Including stochastics in metamodel-based DEM model calibration

Fransen, Marc P.; Langelaar, Matthijs; Schott, Dingena L.

doi:10.1016/j.powtec.2022.117400

Cited by 7 publications

(7 citation statements)

References 29 publications

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“…The model behaviour is investigated by varying one parameter and keeping all other parameters constant [31]. A calibration method involving the stochastic nature of the parameters is investigated by Fransen et al [32].…”

Section: Introductionmentioning

confidence: 99%

“…The determination of Sobol' indices requires a large number of model evaluations [39] which is computationally expensive especially for DEM simulations. In order to lower the computational effort, the evaluation of the Sobol' indices is based on metamodels [39] to predict the DEM simulation results which is a frequently used approach in literature [31,32,40,41]. The sampling points are created with the Latin hypercube sampling (LHS) methodology [42,43].…”

Section: Introductionmentioning

confidence: 99%

“…In [50][51][52], the stress distribution of conical piles is investigated while in [16] the characteristics of a sand heap generated under water with a combined computational fluid dynamics and DEM simulation is treated. For calibration purposes, the pile experiment is also frequently used [12,30,32,40,53]. The creation of a pile for different particle shapes using a superquadric representation is performed in [54].…”

Section: Introductionmentioning

confidence: 99%

“…One approach is slowly lifting a cylindrical tube filled with particles which is performed in [12,15,40]. Another technique is to remove the sidewalls or enable the flow out of a box filled with particles [15,32,56]. Phillip Grima and Wilhelm Wypych [12] investigate also a swing-arm slump test.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the sensitivity of DEM parameters on pile experiments

Jahn,

Meywerk

2024

Comp. Part. Mech.

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The discrete element method (DEM) is suitable to investigate problems where large deformations occur especially in granular material. The fitting of reliable DEM parameters is crucial and a challenge which is caused by the high number of DEM parameters and the computational effort. Despite its drawbacks, a trial and error approach is often used for the DEM parameter calibration. The knowledge of the DEM parameter influence on the model response is necessary to improve the calibration and to check whether the experiment is suitable to calibrate specific parameters or not. It is possible to reduce the dimensionality of the optimisation problem by omitting parameters whose influence on the model response is negligibly small. One approach is to perform a global sensitivity analysis based on Sobol’ indices. A frequently used calibration experiment in literature is the pile experiment. The deviation between the experiment and the simulation is evaluated with the angle of repose. In the present paper, an algorithm to determine the angle of repose considering the three-dimensional shape of the heap is discussed. The global sensitivity analysis is performed for two different experimental heap set-ups. To decrease the computational effort of the sensitivity analysis, the model response is approximated with metamodels whose predictability is evaluated using the root mean squared error (RMSE) based on a separate sampling point set.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the sensitivity of DEM parameters on pile experiments

Jahn,

Meywerk

2024

Comp. Part. Mech.

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“…Due to the stochastic nature of granular experiments, the investigation of a mean-and a mean-variance-based approach is conducted using metamodels [23]. In the meanvariance-based approach, the mean as well as the variance of the experimental data and the simulation should match.…”

Section: Introductionmentioning

confidence: 99%

On the sensitivity analysis of the DEM oedometer experiment

Jahn¹,

Meywerk²

2023

Comp. Part. Mech.

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The discrete element method (DEM) is frequently used to investigate the behaviour of granular media (Bravo in Simulation of soil and tillage-tool interaction by the discrete element method, 2013; Tijskens et al. in J Sound Vib 266:493–514, 2003; Langston et al. in Chem Eng Sci 50:967–987, 1995; Kohring et al. in Comput Methods Appl Mech Eng 124:273–281, 1995; Stahl et al. in Granul Matter 13:417–428, 2011). The parameter calibration is a challenging task due to the large number of input parameters and the computational effort. Sometimes, this is performed with a trial-and-error approach as mentioned in Roessler et al. (Powder Technol 343:803–812, 2019), Rackl and Hanley (Powder Technol 307:73–83, 2017) based on laboratory tests, e.g. the pile experiment, the oedometer experiment and the shear test. To achieve a more suitable calibration, a better model understanding is necessary in which the influence of the DEM parameters is analysed. Consequently, the calibration can be focused on specific parameters, which have a significant influence on thef model response. If parameters with a negligibly small influence exist, the number of calibration parameters can be reduced. On this basis, it is possible to decide whether the laboratory test is suitable for the calibration of specific parameters or not. This is demonstrated with a sensitivity analysis based on Sobol’ indices for the oedometer laboratory test. In order to reduce the computational effort, the sensitivity analysis is performed with different metamodels of the oedometer simulation. The metamodels are fitted and validated with two separate sampling point sets. It is shown that the Young’s modulus for the investigated input space is the most significant parameter. This knowledge can be used to only focus the calibration on this significant parameter which enables an easier calibration and makes clear that for calibrating of other parameters this laboratory test is inappropriate. An algorithm of a force-driven plate is developed and shown which prevents non-physical states in which the interaction force between the particles and the loadplate exceeds the applied force.

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Particle Size Segregation during Charging and Discharging Processes in Bell‐Less Blast Furnace with Serial‐Type Hoppers

Zeng,

Zou,

Wang

et al. 2024

steel research int.

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Burden distribution in a blast furnace not only determines the distribution of gas flow but also affects the thermal efficiency and fuel consumption of the blast furnace. Therefore, it is of great significance to study the burden segregation behaviors during the charging and discharging processes in blast furnaces. Herein, a 3D model of a 1:1 bell‐less top blast furnace with serial‐type hoppers is established based on the discrete element method. The model is used to simulate the entire process of the burden falling from the belt until it leaves the weighing hopper. The results show that the particle size segregation in the upper hopper is more severe than that in the weighing hopper, which also seriously affects the size segregation in the weighing hopper. Changing the charging sequence will reduce the segregation degree in two hoppers, but it cannot change the trend of particle size segregation in the final stage of the discharging process. The small particles are found to gather at the end of the discharging process, so the chute angle should be increased in the last few revolutions of the charging matrix to decrease the accumulation of small particles.

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Including stochastics in metamodel-based DEM model calibration

Cited by 7 publications

References 29 publications

On the sensitivity of DEM parameters on pile experiments

On the sensitivity of DEM parameters on pile experiments

On the sensitivity analysis of the DEM oedometer experiment

Particle Size Segregation during Charging and Discharging Processes in Bell‐Less Blast Furnace with Serial‐Type Hoppers

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