EFFICIENT CALIBRATION OF DISCRETE ELEMENT MATERIAL MODEL PARAMETERS USING LATIN HYPERCUBE SAMPLING AND KRIGING

Characterisation of groundwater modelling involves significant uncertainty because of estimation errors of these models and other different sources of uncertainty. Deterministic models do not account for uncertainties in model parameters, and thus lead to doubtful output. The main alternatives for deterministic models are the probabilistic models and perturbation methods such as Monte Carlo Simulation (MCS). Unfortunately, these methods have many drawbacks when applied in risk analysis of groundwater pollution. In this paper, a modified Latin Hypercube Sampling method is presented and used for risk, uncertainty, and sensitivity analysis of groundwater pollution. The obtained results were compared with other sampling methods. Results of the proposed method have shown that it can predict the groundwater contamination risk for all values of probability better than other methods, maintaining the accuracy of mean estimation. Sensitivity analysis results reveal that the contaminant concentration is more sensitive to longitudinal dispersivity than to velocity.

Download Full-text

A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain

International Journal of Biomathematics ◽

10.1142/s1793524518501103 ◽

2018 ◽

Vol 11 (08) ◽

pp. 1850110 ◽

Cited By ~ 2

Author(s):

Maha A. Mohammed ◽

N. F. M. Noor ◽

A. I. N. Ibrahim ◽

Z. Siri

Keyword(s):

Finite Difference ◽

Random Sampling ◽

Cocaine Abuse ◽

Prediction Interval ◽

Latin Hypercube Sampling ◽

Numerical Approach ◽

Model Parameters ◽

Latin Hypercube ◽

Statistical Probability ◽

Statistical Estimations

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method to complete one cycle of LHS-FD simulation iteration. This process is repeated until [Formula: see text] final iterations of LHS-FD are obtained. The means of these [Formula: see text] final solutions (MLHFD solutions) are tabulated, graphed and analyzed. The numerical simulation results of MLHFD for the SEIR model are presented side-by-side with deterministic solutions obtained from the classical FD scheme and homotopy analysis method with Pade approximation (HAM-Pade). The present MLHFD results are also compared with the previous non-deterministic statistical estimations from 1995 to 2015. Good agreement between the two is perceived with small errors. MLHFD method can be used to predict future behavior, range and prediction interval for the epidemic model solutions. The expected profiles of the cocaine abuse subpopulations are projected until the year 2045. Both the statistical estimations and the deterministic results of FD and HAM-Pade are found to be within the MLHFD prediction intervals for all the years and for all the subpopulations considered.

Download Full-text

Discrete element model calibration for industrial raw material simulations

MATEC Web of Conferences ◽

10.1051/matecconf/202134700036 ◽

2021 ◽

Vol 347 ◽

pp. 00036

Author(s):

Johan Bester ◽

Philip Venter ◽

Martin van Eldik

Keyword(s):

High Speed ◽

Real Life ◽

Material Model ◽

Element Model ◽

Discrete Element ◽

Raw Material ◽

Angle Of Repose ◽

Model Parameters ◽

Deflection Plate ◽

Calibration Methods

The use of computational fluid dynamics in continuous operation industries have become more prominent in recent times. Proposed system improvements through geometric changes or control strategies can be evaluated within a relatively shorter timeframe. Applications for discrete element methods (DEMs) in real life simulations, however, require validated material-calibration-methods. In this paper, the V-model methodology in combination with direct and bulk calibration approaches were followed to determine material model parameters, to simulate real life occurrences. For the bulk calibration approach a test rig with a containment hopper, deflection plate and settling zone was used. Screened material drains from the hopper, interacts with the deflection plate, and then settles at the material angle of repose. A high-speed camera captured material interaction with the rig, where footage was used during simulation validation. The direct measuring approach was used to determine particle size, shape and density, while confirming friction and restitution coefficients determined in the bulk calibration method. The test was repeated and validated for various geometrical changes. Three categories of validation were established, namely particle speed assessment, -trajectory assessment and -plate interaction assessment. In conclusion, the combination of direct and bulk calibration approaches was significant in calibrating the required material model parameters.

