Typology of seismic motion and seismic engineering design

The paper deals with the influence of the seismic motion typology on the structural response and with engineering design under exceptional actions. Various aspects of seismic motion typology that lead to exceptional actions on the structures are covered. The influence of near fault ground motions, the effect of local site parameters and the magnification of the seismic action on short-period structures are among the parameters identified as dominant for the structural response. The paper presents also a methodology for handling uncertainty in engineering design, based on the mathematical framework of fuzzy analysis. Finally the paper presents various applications of performance based design, which is viewed as a tool as a tool for the analysis of structural behaviour under extreme seismic events. The influence of connection behaviour on the structural response is studied, and applications of the capacity design methodology and of the direct displacement design approach for the evaluation of reinforce concrete structures are presented

Criticality, Fractality and Intermittency in Strong Interactions

Assuming a second-order phase transition for the hadronization process, we attempt to associate intermittency patterns in high-energy hadronic collisions to fractal structures in configuration space and corresponding intermittency indices to the isothermal critical exponent at the transition temperature. In this approach, the most general multidimensional intermittency pattern, associated to a second-order phase transition of the strongly interacting system, is determined, and its relevance to present and future experiments is discussed.Comment: 15 pages + 2 figures (available on request), CERN-TH.6990/93, UA/NPPS-5-9

Sprawozdanie z I Spotkania Konsorcjum Akademickich Zakładów Studiów Strategicznych, Warszawa, 10 kwietnia 2017 r.

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Numerical study of low-yield point steel shear walls used for seismic applications

Purpose - The purpose of this paper is to provide the research and practising engineers with insight on the benefits of using low-yield point steel with respect to ordinary steel as a construction material for shear wall panels. The paper seeks to focus on the behaviour of such panels when installed in new or existing structures in order to improve theft seismic performance. Design/methodology/approach - Finite element models are applied in order to approximate the structural response of low-yield steel panels, used for seismic applications. Owing to the specific characteristics of the problem at hand, geometric and material nonlinearities have to be accurately considered. For comparison reasons, low-yield point steel and ordinary steel are considered as construction materials for the aforementioned panels. The paper examines both the case of "pure shear" steel panel and also the more realistic case that the panel is encased in the surrounding frame. Findings - The paper reaches a number of interesting conclusions. The beneficial behaviour of low-yield steel panels with respect to ordinary steel panels is verified. Comments are made distinguishing the differences in the behaviour of panels surrounded by strong elements ("encased" panels) compared with that of panels submitted to pure shear. Finally, the improved seismic behaviour of existing structures retrofitted by shear wall panels is verified. Originality/value - The paper exhibits numerically the advantages of low-yield point steel with respect to ordinary steel as a construction material for panels and, second, contributes to the comprehension of the realistic panel behaviour of encased panels. More specifically, the paper focuses on the differences in the behaviour of encased steel panels with respect to the "pure shear" steel panels

A neural network approach for the solution of frictional contact problems with nonconvex superpotentials

A neural network approach is proposed for the numerical treatment of frictional contact problems. A nonmonotone friction law is assumed to describe the stick-slip process which leads to the formulation of a computational intensive nonconvex-nonsmooth optimization problem. The problem is addressed by a heuristic method which effectively replaces the nonmonotone law by a sequence of monotone friction laws, leading to quadratic programming problems with inequality constraints. The resulting quadratic optimization problems are transformed into a system of appropriately defined differential equations. Then, an appropriate neural network is applied for the solution of the problem. The proposed method is illustrated through the solution of the engineering problem of the frictional contact between two shear walls. (C) 2002 Elsevier Science Ltd. All rights reserved

A heuristic method for nonconvex optimization in mechanics: Conceptual idea, theoretical justification, engineering applications

Structures involving nonmonotone, possibly multivalued reaction-displacement or stress-strain laws cannot be effectively treated by the numerical methods for classical nonlinearities. In this paper we make use of the fact that these problems have as a Variational formulation a hemivariational inequality, leading to a noncovex optimization problem. A new method is proposed which approximates the nonmonotone problem by a series of monotone ones. The method constitutes an iterative scheme for the approximation of the solutions of the corresponding hemivariational inequality. A simple numerical example demonstrates the conceptual idea of the proposed numerical method. In the sequel the method is applied on an engineering problem concerning the ultimate strength analysis of an eccentric braced steel frame

Solution of interface problems with nonmonotone contact and friction laws using a neural network optimization environment

The paper addresses the solution of interface problems which present a degrading behaviour leading to nonmonotone contact and friction laws. The paper is based on a superpotential formulation that leads to hemivariational inequalities, or, equivalently to nonconvex-nonsmooth optimization problems. The above problems are addressed with a heuristic method which effectively replaces the nonconvex-nonsmooth optimization problem by a sequence of quadratic programming problems with inequality constraints. Then, the quadratic optimization problems are transformed into a system of differential equations, which are treated numerically with an appropriate neural network. Finally, a numerical example illustrates the properties of the proposed algorithmic scheme. (C) 2004 Civil-Comp Ltd and Elsevier Ltd. All rights reserved

Ultimate compressive strength of CHS members with flattened edges

The paper studies circular hollow members which have been submitted to a procedure for the formation of a flattened edge. Two different ways of formation of flattened edges are investigated, one involving a single-step procedure and one involving a two-steps procedure. An unexpected failure mode under compressive loading is demonstrated, which is connected with the excessive plastification of the area near the flattened edges. The flattened members are simulated numerically using appropriate finite element models and nonlinear analysis. Finally, parametric analyses are performed in order to clarify the limits between the failure modes, and useful diagrams are obtained. © 2003 Elsevier Science Ltd. All rights reserved

Solution of nonmonotone friction unilateral contact problems within a neural network environment

A neural network approach for dealing with the solution of frictional contact problems is proposed. Such an approach permits the rational treatment of the aforementioned limit states. In particular, discretizing the structure by means of a suitable finite element scheme, the structural behavior is described by a discrete hemivariational inequality. An effective algorithm equivalently transforms the initial nonmonotone problem into a sequence of monotone, Coulomb friction problems. Then, a neural network computing system is applied in order to solve efficiently the arising optimization problems