Browsing by Keyword "Correlation"
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Item Advances in automatic thermal model to test correlation in space industry(Texas Tech. Univeristy (TTU), 2016-07) Klement, Jan; Anglada, Eva; Garmendia, IñakiIn space industry thermal models are an important tool to predict, analyze and understand the thermal behaviour of components, subsystems and whole spacecrafts. Most parameters of these models have a limited accuracy and consequently the models results are uncertain. In order to reduce this uncertainty to a required level the model parameters are adjusted (correlated) by fitting the model to test results obtained during thermo vacuum tests. This is often a difficult long lasting manual process. In order to perform these correlations automatically many different methods have been developed and analyzed. Two of these methods are analyzed regarding their requirements, efficiency and limitations. A genetic algorithm is compared to a method based on non-linear equations solving algorithms of the Broyden class.Item Finite Element Model Correlation of an Investment Casting Process(Trans Tech Publications, 2014-06) Anglada, Eva; Meléndez, Antton; Maestro, Laura; Domínguez, Ignacio; CIRMETAL; Tecnalia Research & InnovationThe achievement of reliable simulations, in the case of complex processes as is the investment casting, is not a trivial task. Their accuracy is significantly related with the knowledge of the material properties and boundary conditions involved, but the estimation of these values usually is highly complex. One helpful option to try to avoid these difficulties is the use of inverse modelling techniques, where experimental temperature measurements are used as base to correlate the simulation models. The research presented hereafter corresponds to the correlation of a finite element model of the investment casting process of two nickel base superalloys, Hastelloy X and Inconel 718. The simulation model has been developed in a commercial software focused specifically on metal casting simulation. The experimental measurements used as base for the adjustment, have been performed at industrial facilities. The methodology employed combines the use of an automatic tool for model correlation with the manual adjustment guided by the researchers. Results obtained present a good agreement between simulation and experimental measurements, according to the industrial necessities. The model obtained is valid for the two studied cases with the only difference of the alloy material properties. The values obtained for the adjusted parameters in both cases are reasonable compared with bibliographic values. These two circumstances suggest that the obtained correlation is appropriate and no overfitting problems exist on it.Item Gradient-Boosting Applied for Proactive Maintenance System in a Railway Bridge(Springer, Cham, 2021) García-Sánchez, David; Iglesias, Francisco; Diez, Jesus; Piñero, Iñaki; Fernández-Navamuel, Ana; Sánchez, Diego Zamora; Jiménez-Fernandez, José Carlos; Rizzo, Piervincenzo; Milazzo, Alberto; Tecnalia Research & Innovation; E&I SEGURAS Y RESILIENTESThis article contributes in the research direction of the application of Machine Learning techniques in bridge safety assessment and it lays basis to further improve the accuracy of safety assessment including analysis of real data. The communication puts forward the process and model of scale measured points correlation of bridge monitoring system on the frequency domain as a tactic to control the influence of a railway device (crossing) located on the top deck of a railway bridge. The process and model are put forward mainly for the characteristics of the damage detection for long-term assessment, going from an intensive multi-sensor monitoring system to a softer one. Finally, a Gradient-Boosting multi-regressor method has been developed to be easily implemented in a warning system that provides predictive skills to the current preventive maintenance strategy. The method is validated by simulating the undamaged and abnormal scenarios with Monte Carlo method.Item Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts(2017-05-24) Anglada, Eva; Martinez-Jimenez, Laura; Garmendia, Iñaki; CIRMETALThe correlation of the thermal mathematical models (TMMs) of spacecrafts with the results of the thermal test is a demanding task in terms of time and effort. Theoretically, it can be automatized by means of optimization techniques, although this is a challenging task. Previous studies have shown the ability of genetic algorithms to perform this task in several cases, although some limitations have been detected. In addition, gradient-based methods, although also presenting some limitations, have provided good solutions in other technical fields. For this reason, the performance of genetic algorithms and gradient-based methods in the correlation of TMMs is discussed in this paper to compare the pros and cons of them. The case of study used in the comparison is a real space instrument flown on board the International Space Station.