Burnaev, E. V.
Published in
Journal of Communications Technology and Electronics
AbstractWe consider the problem of constructing predictive models (surrogate models) to tackle challenges of industrial engineering design. The author analyzed the needs of industrial applications, formulated a number of new mathematical and algorithmic problems and developed appropriate methods of data modeling.
Lataniotis, C.
In the context of complex industrial systems and civil infrastructures, taking into account uncertainties during the design process has received much attention in the last decades. Although there is significant progress in modelling such systems, there are always discrepancies between ideal in-silico designed systems and real-world manufactured one...
Chiaramello, Emma Parazzini, Marta Fiocchi, Serena Bonato, Marta Le Brusquet, Laurent Ravazzani, Paolo
This study focused on the evaluation of the electric field induced in the brain grey matter of a 5 years child when exposed to uniform magnetic field at 50 Hz with uncertain orientation. An innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method) in order to build space-dependent surrogat...
Chiaramello, E Parazzini, M. Fiocchi, S. Bonato, M Le Brusquet, Laurent Ravazzani, P
This study focused on the evaluation of the electric field induced in the brain grey matter of a 5 years child when exposed to uniform magnetic field at 50 Hz with uncertain orientation. An innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method) in order to build space-dependent surrogat...
Lindmark, Daniel M. Servin, Martin
A method for simulation-based development of robotic rock loading systems is described and tested. The idea is to first formulate a generic loading strategy as a function of the shape of the rock pile, the kinematics of the machine and a set of motion design variables that will be used by the autonomous control system. The relation between the load...
Reisgen, Uwe Willms, Konrad Josef Buchholz, Guido Koyama, Chika Herfert, Daniel
Dhariwal, Jay Banerjee, Rangan
Published in
Building Simulation
Building simulation based optimization involves direct coupling of the optimization algorithm to a simulation model, making it computationally intensive. To overcome this issue, an approach is proposed using a combination of experimental design techniques (fractional factorial design and response surface methodology). These techniques approximate t...
Hazyuk, Ion Budinger, Marc Sanchez, Florian Gogu, Christian
Published in
Structural and Multidisciplinary Optimization
This paper presents a method for constructing optimal design of experiments (DoE) intended for building surrogate models using dimensionless (or non-dimensional) variables. In order to increase the fidelity of the model obtained by regression, the DoE needs to optimally cover the dimensionless space. However, in order to generate the data for the r...
Kozieł, Sławomir Bekasiewicz, Adrian
Published in
Metrology and Measurement Systems
This work examines the reduced-cost design optimization of dual- and multi-band antennas. The primary challenge is independent yet simultaneous control of the antenna responses at two or more frequency bands. In order to handle this task, a feature-based optimization approach is adopted where the design objectives are formulated on the basis of the...
Singh, Prashant; Claeys, Tim; 93491; Vandenbosch, Guy; 5450; Pissoort, Davy; 66189;
In this paper, a novel algorithm that selects optimal paths for conducting automated near-field (NF) measurements is presented. The resulting dataset of measurements can then be used to model the complete NF electromagnetic emissions of an electronic device or predict the far-field emissions. The models obtained using the training sets generated wi...