A Variance-Expected Compliance Model for Structural Optimization

t The goal of this paper is to find robust structures for a given main load and its perturbations. In the first part, we show the mathematical formulation of an original variance-expected compliance model used for structural optimization. In the second part, we study the interest of this model on two 3D benchmark test cases and compare the obtained results with those given by an expected compliance mode

Inverse modelling of an aneurysm's stiffness using surrogate-based optimization and fluid-structure interaction simulations

Characterization of the mechanical properties of arterial tissues is highly relevant. In this work, we apply an inverse modelling approach to a model accounting for an aneurysm and the distal part of the circulation which can be modified using two independent stiffness parameters. For given values of these parameters, the position of the arterial wall as a function of time is calculated using a forward simulation which takes the fluid-structure interaction (FSI) into account. Using this forward simulation, the correct values of the stiffness parameters are obtained by minimizing a cost function, which is defined as the difference between the forward simulation and a measurement. The minimization is performed by means of surrogate-based optimization using a Kriging model combined with the expected improvement infill criterion. The results show that the stiffness parameters converge to the correct values, both for a zero-dimensional and for a three-dimensional model of the aneurysm

Selection of earthquake ground motions for multiple objectives using genetic algorithms

Existing earthquake ground motion (GM) selection methods for the seismic assessment of structural systems focus on spectral compatibility in terms of either only central values or both central values and variability. In this way, important selection criteria related to the seismology of the region, local soil conditions, strong GM intensity and duration as well as the magnitude of scale factors are considered only indirectly by setting them as constraints in the pre-processing phase in the form of permissible ranges. In this study, a novel framework for the optimum selection of earthquake GMs is presented, where the aforementioned criteria are treated explicitly as selection objectives. The framework is based on the principles of multi-objective optimization that is addressed with the aid of the Weighted Sum Method, which supports decision making both in the pre-processing and post-processing phase of the GM selection procedure. The solution of the derived equivalent single-objective optimization problem is performed by the application of a mixed-integer Genetic Algorithm and the effects of its parameters on the efficiency of the selection procedure are investigated. Application of the proposed framework shows that it is able to track GM sets that not only provide excellent spectral matching but they are also able to simultaneously consider more explicitly a set of additional criteria

Model B4 : multi-decade creep and shrinkage prediction of traditional and modern concretes

To improve the sustainability of concrete infrastructure, engineers face the challenge of incorporating new concrete materials while pushing the expected design life beyond 100 years. The time-dependent creep and shrinkage response of concrete governs the serviceability and durability in this multi-decade time frame. It has been shown that current prediction equations for creep and shrinkage underestimate material deformations observed in structures outside of a laboratory environment. A new prediction model for creep and shrinkage is presented that can overcome some of the shortcomings of the current equations. The model represents an extension and systematic recalibration of model B3, a 1995 RILEM Recommendation, which derives its functional form from the phenomena of diffusion, chemical hydration, moisture sorption, and the evolution of micro-stresses in the cement structure. The model is calibrated through a joint optimization of a new enlarged laboratory test database and a new database of bridge deflection records to overcome the bias towards short-term behavior. A framework for considering effects of aggregates, admixtures, additives, and higher temperatures is also incorporated

Energy Risk Management with Carbon Assets

This article proposes a mean-variance optimization and portfolio frontier analysis of energy risk management with carbon assets, introduced in January 2005 as part of the EU Emissions Trading Scheme. In a stylized exercise, we compute returns, standard deviations and correlations for various asset classes from April 2005 to January 2009. Our central result features an expected return of 3% with a standard deviationMean-variance optimization; Portfolio frontier analysis; CAPM; CO2; Carbon; Energy; Bonds; Equity; Asset Management; EU ETS; CERs