Download Full-text

Combining Latin Hypercube Sampling with Other Variance Reduction Techniques

SSRN Electronic Journal ◽

10.2139/ssrn.2179680 ◽

2012 ◽

Author(s):

Natalie Packham

Keyword(s):

Variance Reduction ◽

Latin Hypercube Sampling ◽

Latin Hypercube ◽

Variance Reduction Techniques ◽

Reduction Techniques

Download Full-text

Comparison of Factorial and Latin Hypercube Sampling Designs for Meta-Models of Building Heating and Cooling Loads

Energies ◽

10.3390/en14020512 ◽

2021 ◽

Vol 14 (2) ◽

pp. 512

Author(s):

Younhee Choi ◽

Doosam Song ◽

Sungmin Yoon ◽

Junemo Koo

Keyword(s):

Latin Hypercube Sampling ◽

Building Design ◽

Gain Coefficient ◽

Design Parameters ◽

Latin Hypercube ◽

Heating And Cooling ◽

Factor Design ◽

Heating Loads ◽

Cooling Loads ◽

Interest In Research

Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information.

Download Full-text

Assimilation of Dynamic Combined Finite Discrete Element Methods Using the Ensemble Kalman Filter

Applied Sciences ◽

10.3390/app11072898 ◽

2021 ◽

Vol 11 (7) ◽

pp. 2898

Author(s):

Humberto C. Godinez ◽

Esteban Rougier

Keyword(s):

Kalman Filter ◽

Ensemble Kalman Filter ◽

Failure Modes ◽

Split Hopkinson Pressure Bar ◽

Peak Stress ◽

Discrete Element ◽

Material Behavior ◽

Model Parameters ◽

Hopkinson Pressure Bar ◽

Parameter Values

Simulation of fracture initiation, propagation, and arrest is a problem of interest for many applications in the scientific community. There are a number of numerical methods used for this purpose, and among the most widely accepted is the combined finite-discrete element method (FDEM). To model fracture with FDEM, material behavior is described by specifying a combination of elastic properties, strengths (in the normal and tangential directions), and energy dissipated in failure modes I and II, which are modeled by incorporating a parameterized softening curve defining a post-peak stress-displacement relationship unique to each material. In this work, we implement a data assimilation method to estimate key model parameter values with the objective of improving the calibration processes for FDEM fracture simulations. Specifically, we implement the ensemble Kalman filter assimilation method to the Hybrid Optimization Software Suite (HOSS), a FDEM-based code which was developed for the simulation of fracture and fragmentation behavior. We present a set of assimilation experiments to match the numerical results obtained for a Split Hopkinson Pressure Bar (SHPB) model with experimental observations for granite. We achieved this by calibrating a subset of model parameters. The results show a steady convergence of the assimilated parameter values towards observed time/stress curves from the SHPB observations. In particular, both tensile and shear strengths seem to be converging faster than the other parameters considered.

Download Full-text

Uncertainty Quantification of the 1-D SFR Thermal Stratification Model via the Latin Hypercube Sampling Monte Carlo Method

Nuclear Technology ◽

10.1080/00295450.2021.1874779 ◽

2021 ◽

pp. 1-12

Author(s):

Cihang Lu ◽

Zeyun Wu

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Uncertainty Quantification ◽

Thermal Stratification ◽

Latin Hypercube Sampling ◽

Latin Hypercube

Download Full-text

Variation of Passive Biomechanical Properties of the Small Intestine along Its Length: Microstructure-Based Characterization

Bioengineering ◽

10.3390/bioengineering8030032 ◽

2021 ◽

Vol 8 (3) ◽

pp. 32

Author(s):

Dimitrios P. Sokolis

Keyword(s):

