, P. Komodromos and J. V. Lemos, "Numerical Modeling of Historic Masonry Structures", in Handbook of Research on Seismic Assessment and Rehabilitation of Historic Structures, P. G. Asteris and V. Plevris (Eds.), IGI Global, pp. 213-256, 2015.

Abstract:
The majority of historical and heritage structures around the world consist of unreinforced masonry walls. A masonry structure is composed of masonry units, such as brick or marble blocks, with or without a joint filling material, such as mortar. A masonry with a joint material is usually made of two different materials (i.e. masonry units and mortar), representing a non-homogeneous and anisotropic structural component. In other words, masonry is a discontinuous structural component whose deformations and failure mechanism are governed by its blocky behavior. Some ancient masonry structures, such as ancient columns and colonnades, are constructed without any form of joint material between the individual blocks. Therefore, the isotropic elastic continuum-based models are not suitable for the simulation of the real nonlinear behavior of masonry walls under applied load.

Book: "Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications", Eds: V. Plevris, Ch. Ch. Mitropoulou, N.D. Lagaros, IGI Global, 2012.

Description

Throughout the past few years, there has been extensive research done on structural design in terms of optimization methods or problem formulation. But, much of this attention has been on the linear elastic structural behavior, under static loading condition. Such a focus has left researchers scratching their heads as it has led to vulnerable structural configurations. What researchers have left out of the equation is the element of seismic loading. It is essential for researchers to take this into account in order to develop earthquake resistant real-world structures.

Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications focuses on the research around earthquake engineering, in particular, the field of implementation of optimization algorithms in earthquake engineering problems. Topics discussed within this book include, but are not limited to, simulation issues for the accurate prediction of the seismic response of structures, design optimization procedures, soft computing applications, and other important advancements in seismic analysis and design where optimization algorithms can be implemented. Readers will discover that this book provides relevant theoretical frameworks in order to enhance their learning on earthquake engineering as it deals with the latest research findings and their practical implementations, as well as new formulations and solutions.

Reviews and Testimonials

"In this resource, civil engineers from around the world show how tools of optimum design developed for linear elastic structure behavior can be applied in designing earthquake- resistant structures. Their topics include discrete variable structural optimization of systems under stochastic earthquake excitation, assessing the damage in inelastic structures under simulated critical earthquakes, and overall conceptual seismic design and local seismic capacity design for bridges..."

– Book News Inc., Research Book News, 2012

Topics Covered

• Design optimization in earthquake engineering
• Life cycle cost structural analysis
• Optimal seismic performance-based design of structures
• Optimization algorithms
• Performance-based structural design
• Reliability based design optimization
• Robust design optimization
• Structural optimization

Publisher

This book is published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. For additional information regarding the publisher, please visit www.igi-global.com.

Book: "Design Optimization of Active and Passive Structural Control Systems", Eds: N.D. Lagaros, V. Plevris, Ch. Ch. Mitropoulou, IGI Global, 2012.

Description

A typical engineering task during the development of any system is, among others, to improve its performance in terms of cost and response. Improvements can be achieved either by simply using design rules based on the experience or in an automated way by using optimization methods that lead to optimum designs.

Design Optimization of Active and Passive Structural Control Systems includes Earthquake Engineering and Tuned Mass Damper research topics into a volume taking advantage of the connecting link between them, which is optimization. This is a publication addressing the design optimization of active and passive control systems. This title is perfect for engineers, professionals, professors, and students alike, providing cutting edge research and applications.

Reviews and Testimonials

"Structural control systems are designed to protect buildings, bridges, power plants, and other structures during earthquakes, and provide an alternative to conventional structural design methods. Pivoting on the concept of optimization, engineers here discuss various aspects of active and passive versions. Among the topics are the optimal placement of viscous dampers for seismic building design, the optimal design and practical considerations of tuned mass dampers, a neuromorphic smart controller for seismically excited structures, the optimum design of a new hysteretic dissipater, and multi-objective genetic algorithms for seismic response controls of structure".

– Book News Inc. Portland, OR

Topics Covered

• Active Control Systems
• Linear tuned mass dampers for seismic control
• Optimization algorithms
• Parametric identification
• Passive dissipative devices
• Seismic damage identification
• Seismically isolated structures
• Tuned Mass Dampers
• Variable stiffness systems for structural control
• Vibration control

Publisher

This book is published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. For additional information regarding the publisher, please visit www.igi-global.com.

Book: "Computational Methods in Earthquake Engineering: Volume 2", Eds: M. Papadrakakis, M. Fragiadakis, V. Plevris , Springer, 2013.

Description

This book provides an insight on advanced methods and concepts for the design and analysis of structures against earthquake loading. This second volume is a collection of 28 chapters written by leading experts in the field of structural analysis and earthquake engineering. Emphasis is given on current state-of-the-art methods and concepts in computing methods and their application in engineering practice. The book content is suitable for both practicing engineers and academics, covering a wide variety of topics in an effort to assist the timely dissemination of research findings for the mitigation of seismic risk. Due to the devastating socioeconomic consequences of seismic events, the topic is of great scientific interest and is expected to be of valuable help to scientists and engineers. The chapters of this volume are extended versions of selected papers presented at the COMPDYN 2011 conference, held in the island of Corfu, Greece, under the auspices of the European Community on Computational Methods in Applied Sciences (ECCOMAS).

Book: "Handbook of Research on Seismic Assessment and Rehabilitation of Historic Structures (2 Volumes)", Eds: P. G. Asteris and V. Plevris, IGI Global, 2015.

Description

Rehabilitation of heritage monuments provides sustainable development and cultural significance to a region. The most sensitive aspect of the refurbishment of existing buildings lies in the renovation and recovery of structural integrity and public safety.

The Handbook of Research on Seismic Assessment and Rehabilitation of Historic Structures evaluates developing contributions in the field of earthquake engineering with regards to the analysis and treatment of structural damage inflicted by seismic activity. This book is a vital reference source for professionals, researchers, students, and engineers active in the field of earthquake engineering who are interested in the emergent developments and research available in the preservation and rehabilitation of heritage buildings following seismic activity.

Topics Covered

• Masonry Materials
• Monument Restoration
• Passive Seismic Protection
• Probabilistic Seismic Hazard Analysis
• Restoration Materials Technology
• Structural Control Techniques
• Structural Damage
• Structural Rehabilitation

Publisher

This book is published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. For additional information regarding the publisher, please visit www.igi-global.com.