Alberto Gallina

Parameter Identification of a Planetary Rover Wheel–Soil Contact Model via a Bayesian Approach

Soft soil contact models developed for planetary exploration rovers play an important role in the study of rover mobility. Nowadays, most of the existing contact models are based on Bekker theory, which requires the evaluation of several soil parameters usually measured via bevameter tests. However, substantial differences existing between the plate-soil contact scenario and the wheel-soil contact scenario, along with large variability associated with the bevameter experiments, give rise to large uncertainty in the choice of the model parameter values. In this paper, a Bayesian procedure is proposed to deal effectively with the presence of uncertainty. In the proposed approach, model parameters are random variables with prior distributions derived from bevameter measurements. The prior distributions are then enhanced to posterior distributions through single wheel test data. At the end, the procedure identifies a set of possible model parameter configurations that result in high experimental-numerical matching

Study of the Effect of Process Induced Uncertainties on the Performance of a Micro-Comb Resonator

This paper presents a modeling technique based on the integration in the classic deterministic simulation methods of probabilistic computational techniques such as uncertainty analysis and sensitivity analysis. As study case, it is presented a micro-comb resonator that is actuated electrostatically to vibrate in the plane parallel to the substrate. A deterministic Finite Element coupled electromechanical analysis is performed to evaluate the mode shapes and the corresponding eigenfrequencies of the mobile mass and afterwards a Monte Carlo simulation is used to determine the dispersion of the eigenfrequency of the mode shape of interest in function of the variations of the input parameters. The scatter of the results is analyzed and then it is presented a sensitivity analysis for establishing which of the input parameters have more influence on the variability of the microresonators performance.

Bayesian parameter identification of orthotropic composite materials using Lamb waves dispersion curves measurement

This paper deals with the problem of elastic constant identification in thin plates made of orthotropic composite materials. The approach is based on the analysis of Lamb wave propagation and the related dispersion curves to find the underlying material elastic constants. In the proposed implementation a scanning laser Doppler vibrometer is used to measure Lamb wave dispersion curves. The Local Interaction Simulation Approach is used simultaneously to find a solution to a high-frequency wave propagation problem. The experimental and simulated data are combined in a Bayesian framework for parameter identification which is robust in condition of parameter, modeling and measurement uncertainty. The results are discussed and compared with the results from a deterministic optimization.

Analysis of Lamb wave dispersion curve sensitivity to material elastic constants in composites

The paper deals with the problem of Lamb waves dispersion curves sensitivity to the change of elastic constants in composite materials. The framework of the present work is a more general problem of material constants identification in thin plates made of composite materials. The approach is based on the analysis of guided waves propagation and the related dispersion curves to find the underlying material elastic constants. In present work a numerical study is performed to identify measurement directions and wave propagation modes that are most sensitive to the change of the particular elastic constants. This approach will allow to optimize the material constants identification procedure and experimental setup by specifying the preferred measurement directions and wave propagation modes. The approach can be used within the Structural Health Monitoring framework to monitor material degradation of plate-like structures made of composite materials.

Application of multibody simulation for semitrailer optimization

This paper presents an approach of optimization of a truck semitrailer suspension system, with utilization of multibody model; its purpose was to find the best values of operational parameters: stiffness and damping factors, in order to minimize the disadvantageous influence of force distribution in the high risk areas, where preceding strength analysis has pointed out dangerous load values. The model contains elements of two different types: flexible and rigid bodies, in purpose of increasing the accuracy level of conducted numerical calculations. A number of simulations with different parameters and under different load cases have been carried out, combined with a parametric and structural sensitivity analysis, what has enabled an estimation of individual factors influencing particular forces that have been the objectives of optimization procedure. The stiffness and damping coefficients of the construction suspension system have been adjusted by applying metamodeling techniques. Basing on the chosen design of experiment results, this procedure allows for an approximation of the behaviour of the analysed construction in the whole design space. In this process, two different approaches have been used: Kriging and polynomial regression, and both have been compared to the simulations results. Finally, using a desirability function, the most optimal solution has been found.

Simulation and optimization of heavy-duty semitrailer dynamic model/Symulacja i optymalizacja dynamicznego modelu naczepy pojazdów transportu ciężkiego

Abstract This paper presents an optimization of a multibody truck semitrailer model; its purpose was to find the best values of suspension parameters in order to minimize the disadvantageous influence of force distribution in the high risk areas. A number of simulations with different parameters and under different load cases have been carried out, combined with a parametric and structural sensitivity analysis, and in this way individual factors influencing particular forces have been estimated. The stiffness and damping coefficients of the construction suspension system have been adjusted by applying metamodeling techniques, using two different approaches: Kriging and polynomial regression. Finally, using a desirability function, the most optimal solution has been found. Streszczenie Artykuł przedstawia proces optymalizacji systemu zawieszenia wirtualnego modelu dynamicznego naczepy samochodowej, przeznaczonej dla pojazdów transportu ciężkiego. Celem podjętych prób było znalezienie wartości charakteryzujących odpowiedź układu na wymuszenia dynamiczne, minimalizujących ich niekorzystny wpływ na punkty konstrukcyjne, będące narażone na nadmierne obciążenia. Przeprowadzono szereg symulacji numerycznych, w oparciu o wyniki których określono wrażliwość systemu na zmieniające się parametry konstrukcyjne oraz użytkowe. Optymalne wartości współczynników tłumienia oraz sztywności badanego systemu obliczono z wykorzystaniem konwersji zagadnienia na monokryterialny problem decyzyjny, w oparciu o skonstruowane dwiema metodami (tj. Kriging i regresją wielomianową) powierzchnie odpowiedzi.