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The main purpose of this paper is to present a comprehensive upscale theory of the thermo-mechanical coupling particle simulation for three-dimensional (3D) large-scale non-isothermal problems, so that a small 3D length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large 3D length-scale one.

The objective is achieved by following the scaling methodology proposed by Feng and Owen (2014).

After four basic physical quantities and their similarity-ratios are chosen, the derived quantities and its similarity-ratios can be derived from its dimensions. As the proposed comprehensive 3D upscale theory contains five similarity criteria, it reveals the intrinsic relationship between the particle-simulation solution obtained from a small 3D length-scale (e.g. a laboratory length-scale) model and that obtained from a large 3D length-scale (e.g. a geological length-scale) one. The scale invariance of the 3D interaction law in the thermo-mechanical coupled particle model is examined. The proposed 3D upscale theory is tested through two typical examples. Finally, a practical application example of 3D transient heat flow in a solid with constant heat flux is given to illustrate the performance of the proposed 3D upscale theory in the thermo-mechanical coupling particle simulation of 3D large-scale non-isothermal problems. Both the benchmark tests and application example are provided to demonstrate the correctness and usefulness of the proposed 3D upscale theory for simulating 3D non-isothermal problems using the particle simulation method.

The paper provides some important theoretical guidance to modeling 3D large-scale non-isothermal problems at both the engineering length-scale (i.e. the meter-scale) and the geological length-scale (i.e. the kilometer-scale) using the particle simulation method directly.

3D steady heat conduction analysis considering heat source is conducted on the fundamental of the fast multipole method (FMM)-accelerated line integration boundary element method (LIBEM).

Due to considering the heat source, domain integral is generated in the traditional heat conduction boundary integral equation (BIE), which will counteract the well-known merit of the BEM, namely, boundary-only discretization. To avoid volume discretization, the enhanced BEM, the LIBEM with dimension reduction property is introduced to transfer the domain integral into line integrals. Besides, owing to the unsatisfactory performance of the LIBEM when it comes to large-scale structures requiring massive computation, the FMM-accelerated LIBEM (FM-LIBEM) is proposed to improve the computation efficiency further.

Assuming N and M are the numbers of nodes and integral lines, respectively, the FM-LIBEM can reduce the time complexity from O(NM) to about O(N+ M), and a full discussion and verification of the advantage are done based on numerical examples under heat conduction.

(1) The LIBEM is applied to 3D heat conduction analysis with heat source. (2) The domain integrals can be transformed into boundary integrals with straight line integrals by the LIM. (3) A FM-LIBEM is proposed and can reduce the time complexity from O(NM) to O(N+ M). (4) The FM-LIBEM with high computational efficiency is exerted to solve 3D heat conduction analysis with heat source in massive computation successfully.

The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional.

Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images).

Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.

Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

To present a discrete particle model for granular materials.

Starting with kinematical analysis of relative movements of two typical circular grains with different radii in contact, both the relative rolling and the relative sliding motion measurements at contact, including translational and angular velocities (displacements) are defined. Both the rolling and sliding friction tangential forces, and the rolling friction resistance moment, which are constitutively related to corresponding relative motion measurements defined, are formulated and integrated into the framework of dynamic model of the discrete element method.

Numerical results demonstrate that the importance of rolling friction resistance, including both rolling friction tangential force and rolling friction resistance moment, in correct simulations of physical behavior in particulate systems; and the capability of the proposed model in simulating the different types of failure modes, such as the landslide (shear bands), the compression cracking and the mud avalanching, in granular materials.

Each grain in the particulate system under consideration is assumed to be rigid and circular. Do not account for the effects of plastic deformation at the contact points.

To model the failure phenomena of granular materials in geo‐mechanics and geo‐technical engineering problems; and to be a component model in a combined discrete‐continuum macroscopic approach or a two‐scale discrete‐continuum micro‐ macro‐scopic approach to granular media.

This paper develops a new discrete particle model to describe granular media in several branches of engineering such as soil mechanics, power technologies or sintering processes.

The main purpose of this paper is to compare the performance of three commonly used global search algorithms, namely tree‐based augmented spatial digital tree, cell‐based no binary search and D‐cell, in the discrete element simulations.

