On modeling the dynamic thermal behavior of electrical machines using genetic programming and artificial neural networks.

We describe initial attempts to model the dynamic thermal behavior of electrical machines by evaluating the ability of linear and non-linear (regression) modeling techniques to replicate the performance of simulations carried out using a lumped parameter thermal network (LPTN) and two different test scenarios. Our focus falls on creating highly accurate simple models that are well-suited for the real-time computational demands of an envisioned symbiotic interaction paradigm. Preliminary results are quite encouraging and highlight the very positive impact of integrating synthetic features based on exponential moving averages

Comparative run-time performance of evolutionary algorithms on multi-objective interpolated continuous optimisation problems.

We propose a new class of multi-objective benchmark problems on which we analyse the performance of four well established multi-objective evolutionary algorithms (MOEAs) – each implementing a different search paradigm – by comparing run-time convergence behaviour over a set of 1200 problem instances. The new benchmarks are created by fusing previously proposed single-objective interpolated continuous optimisation problems (ICOPs) via a common set of Pareto non-dominated seeds. They thus inherit the ICOP property of having tunable fitness landscape features. The benchmarks are of intrinsic interest as they derive from interpolation methods and so can approximate general problem instances. This property is revealed to be of particular importance as our extensive set of numerical experiments indicates that choices pertaining to (i) the weighting of the inverse distance interpolation function and (ii) the problem dimension can be used to construct problems that are challenging to all tested multi-objective search paradigms. This in turn means that the new multi-objective ICOPs problems (MO-ICOPs) can be used to construct well-balanced benchmark sets that discriminate well between the run-time convergence behaviour of different solvers

PAVED: Pareto Front Visualization for Engineering Design

Design problems in engineering typically involve a large solution space and several potentially conflicting criteria. Selecting a compromise solution is often supported by optimization algorithms that compute hundreds of Pareto-optimal solutions, thus informing a decision by the engineer. However, the complexity of evaluating and comparing alternatives increases with the number of criteria that need to be considered at the same time. We present a design study on Pareto front visualization to support engineers in applying their expertise and subjective preferences for selection of the most-preferred solution. We provide a characterization of data and tasks from the parametric design of electric motors. The requirements identified were the basis for our development of PAVED, an interactive parallel coordinates visualization for exploration of multi-criteria alternatives. We reflect on our user-centered design process that included iterative refinement with real data in close collaboration with a domain expert as well as a summative evaluation in the field. The results suggest a high usability of our visualization as part of a real-world engineering design workflow. Our lessons learned can serve as guidance to future visualization developers targeting multi-criteria optimization problems in engineering design or alternative domains

Cu mixed oxides based on hydrotalcite-like compounds for the oxidation of trichloroethylene

Consolider Ingenio Multicat MAT-2012-3856-C02-01[EN] Different Cu/(Mg or Ni)/Al mixed oxides based on hydrotalcite-like compounds have been studied for the catalytic oxidation of trichloroethylene. The catalysts have been synthesized and characterized by different techniques such as N-2-adsorption, inductively coupled plasma (ICP), X-ray diffraction, and temperature-programmed reduction (TPR). It has been shown that the activity for the catalytic abatement of trichloroethylene depends on the presence of metals with redox properties in the catalyst composition. The best results have been obtained with containing copper mixed oxides, although there is no direct correspondence between the copper content and the catalyst activity. These catalysts are highly active and selective, CO2 and HCl being the main reaction products. A mechanism for the reaction has been proposed.The authors wish to thank CONACYT (project 154060), the Spanish Ministry of Economy and Competitiveness through the Severo Ochoa program (SEV-2012-0267), as well as operating grants Consolider Ingenio Multicat (CSD-2009-00050) and MAT-2012-3856-C02-01 for the financial support. N.B.R. acknowledges Catedra Cemex Sostenibilidad (UPV) for a fellowship. The technical work of Adriana Tejeda in X-ray diffraction is also gratefully recognized.Blanch Raga, N.; Palomares Gimeno, AE.; Martínez Triguero, LJ.; Fetter, G.; Bosch, P. (2013). Cu mixed oxides based on hydrotalcite-like compounds for the oxidation of trichloroethylene. Industrial and Engineering Chemistry Research. 52(45):15772-15779. https://doi.org/10.1021/ie4024935S1577215779524