Engineering with Computers最新文献

Untangling flow and mass transport in aquifers is essential for effective water management and protection. However, understanding the mechanisms underlying such phenomena is challenging, particularly in highly heterogeneous natural aquifers. Past research has been limited by the lack of dense data series and experimental models that provide precise knowledge of such aquifer characteristics. To bridge this gap and advance our current understanding, we present the findings of a pioneering experimental investigation that characterizes a unique, strongly heterogeneous, laboratory-constructed phreatic aquifer at an intermediate scale under radial flow conditions. This strong heterogeneity was achieved by randomly distributing 2527 cells across 7 layers, each filled with one of 12 different soil mixtures, with their textural characteristics, porosity, and saturated hydraulic conductivity measured in the laboratory. We placed 37 fully penetrating piezometers radially at varying distances from the central pumping well, allowing for an extensive pumping test campaign to obtain saturated hydraulic conductivity values for each piezometer location and scaling laws along eight directions. Results reveal that the aquifer’s strong heterogeneity led to significant vertical and directional anisotropy in saturated hydraulic conductivity. Furthermore, we experimentally demonstrated for the first time that the porous medium tends toward homogeneity when transitioning from the scale of heterogeneity to the scale of investigation. These novel findings, obtained on a uniquely highly heterogeneous aquifer, contribute to the field and provide valuable insights for researchers studying flow and mass transport phenomena. The comprehensive dataset obtained will serve as a foundation for future research and as a tool to validate findings from previous studies on strongly heterogeneous aquifers.

This paper presents a novel and effective strategy for modelling three-dimensional periodic representative volume elements (RVE) of particulate composites. The proposed method aims to generate an RVE that can represent the microstructure of particulate composites with hollow spherical inclusions for homogenization (e.g., deriving the full-field effective elastic properties). The RVE features periodic and randomised geometry suitable for the application of periodic boundary conditions in finite element analysis. A robust algorithm is introduced following the combined theories of Monte Carlo and collision driven molecular dynamics to pack spherical particles in random spatial positions within the RVE. This novel technique can achieve a high particle-matrix volume ratio of up to 50% while still maintaining geometric periodicity across the domain and random distribution of inclusions within the RVE. Another algorithm is established to apply periodic boundary conditions (PBC) to precisely generate full field elastic properties of such microstructures. Furthermore, a user-friendly automatic ABAQUS CAE plug-in tool ‘Gen_PRVE’ is developed to generate three-dimensional RVE of any spherical particulate composite or porous material. Gen_PRVE provides users with a great deal of flexibility to generate Representative Volume Elements (RVEs) with varying side dimensions, sphere sizes, and periodic mesh resolutions. In addition, this tool can be effectively utilized to conduct a rapid mesh convergence study, an RVE size sensitivity study, and investigate the impact of inclusion/matrix volume fraction on the solution. Lastly, examples of these applications are presented.

Mesh adaptivity is a technique to provide detail in numerical solutions without the need to refine the mesh over the whole domain. Mesh adaptivity in isogeometric analysis can be driven by Truncated Hierarchical B-splines (THB-splines) which add degrees of freedom locally based on finer B-spline bases. Labeling of elements for refinement is typically done using residual-based error estimators. In this paper, an adaptive meshing workflow for isogeometric Kirchhoff–Love shell analysis is developed. This framework includes THB-splines, mesh admissibility for combined refinement and coarsening and the Dual-Weighted Residual (DWR) method for computing element-wise error contributions. The DWR can be used in several structural analysis problems, allowing the user to specify a goal quantity of interest which is used to mark elements and refine the mesh. This goal functional can involve, for example, displacements, stresses, eigenfrequencies etc. The proposed framework is evaluated through a set of different benchmark problems, including modal analysis, buckling analysis and non-linear snap-through and bifurcation problems, showing high accuracy of the DWR estimator and efficient allocation of degrees of freedom for advanced shell computations.

