The advancement in high-order computational methods is reshaping the landscape of mesh generation in Computational Fluid Dynamics (CFD), steering the focus towards curvilinear mesh techniques to meet the escalating accuracy demands. Gridder-HO, the software designed to generate high-order curvilinear mesh efficiently and rapidly, has been developed. Gridder-HO supports the elevation of meshes to P2 (quadratic-order) or P3 (cubic-order). It features a layered architecture and utilizes the concurrent hash table and the Alternating Digital Tree (ADT) data structure, supporting thread-level parallelism to convert straight-edge mesh into high-order curvilinear mesh seamlessly. Gridder-HO utilizes the projection method based on a thread pool to precisely preserve geometry, and employs a novel localized RBF method with ADT for volume node interpolation to untangle the mesh, which aims to achieve a satisfactory balance between efficiency and accuracy. Validated through CFD simulations using the GPU-accelerated Python Flux Reconstruction (PyFR) solver, the practicality of Gridder-HO is demonstrated across various Reynolds numbers in typical cases such as sphere, cylinder, and SD7003 airfoil. These results confirm the high-order curvilinear meshes generated by Gridder-HO meet the high-order requirements of emerging computational methods. Moreover, Gridder-HO exemplifies its effectiveness in generating large-scale, high-order curvilinear meshes for the DLR-F6 transport aircraft configuration standard test cases. It elevates a mesh with 5 million elements to P2 in 3 min 39 sec at 68% parallel efficiency on 16 threads, and another with 14 million elements to P3 in 52 min 39 sec at 60% efficiency, illustrating its efficiency and potential in satisfying the demands of complex geometries in engineering applications.

Enhancing nuclear power plant (NPP) safety is demanded because of the recent beyond-design-basis earthquake near a NPP. Therefore, research on improving the seismic performance of the electrical cabinet, which ensures the safe operation of NPPs, is needed. In this paper, a tuned mass damper (TMD) is employed to control the seismic response of cabinet. To design the TMD, we employ existing design equations or perform numerical model–based optimization. However, limitations, such as inconsistencies with targeted control of the load and structure, the possibility of converging a local solution, and the high cost of numerical analysis. Therefore, this paper proposes a two-step machine learning and optimization method. Such an approach is utilized to find the optimal global design solution and reduce numerical analysis costs. Each step involves the design of experiment (DOE), response surface, and optimization. Notably, range setting in the DOE accounts for the difference between each step. In the first step, the sampling range is widened to determine the relationship between the design variables and the cabinet's response, and in the second step, the sampling range is narrowed depending on the result of the first step. Consequently, the proposed method reduced the cabinet's response by 35.4 % on average and numerical analysis cost declined by 1/3.

The seismic safety of arch dams has long been a focal point of research. Due to the complexity of modeling and computation, analyzing the seismic response of arch dams using traditional finite element methods requires a considerable amount of time. In the event of a sudden earthquake, it is challenging to quickly obtain stress analysis results or conduct a safety assessment. To address these issues, a rapid and automated analysis procedure is proposed in this paper, providing seismic response of arch dams within hours after an earthquake. The procedure includes a pre-processing program, a computing program EACD-3D-2008, and a post-processing program, achieving a fully automated process from generating non-uniform earthquakes to analyzing dam dynamic responses and visualizing computation results. As a case study, the 294.5 m high Xiaowan arch dam in southwest China is analyzed, which is equipped with strong motion instruments that have recorded several small earthquakes. The case study revealed that accounting for the non-uniformity of the earthquake significantly improves simulation results, with maximum principal stresses typically occurring near the dam-foundation rock interface. Additionally, the procedure effectively compensates for missing data, allowing for the successful supplementation of the missing acceleration records. For stronger earthquakes, high-stress regions are clearly displayed in the result visualization, providing an effective reference for safety assessment. The case study validated the accuracy and wide applicability of the procedure, demonstrating its potential to offer valuable insights for similar analyses in various engineering projects.

The existing data indicate that two-thirds of engineering accidents occur during construction among which engineering accidents caused by scaffold collapse account for a large proportion. Due to the complex mechanical behavior of connection and random nature of scaffold system caused by random geometrical imperfection, the reliability of scaffold system is lower than other kinds of building structures. However, the method considering the random geometrical imperfection is limited. To facilitate the analysis of random geometrical imperfection, the original numerical algorithm is proposed based on ANSYS Parametric Design Language. Through proposed method, two types of geometrical imperfections, i.e., the nodal location error and initial curvature can be automatically considered. The randomness in initial curvature includes random magnitude and random direction. The established numerical model is as close to reality as possible and the process of establishing stochastic numerical model can be automatically finished. The only work that needs to be done is to enter the dimensions of the scaffold. Except the propose of numerical algorithm, the objective of this study is to reveal the influence of geometrical imperfection on random distribution of loading capacity of scaffold system under different load conditions. The influence of random geometrical imperfection on probabilistic distribution of loading capacity is systematically investigated. The results indicated that there may be several buckling modes exist and the buckling mode occurred in actual condition is closely related to the random distribution of geometrical imperfection. The load factor of internal post (point 3) is 8 %–12 % larger than that of corner post. The load factor of side post is 4.7 %–7.2 % larger than that of corner post. The ultimate bending capacity Mu has little influence on the loading capacity of scaffold system when the initial bending stiffness ko is small enough.