A large number of test cases with up to five million particles/discrete objects are employed to numerically examine the computational costs of the three search algorithms and their performance is compared.

Comprehensive comparisons reveal that the D‐cell is more efficient than the tree‐based search algorithms for large‐scale problems. The parametric study of the D‐cell algorithm itself shows that the performance of the algorithm is strongly dependent on the cell dimension chosen.

The only limitation of the current work is that the tested domain shape is regular, and thus more complex domain shapes may need to be considered.

The paper provides clear guidance regarding the possible actual computational performance of the tested search algorithms for practical applications.

The purpose of this paper is to establish a new two-phase Discrete Element Method (DEM) model to investigate the movement of fresh concrete which consists of mortar and aggregate. The established DEM model was adopted to simulate the mixing process of fresh concrete based on the commercial software package PFC3D. The trajectories of particles and particle clusters were recorded to analyze the mixing behavior from different scales. On one hand, the macro-scale movement was obtained to make the mixing process visualization. On the other hand, the relative micro movement of the single particle and particle clusters was also monitored to further study the mixing mechanism of the fresh concrete.

A new two-phase DEM model was designed to simulate the movement of fresh concrete which consists of mortar and aggregate. The linear-spring dashpot model was used to model all the contacts between particle and particle/wall to characterize the viscidity of fresh concrete. Moreover, two sets of parallel bond models were employed to characterize the contact between the mortar particles and mortar/coarse aggregate particles, namely the pbond1 and pbond2. The hybrid treatment enables the current DEM model to handle the yield behavior.

The mixing process of fresh concrete is mainly composed by the transportation in the x-direction and the overturn and fall off in the y- and z-directions. With these movements in different directions, the concrete particles can be fully mixed in the mixing drum.

A new two-phase DEM model was proposed and used to simulate the mixing process of fresh concrete. The outcomes of the simulation would be helpful for making the transporting truck visualization and the movement behavior of fresh concrete observable. The model can provide dynamic information of particles to reveal the interaction mechanism of fresh concrete in the truck mixer which is extremely difficult to obtain on-line in physical experiments or building site.

Sand production is a challenging issue during hydrocarbon production in the oil and gas industry. This paper aims to investigate one sand production process, i.e. transient sand production, using a novel bonded particle lattice Boltzmann method. This mesoscopic technique provides a unique insight into complicated sand erosion process during oil exploitation.

The mesoscopic fluid-particle coupling is directly approached by the immersed moving boundary method in the framework of lattice Boltzmann method. Bonded particle method is used for resolving the deformation of solid. The onset of grain erosion of rocks, which are modelled by a bonded particle model, is realised by breaking the bonds simulating cementation when the tension or tangential force exceeds critical values.

It is proved that the complex fluid–solid interaction occurring at the pore/grain level can be well captured by the immersed moving boundary scheme in the framework of the lattice Boltzmann method. It is found that when the drawdown happens at the wellbore cavity, the tensile failure area appears at the edge of the cavity. Then, the tensile failure area gradually propagates inward, and the solid particles at the tensile failure area become fluidised because of large drag forces. Subsequently, some eroded particles are washed out. This numerical investigation is demonstrated through comparison with the experimental results. In addition, through breaking the cementation, which is simulated by bond models, between bonded particles, the transient particle erosion process is successfully captured.

A novel bonded particle lattice Boltzmann method is used to investigate the sand production problem at the grain level. It is proved that the complex fluid–solid interaction occurring at the pore/grain level can be well captured by the immersed moving boundary scheme in the framework of the lattice Boltzmann method. Through breaking the cementation, which is simulated by bond models, between bonded particles, the transient particle erosion process is successfully captured.

The purpose of this paper is to find two iterative methods to solve the general coupled matrix equations over the generalized centro‐symmetric and central antisymmetric matrices.

By extending the idea of conjugate gradient (CG) method, the authors present two iterative methods to solve the general coupled matrix equations over the generalized centro‐symmetric and central antisymmetric matrices.