This paper introduces the OxCM contour method solver, a console application structured based on the legacy version of the FEniCS open-source computing platform for solving partial differential equations (PDEs) using the finite element method (FEM). The solver provides a standardized approach to solving linear elastic numerical models, calculating residual stresses corresponding to measured displacements resulting from changes in the boundary conditions after minimally disturbing (non-contact) cutting. This is achieved through a single-line command, specifically in the case of availability of a domain composed of a tetrahedral mesh and experimentally collected and processed profilometry data. The solver is structured according to a static boundary condition rule, allowing it to rely solely on the cross-section occupied by the experimental data, independent of the geometric irregularities of the investigated body. This approach eliminates the need to create realistic finite element domains for complex-shaped, discontinuous processing bodies. While the contour method provides highly accurate quantification of residual stresses in parts with continuously processed properties, real scenarios often involve parts subjected to discontinuous processing and geometric irregularities. The solver’s validation is performed through numerical experiments representing both continuous and discontinuous processing conditions in artificially created domains with regular and irregular geometric features based on the eigenstrain theory. Numerical experiments, free from experimental errors, contribute to a novel understanding of the contour method's capabilities in reconstructing residual stresses in such bodies through a detailed error analysis. Furthermore, the application of the OxCM contour method solver in a real-case scenario involving a nickel-based superalloy finite-length weldment is demonstrated. The results exhibit the expected distribution of the longitudinal component of residual stresses along the long-transverse direction, consistent with the solution of a commercial solver that was validated by neutron diffraction strain scanning.

This work focuses on the coupling of trimmed shell patches using Isogeometric Analysis, based on higher continuity splines that seamlessly meet the (C^1) requirement of Kirchhoff–Love-based discretizations. Weak enforcement of coupling conditions is achieved through the symmetric interior penalty method, where the fluxes are computed using their correct variationally consistent expression that was only recently proposed and is unprecedentedly adopted herein in the context of coupling conditions. The constitutive relationship accounts for generically laminated materials, although the proposed tests are conducted under the assumption of uniform thickness and lamination sequence. Numerical experiments assess the method for an isotropic and a laminated plate, as well as an isotropic hyperbolic paraboloid shell from the new shell obstacle course. The boundary conditions and domain force are chosen to reproduce manufactured analytical solutions, which are taken as reference to compute rigorous convergence curves in the (L^2), (H^1), and (H^2) norms, that closely approach optimal ones predicted by theory. Additionally, we conduct a final test on a complex structure comprising five intersecting laminated cylindrical shells, whose geometry is directly imported from a STEP file. The results exhibit excellent agreement with those obtained through commercial software, showcasing the method’s potential for real-world industrial applications.

Loaded shell structures may deform, rotate, and crack, leading to fracture. The traditional finite element method describes material internal forces through differential equations, posing challenges in handling discontinuities and complicating fracture problem resolution. Peridynamics (PD), employing integral equations, presents advantages for fracture analysis. However, as a non-local theory, PD requires discretizing materials into nodes and establishing interactions through bonds, leading to reduce computational efficiency. This study introduces a GPU-based parallel PD algorithm for large deformation problems in shell structures within the compute unified device architecture (CUDA) framework. The algorithm incorporates element mapping and bond mapping for high parallelism. The algorithm optimizes data structures and GPU memory usage for efficient parallel computing. The parallel computing capabilities of GPU expedite crack analysis simulations, greatly reducing the time required to address large deformation problems. Experimental tests confirm the algorithm’s accuracy, efficiency, and value for engineering applications, demonstrating its potential to advance fracture analysis in shell structures.

This study introduces an innovative dynamic infinite meshfree method for robust and efficient solutions to half-space problems. This approach seamlessly couples this method with the nodal integral reproducing kernel particle method to discretize half-spaces defined by an artificial boundary. The infinite meshfree shape function is uniquely constructed using the 1D reproducing kernel shape function combined with the boundary singular kernel method, ensuring the Kronecker delta property on artificial boundaries. Coupled with the wave-transfer function, the proposed approach models dissipation actions effectively. The infinite domain simulation employs the dummy node method, enhanced by Newton–Cotes integrals. To ensure solution stability and convergence, our approach is based on the Galerkin weak form of the domain integral method. To combat the challenges of instability and imprecision, we integrated the stabilized conforming nodal integration method and the naturally stable nodal integration. The proposed methods efficacy is validated through various benchmark problems, with preliminary results showcasing superior precision and stability.

Deep learning is a powerful tool for solving data driven differential problems and has come out to have successful applications in solving direct and inverse problems described by PDEs, even in presence of integral terms. In this paper, we propose to apply radial basis functions (RBFs) as activation functions in suitably designed Physics Informed Neural Networks (PINNs) to solve the inverse problem of computing the perydinamic kernel in the nonlocal formulation of classical wave equation, resulting in what we call RBF-iPINN. We show that the selection of an RBF is necessary to achieve meaningful solutions, that agree with the physical expectations carried by the data. We support our results with numerical examples and experiments, comparing the solution obtained with the proposed RBF-iPINN to the exact solutions.