Papers by Keyword: Inverse Analysis

Abstract: The sintering behavior of spark plasma sintering was analyzed by extracting features from process data obtained during the fabrication of aluminum matrix composites and machine learning using the obtained features were performed to predict relative density of composites. Seventy-five samples were sintered with different types of reinforcement, and different temperature and pressure conditions. Regression methods include linear regression such as Ridge, Lasso and Elastic Net, and nonlinear regression such as random forest, gradient boosting and XGBoost were tested. XGBoost had the highest prediction accuracy and the trained model was used for Shapley additive explanations value analysis and inverse analysis.

Abstract: Magnetorheological Fluids (MRFs) are included in the so called “smart materials”: they are suspensions of magnetically responsive particles in a liquid carrier, whose rheological behaviour (e.g., its viscosity) can be changed quickly and reversibly if subjected to a magnetic field. Their application as forming medium in sheet metal forming processes is gaining interests in the recent years since the thickness and the strain distribution on the formed part can be affected by properly changing the properties of the MRF. In order to widely adopt MRFs in such processes, the evaluation of their rheological behaviour according to the applied magnetic field plays a key role. But there are still few works in the literature about the most effective way to characterise the MRFs to be used in sheet metal forming applications.In this work, the rheological behaviour of a MRF is carried out by means of an inverse analysis approach using data from bulge tests performed using an MRF as forming medium. Bulge tests were conducted on sheets having known properties using an equipment with a solenoid to generate the magnetic field, which was specifically designed and manufactured. Pressure rate and magnetic flux density were varied according to a Design of Experiments (DoE) while the strain experienced by the sheet material was acquired by means of a Digital Image Correlation (DIC) system in order to compare it with the numerical one. In particular, the fitting between numerical and experimental data was obtained by changing the MRF’s rheological properties using an inverse analysis technique. The proposed methodology allows to evaluate the MRF behaviour at different levels of both magnetic field and pressure rate, which are determinant for the FE simulation of sheet metal forming processes.

Abstract: In this work we apply a numerical inverse analysis procedure based on the ICME framework to ensure a required microstructure and combination of properties in the quenched plate. The microstructure is decided first, and the cooling profile needed to obtain such microstructure is then calculated using the CALPHAD approach. Subsequently, an inverse analysis of the heat transfer problem provides the description of the convection mechanism in quenching that results in the demanded cooling profile. An additional constraint is set on the through-thickness thermal gradient to achieve a homogeneous microstructure. Finally, the resultant microstructure is computed. By means of the proposed model we are able to retrieve the necessary quenching process parameters and to quantify the influence of these parameters on the temperature and microstructure distribution within the plate after the quenching.

Abstract: In this study, a new inverse analysis framework for estimation of myocardium constitutive parameters is established. In this framework, by using cardiac magnetic resonance image of realistic human left ventricular, a more realistic, finite element analysis model for analyzing the deformation of left ventricle during diastole is introduced. The anisotropic nonlinear Holzapfel-Ogden constitutive model is used to describe the material behavior of myocardium. Estimating the parameters as for the inverse problem of left ventricle deformation, a novel hybrid simplex and particle swarm optimization algorithm is proposed to estimate the parameters of myocardium’s constitutive model. Numerical examples presents that finite element analysis results and the estimated parameters are in good agreement with the experimental data reported in literature, comparing with current optimization algorithm, the presented hybrid optimal algorithm can estimate the constitutive parameters more efficient. The efficiency and validity of the proposed parameter estimation framework is demonstrated.

Abstract: A new model to predict the structure evolution of 30Cr2Ni4MoV steel is proposed based on the dislocation density in this research. Hot compression of 30Cr2Ni4MoV steel is carried out on Gleeble 1500 at different temperatures from 1233 K to 1473 K with a strain rate of 0.01 s^-1 and the deformed samples are immediately quenched by water to frozen the austenite structure. The recrystallization kinetics model of 30Cr2Ni4MoV steel is successfully established by inverse analysis of the flow curve based on the relation between flow stress and dislocation density. In order to validate the proposed model, comparison between the predicted values and experimental values obtained by metallographic analysis is implemented. It is shown that the predicted results agree with the experimental results well.

Abstract: To predict accurate cutting forces and residual stresses while machining products or to design optimum machining conditions like friction stir welding (FSW), FEM analyses are effective because they can reduce the cost of product design and improve product qualities. In order to conduct these FEM analyses precisely, it is necessary to determine accurate flow stresses of workpieces used for the constitutive equations of analyses that generally have a wide range of temperatures and strain rates. Correct identification of flow stress can lead to better analysis results close to actual phenomenon. In this study, focusing on 6061-T6 aluminum alloy used for objects such as civil engineering structures and railway vehicle bodies, we investigated the properties for machining the material. For this, we carried out an inverse analysis to understand the flow stress of 6061-T6 machined at high-strain rates and high temperatures. Then, we used this identified flow stress in the constitutive equation of FEM models, and inspected the accuracy of material properties conducting verification experiments and analyses to check the cutting forces and chip temperature while machining. As a result, we obtained good correlations between verification experiments and an analysis, which means the identified flow stress can be used for precise FEM analyses when machining materials.

Abstract: An objective reliability analysis of structural members made of advanced cementitious composites must be based on good knowledge of stochastic properties of individual mechanical fracture parameters of utilized material models. The article presents a comprehensive approach to the design and assessment of precast structural elements including: The series of fracture tests of the two concrete mixtures with various ages in two configurations (three point bending and wedge splitting test, subsequent identification of material parameters using effective crack model, work of fracture method and artificial neural networks, execution of destructive tests of scaled structural members and creation of deterministic models of these tests using collected data. In subsequent phases of the project reliability analysis of tested beams will be carried out in order to obtain stochastic parameters of structural response of prestressed elements to shear load. The obtained data will be used to calibrate the analytical equation describing the response of element exposed to both normal and shear forces. The entire process will be concluded by reliability-based optimization of manufactured components.

Abstract: It’s well known that the microstructure dramatically affects the strain behaviour of superplastic materials. Virtually, each batch should be characterized ex novo: optimal ranges of temperature and strain rate as well as material constants have to be defined. An accurate and simple characterization methodology based on a strain condition close enough to the real forming process is of great industrial interest. In this work, a characterization methodology based on an experimental and numerical approach is proposed. Experimental free inflation tests with a pressure jump were carried out on a titanium alloy. Results were used as reference data for an inverse analysis based on the height evolution of the dome. Material constants were calculated by means of a genetic algorithm. The approach was verified with further experimental results and a good correlation was found.

Abstract: An analytical approach to the determination of a varying salt diffusion coefficient is discussed. It is argued that the approach is fast and reliable and can be very convenient in various civil engineering applications dealing with the transport of salts in porous building materials. The advection-diffusion model of Bear and Bachmat is used to describe the salt transport, and the Bolztmann-Matano inverse analysis is applied to calculate the salt diffusion coefficient. Possible extensions to other models of transport are pointed out. The results are applied to a sandstone from the Msene quarry, Czech Republic.

Abstract: This paper offers a comparison of two different approaches aimed at the identification of moisture diffusivity of porous building materials as a function of moisture content. The approaches are represented by a traditional deterministic approach using the Boltzmann-Matano method and novel stochastic approach by genetic programming. The results of the comparative analysis show that genetic programming may be used as an alternative to the traditional approaches. On the basis of the very good agreement between experimental data and optimized output of genetic programming, the validation of the genetic programming method may be considered as successful.