Lecture

Maximizing Load Train Effect

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In course

CIVIL-124: Statics (for GC)

Ce cours a pour but de développer une compréhension des modèles statiques de structures. Il présente l'étude du jeu des forces dans les constructions isostatiques formées de barres, poutres et câbles. ...

Description

This lecture covers the concept of virtual work to find the position of loads in a train that maximizes the moment. Through examples and calculations, the instructor demonstrates how to determine the optimal position for maximum effect.

Instructors (2)

Emmanuel Denarié

Emmanuel Denarié is a civil engineer, with a PhD in Materials Science. He worked for 3 years in a civil engineering company where he was in charge of the design of structures and the maintenance of bridges. He has 30 years’ experience on research and applications in the field of building materials, advanced concretes, and rehabilitation of reinforced concrete structures. He is since 2000 senior scientist and lecturer in the Laboratory for Maintenance and Safety of structures, at Ecole Polytechnique Fédérale de Lausanne (EPFL), in charge of research and development activities on the application of concretes and advanced cementitious materials to the improvement of existing and new structures. In 2013, under the lead of Emmanuel Denarié, in cooperation with CEREMA, Subdivision des Phares et Balises from Lorient, and Lafarge, a turret at sea (Le Cabon, Brittany, France) was reinforced by a cast on site 60 mm thick UHPFRC shell. The strain hardening mix was developed jointly with Lafarge. This successful application in extreme conditions of access and restraint of the substrate (thin ring geometry) opened the way to large-scale industrial applications of UHPFRC for the reinforcement of existing structures.

Katrin Beyer

Since 2017 Associate Professor, School of Architecture, Civil and Environmental Engineering (ENAC), EPFL. Head of the Earthquake Engineering and Structural Dynamics (EESD) Laboratory 2010-2017 Assistant Professor, EPFL. 2008-2010 Post-doctoral researcher, ETH Zürich. 2003-2007 Ph.D., Roseschool / Università di Pavia, Italy. 2001-2003 Ove Arup & Partners, Advanced Technology and Research Group, London. 2001 Diploma, Civil engineering, ETH Zürich.

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Related concepts (20)

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

Combinatorial optimization

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the set of feasible solutions is discrete or can be reduced to a discrete set. Typical combinatorial optimization problems are the travelling salesman problem ("TSP"), the minimum spanning tree problem ("MST"), and the knapsack problem. In many such problems, such as the ones previously mentioned, exhaustive search is not tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead.

Program optimization

In computer science, program optimization, code optimization, or software optimization, is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. In general, a computer program may be optimized so that it executes more rapidly, or to make it capable of operating with less memory storage or other resources, or draw less power. Although the word "optimization" shares the same root as "optimal", it is rare for the process of optimization to produce a truly optimal system.

Convex optimization

Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard.

Mechanical engineering

Mechanical engineering is the study of physical machines that may involve force and movement. It is an engineering branch that combines engineering physics and mathematics principles with materials science, to design, analyze, manufacture, and maintain mechanical systems. It is one of the oldest and broadest of the engineering branches. Mechanical engineering requires an understanding of core areas including mechanics, dynamics, thermodynamics, materials science, design, structural analysis, and electricity.

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