When the general coupled matrix equations are consistent over the generalized centro‐symmetric and central anti‐symmetric matrices, the generalized centro‐symmetric and central anti‐symmetric solutions can be obtained within nite iterative steps. Also the least Frobenius norm generalized centrosymmetric and central anti‐symmetric solutions can be derived by choosing a special kind of initial matrices. Furthermore, the optimal approximation generalized centrosymmetric and central anti‐symmetric solutions to given generalized centro‐symmetric and central anti‐symmetric matrices can be obtained by finding the least Frobenius norm generalized centro‐symmetric and central anti‐symmetric solutions of new matrix equations. The authors employ some numerical examples to support the theoretical results of this paper. Finally, the application of the presented methods is highlighted for solving the projected generalized continuous‐time algebraic Lyapunov equations (GCALE).

By the algorithms, the solvability of the general coupled matrix equations over generalized centro‐symmetric and central anti‐symmetric matrices can be determined automatically. The convergence results of the iterative algorithms are also proposed. Several examples and an application are given to show the efficiency of the presented methods.

Contact detection for convex polygons/polyhedra has been a critical issue in discrete/discontinuous modelling, such as the discrete element method (DEM) and the discontinuous deformation analysis (DDA). The recently developed 3D contact theory for polyhedra in DDA depends on the so-called entrance block of two polyhedra and reduces the contact to evaluate the distance between the reference point to the corresponding entrance block, but effective implementation is still lacking.

In this paper, the equivalence of the entrance block and the Minkowski difference of two polyhedra is emphasised and two well-known Minkowski difference-based contact detection and overlap computation algorithms, GJK and expanding polytope algorithm (EPA), are chosen as the possible numerical approaches to the 3D contact theory for DDA, and also as alternatives for computing polyhedral contact features in DEM. The key algorithmic issues are outlined and their important features are highlighted.

Numerical examples indicate that the average number of updates required in GJK for polyhedral contact is around 6, and only 1 or 2 iterations are needed in EPA to find the overlap and all the relevant contact features when the overlap between polyhedra is small.

The equivalence of the entrance block in DDA and the Minkowski difference of two polyhedra is emphasised; GJK- and EPA-based contact algorithms are applied to convex polyhedra in DEM; energy conservation is guaranteed for the contact theory used; and numerical results demonstrate the effectiveness of the proposed methodologies.

The purpose of this paper is to investigate the effect of four controllable parameters (fuel mixture, evaporation bubble point temperature, expander inlet temperature and condensation dew point temperature) of a solar-driven organic Rankine cycle (ORC) on the first-law efficiency, the exergetic efficiency, the exergy destruction and the volume flow ratio (expander outlet/expander inlet).

Nine experiments as per Taguchi’s standard L9 orthogonal array were performed on the solar-driven ORC. Subsequently, multi-response optimization was performed using grey relational and principal component analyses.

The results revealed that the grey relational analysis along with the principal component analysis is a simple as well as effective method for solving the multi-response optimization problem and it provides the optimal combination of the solar-driven ORC parameters. Further, the analysis of variance was also employed to identify the most significant parameter based on the percentage of contribution of each cyclic parameter. Confirmation tests were performed to check the validity of the results which revealed good agreement between predicted and experimental values of the response variables at optimum combination of the input parameters. The optimal combination of process parameters is the set with A3 (the best fuel mixture in the context of optimal performance is 0.9 percent butane and 0.1 percent pentane by weight), B2 (evaporation bubble point temperature=358 K), C1 (condensation dew point temperature=300 K) and D3 (expander inlet temperature=370 K).

In this research, the Taguchi-based grey relational analysis coupled with the principal components analysis has been successfully carried out, whereas for any optimized solution, it is required to have a real-time scenario that may be taken into consideration by the application of different soft computing techniques like genetic algorithm, simulated annealing, etc. The results generated are purely based on theoretical modeling, and, for further research, experimental analyses are required to consolidate the generated results.

This piece of research work will be helpful to users of solar energy, academicians, researchers and other concerned persons, in understanding the importance, severity and benefits obtained by the application, implementation and optimization of the cyclic parameters of the solar-driven ORC.