Small Intestine ◽

Orientation Angle ◽

Axial Direction ◽

Material Model ◽

Biomechanical Properties ◽

Intestinal Wall ◽

Model Parameters ◽

Material Models ◽

Hyper Elastic ◽

Rat Tissue

Multiaxial testing of the small intestinal wall is critical for understanding its biomechanical properties and defining material models, but limited data and material models are available. The aim of the present study was to develop a microstructure-based material model for the small intestine and test whether there was a significant variation in the passive biomechanical properties along the length of the organ. Rat tissue was cut into eight segments that underwent inflation/extension testing, and their nonlinearly hyper-elastic and anisotropic response was characterized by a fiber-reinforced model. Extensive parametric analysis showed a non-significant contribution to the model of the isotropic matrix and circumferential-fiber family, leading also to severe over-parameterization. Such issues were not apparent with the reduced neo-Hookean and (axial and diagonal)-fiber family model, that provided equally accurate fitting results. Absence from the model of either the axial or diagonal-fiber families led to ill representations of the force- and pressure-diameter data, respectively. The primary direction of anisotropy, designated by the estimated orientation angle of diagonal-fiber families, was about 35° to the axial direction, corroborating prior microscopic observations of submucosal collagen-fiber orientation. The estimated model parameters varied across and within the duodenum, jejunum, and ileum, corroborating histologically assessed segmental differences in layer thicknesses.

Download Full-text

Flexural behavior of composite structural insulated panels with magnesium oxide board facings

Archives of Civil and Mechanical Engineering ◽

10.1007/s43452-020-00109-y ◽

2020 ◽

Vol 20 (4) ◽

Author(s):

Łukasz Smakosz ◽

Ireneusz Kreja ◽

Zbigniew Pozorski

Keyword(s):

Magnesium Oxide ◽

Material Model ◽

Expanded Polystyrene ◽

Flexural Behavior ◽

Joint Analysis ◽

Model Parameters ◽

Fe Model ◽

Computational Results ◽

Four Point Bending ◽

Proposed Model

Abstract The current report is devoted to the flexural analysis of a composite structural insulated panel (CSIP) with magnesium oxide board facings and expanded polystyrene (EPS) core, that was recently introduced to the building industry. An advanced nonlinear FE model was created in the ABAQUS environment, able to simulate the CSIP’s flexural behavior in great detail. An original custom code procedure was developed, which allowed to include material bimodularity to significantly improve the accuracy of computational results and failure mode predictions. Material model parameters describing the nonlinear range were identified in a joint analysis of laboratory tests and their numerical simulations performed on CSIP beams of three different lengths subjected to three- and four-point bending. The model was validated by confronting computational results with experimental results for natural scale panels; a good correlation between the two results proved that the proposed model could effectively support the CSIP design process.

Download Full-text

Considering multiple process observables to determine material model parameters for FE-cutting simulations

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-021-06845-6 ◽

2021 ◽

Author(s):

Marvin Hardt ◽

Thomas Bergs

Keyword(s):

Chip Thickness ◽

Material Model ◽

Experimental Investigations ◽

Model Parameters ◽

Inverse Approach ◽

Local Material ◽

Novel Approach ◽

Validation Parameters ◽

Multiple Process ◽

Cutting Simulations

AbstractAnalyzing the chip formation process by means of the finite element method (FEM) is an established procedure to understand the cutting process. For a realistic simulation, different input models are required, among which the material model is crucial. To determine the underlying material model parameters, inverse methods have found an increasing acceptance within the last decade. The calculated model parameters exhibit good validity within the domain of investigation, but suffer from their non-uniqueness. To overcome the drawback of the non-uniqueness, the literature suggests either to enlarge the domain of experimental investigations or to use more process observables as validation parameters. This paper presents a novel approach merging both suggestions: a fully automatized procedure in conjunction with the use of multiple process observables is utilized to investigate the non-uniqueness of material model parameters for the domain of cutting simulations. The underlying approach is two-fold: Firstly, the accuracy of the evaluated process observables from FE simulations is enhanced by establishing an automatized routine. Secondly, the number of process observables that are considered in the inverse approach is increased. For this purpose, the cutting force, cutting normal force, chip temperature, chip thickness, and chip radius are taken into account. It was shown that multiple parameter sets of the material model can result in almost identical simulation results in terms of the simulated process observables and the local material loads.

Download Full-text