Engineering with Computers

a posteriori local mesh improvement procedure is used. The performance of the algorithm is evaluated by application to a number of realistically complex, cracked geometries.

The 3D chiral-type auxetic metamaterials have attracted massive attention in both academia and engineering. However, the complex deformation mechanism makes this kind of metamaterial hard to be topologically devised, especially in the 3D scenario. Most of existed studies only dealt with the re-entrant auxetics, and the optimized results are not able to be fabricated directly. This paper proposes a topology optimization design method for the 3D chiral-type auxetic metamaterial with ready-to-manufacture features. In this method, the matrix-compressed parametric level set is used to implicitly describe the high-resolution design boundary for the auxetic. In particular, the Gaussian radial basis function with global support is employed to parameterize the level set, and a discrete wavelet transform scheme is incorporated into the parametrization framework to effectively compress the full interpolation matrix. In this way, the optimization cost in 3D is noticeably reduced under a high numerical accuracy. To induce rotational deformation, rotation symmetry is applied to the micro-structured unit cell. The optimized microstructures possess explicit and smooth boundaries, and thus they can be 3D printed without tedious post-processing. Several 3D metallic microstructures with different Poisson’s ratios are numerically optimized and then fabricated using selective laser sintering. Practical Poisson's ratios of the samples are evaluated by conducting simulation and compression experiments. The tested Poisson's ratios by the compression experiment match the numerical estimation of the proposed method in a high consistency, which demonstrates the advances of our design method for creating reliable auxetic microstructures for 3D printing. The failure test is also implemented on different microstructures. It is concluded that the devised chiral metamaterial exhibits a great ability to absorb external deformation energy.

The mechanism of dam safety monitoring model is analyzed; for the dam system comprehensive affected by multi-factor, the mapping relationship between the influence factors and the dam behavior effects domain is usually nonlinear. Synthesizing each kind of factor, 27 parameters are chosen as the main factors which affect the accuracy of the monitoring model. Taking the actual monitoring data as the evaluation factor, the dam safety monitoring model based on the random forest (RF) intelligent algorithm was built with the actual monitoring data to predict uplift pressure. At the same time, test the significance of each variable based on the RF monitoring model and calculate the importance degree of each variable for the model through the importance function. It is indicated that RF model can be relatively fast and accurately predict the uplift pressure of the dam according to the influence factors. The average prediction accuracy is more than 95%. As compared with other intelligent algorithms such as support vector machine, RF has better robustness, higher prediction accuracy, and faster convergence speed. Because of the uniformity of the calculation procedure and the universality of the prediction method, the RF model also has reasonable extrapolation for other dam safety monitoring models (such as crack opening and seepage discharge). Significance test results obtained by the two methods have shown that the impact of reservoir water level and daily rainfall on the uplift pressure is significant, and other factors’ impact on dam deformation is unstable and changes with the external environmental influence.

This paper presents a method for the interactive analysis design of planar steel trusses. Given an initial feasible design, that is, a design that satisfies stress and displacement performance conditions, and fabrication conditions, a parametric analysis is used to identify the extent to which one or two members can be redesigned while still satisfying design feasibility. The parametric analysis is obtained from the solution of a parametric Hessian quadratic programming problem (PHQP). The analysisdesign methodology is demonstrated with a three member truss.

The neighborhood problem appears in many applications of computational geometry, computational mechanics, etc. In all these situations, the main requirement for a competitive implementation is performance, which can only be attained in modern hardware by exploiting parallelism. However, whereas the performance of serial algorithms is fairly predictable, that of parallel methods depends on delicate issues that have a huge impact (cache memory, cache misses, memory alignment, etc.), but are not easy to control. Even if there is not a simple approach to deal with these factors in shared-memory architectures, it is quite convenient to program parallel algorithms where the data are segregated on a per-thread basis. With this objective in mind, we propose a strategy to develop parallel algorithms based on a two-level design, and apply it to efficiently solve the nearest neighborhood problem. At a higher level, the proposed methods orchestrate the parallel algorithm and split the space into cells stored in a hash table; at the lower level, our methods hold serial search algorithms that are completely agnostic to the high-level counterpart. Using this strategy, we have developed a library combining different serial and parallel algorithms, optimized them, and assessed their performance. The analysis carried out allows to better understand the main bottlenecks in the algorithmic solution of the nearest neighborhood problem and come out with very fast implementations that improve existing available software.

The main objective in this paper is to propose an efficient numerical formulation for solving the time-fractional distributed-order advection–diffusion equation. First, the distributed-order term has been approximated by the Gauss quadrature rule. In the next, a finite difference approach is applied to approximate the temporal variable with convergence order $$\mathcal{O}(\tau ^{2-\alpha })$$ as $$0<\alpha <1$$ . Finally, to discrete the spacial dimension, an upwind local radial basis function-finite difference idea has been employed. In the numerical investigation, the effect of the advection coefficient has been studied in terms of accuracy and stability of the proposed difference scheme. At the end, two examples are studied to approve the impact and ability of the numerical procedure.

Classification systems such as rock mass rating (RMR) are used to evaluate rock mass quality. This paper intended to evaluate RMR based on a fuzzy clustering algorithm to improve linguistic and empirical criteria for the RMR classification system. In the proposed algorithm, membership functions were first extracted for each RMR parameter based on the questionnaires filled out by experts. RMR clustering algorithm was determined by considering the percent importance of each parameter in the RMR classification system. In all implementation stages of the proposed algorithm, no empirical judgment was made in determining the classification classes in the RMR system. According to the obtained results, the proposed algorithm is a powerful tool to modify the rock mass rating system and can be generalized for future research.

Assembly free FEM bypasses the assembly step and solves the system of linear equations at the element level using Conjugate Gradient (CG) type iterative solver. The smaller dense Matrix-vector Products (MvPs) are encapsulated within the CG solver and are computed either at element level or degree of freedom (DoF) level. Both these strategies exploit the computing power of GPU effectively, but the performance is lagging due to the uncoalesced global memory access on GPU. This paper proposes an improved MvP strategy in assembly free FEM, which improves the performance by coalesced global memory access using on-chip faster shared memory and using the texture cache memory on GPU. Since GPU has limited shared memory (in few KBs), the proposed technique suffers from a problem known as low occupancy. Despite the low occupancy issue, the proposed strategy outperforms both element based and DoF based MvP strategies on GPU. Numerical experiments compared with element level and DoF level strategies on GPU and found that, GPU instance of proposed MvP outperforms both strategies approximately by factor of 7 and 1.5 respectively.

We present a new method to construct a trivariate T-spline representation of complex solids for the application of isogeometric analysis. We take a genus-zero solid as a basis of our study, but at the end of the work we explain the way to generalize the results to any genus solids. The proposed technique only demands a surface triangulation of the solid as input data. The key of this method lies in obtaining a volumetric parameterization between the solid and the parametric domain, the unitary cube. To do that, an adaptive tetrahedral mesh of the parametric domain is isomorphically transformed onto the solid by applying a mesh untangling and smoothing procedure. The control points of the trivariate T-spline are calculated by imposing the interpolation conditions on points sited both on the inner and on the surface of the solid. The distribution of the interpolating points is adapted to the singularities of the domain to preserve the features of the surface triangulation. We present some results of the application of isogeometric analysis with T-splines to the resolution of Poisson equation in solids parameterized with this technique.