The aim of this work is modeling processes of field electron emission in strong electromagnetic fields. This problem is relevant for many technical and medical applications. At present time, electrical devices that combine a large value of field, a powerful relativistic effect and an ultra-short time interval of action are in demand. They find their application in the treatment of the surfaces with inorganic, organic and mixed structures. Modeling of such devices encounters certain difficulties due to the complexity of the mathematical description of the emission processes. In this paper, an approach using the method of large smoothed particles in combination with grid calculation of fields based on Maxwell's equations is proposed. The study was carried out within the framework of the problem of calculating the field emission of electrons from the surface of axisymmetric metal cathodes on Cartesian and unstructured curved meshes. To implement the approach, a complex mathematical model, a parallel numerical algorithm and its software realization have been developed. The elaborated software is focused on the use of multiprocessor computing systems with a central architecture. Test calculations confirmed the correctness of the proposed approach and the high efficiency of its software implementation.

This paper presents a user-friendly software to assign spatially distributed material properties to nonlinear finite element models in LS-DYNA using discretized three dimensional random fields and random variables. The purpose of the software is to enable probabilistic analysis frameworks that incorporate results from LS-DYNA simulations with random material properties. The software leverages the existing well-established deterministic formulation of LS-DYNA by utilizing inbuilt material constitutive laws. K-nearest neighbors spatial interpolation and k-means clustering are implemented to streamline the generation and assignment of random fields to parts in LS-DYNA models. The functionality of the software is demonstrated through real-life safety assessments of two marine structural elements composed of steel-reinforced concrete. Analysis results demonstrated the robustness and efficiency of the software where it can be successfully integrated into analysis frameworks to evaluate the safety of structural members.

The classic Kresling origami structure has been widely studied in the past two decades because of its interesting mechanical properties, including compressive-twist coupling deformation and bistability. It is also known that the conical derivative of Kresling origami can achieve a wider range of structural configurations while preserving the bistability of the original design. Moreover, different origami structures exhibit different responses to local geometric or material imperfections which are often inevitable in practical applications. In this study, we utilize the bar-and-hinge model to convert local imperfections to corresponding variations in nodal coordinates and equivalent stiffness values. Subsequently, we examine the response of conical Kresling origami structures to certain local imperfections. It is demonstrated that the effect of geometric imperfections on the folding properties of such structures is more substantial than that of material imperfections. We show that the multistability of conical Kresling origami structures may undergo a radical transformation when the value of the imperfection exceeds a certain threshold. Furthermore, based on responses to local imperfections, a derivative of the conical Kresling origami structure is designed which manifests tristability. This work develops a strategy for the form-finding of origami structures with tunable multistability, and can be generalized to analyze combined results from multiple local imperfections.

Products created by additive manufacturing often have surface imperfections that require post-processing operations to remove extraneous material in order to meet design specifications. The usage of computational fluid dynamics (CFD) simulations to predict material removal rates of components, allows practitioners to optimize the setup and usage of post-processing equipment. However, those without in-depth knowledge of CFD or the related specialized software, require an easy-to-use and cost-effective application to manage the computational workflow. The two specific surface finishing applications investigated here, are, abrasive flow machining (AFM) and robotic stream finishing (RSF). In order to satisfy user requirements, a modular, threaded, fault-tolerant and object-oriented project management application, written with the Python programming language and PyQt6 framework, has been developed to conduct surface finishing-related CFD simulations using OpenFOAM®. The advantages of the proposed software are: 1) the modern PyQt6 framework is used to develop a cross-platform and user-friendly application which employs the model-view class architectural paradigm for data management and its display, 2) step-by-step interactive project workflows have been tailored specifically for AFM and RSF simulations, 3) the developed steady-state viscoelastic flow solver for AFM and continuum-based steady-state dense granular flow solver for RSF, offer advantages over those provided by OpenFOAM® and 4) simulation results have been corroborated by experimental data to assess the improved accuracy of material removal prediction of the current software when compared to other commercial applications.

An adaptive dimension-reduction Chebyshev metamodel (ADC) is proposed to balance the accuracy and efficiency of dimension-reduction Chebyshev metamodels. A univariate dimension-reduction Chebyshev metamodel (UDC) is constructed by the dimension-reduction method and the Chebyshev metamodel. Based on the UDC, the bivariate terms largely impacting the metamodel are selected using an adaptive selection method, and are combined with the UDC to construct the ADC. The ADC has higher accuracy than the UDC because more calculated sample points are added. Compared with the bivariate dimension-reduction Chebyshev metamodel, the ADC needs fewer sample points and has higher efficiency. The result of numerical examples illustrate that ADC has higher accuracy compared with other commonly-used metamodels and is more suitable for approximating high-dimensional complex models.

To address the challenge of establishing and solving mathematical models for engineering structural optimization, a new topological optimization method that integrates load-transfer path theory with the engulfment algorithm is presented in this paper. The presented method applies the load-transfer path theory to identify the main load-bearing areas of the structure and utilizes the principle of concentrating more materials in relatively high-stress regions and fewer materials in relatively low-stress regions. An engulfment algorithm is introduced to optimize the material distribution. A comparative analysis between the presented and variable-density methods revealed that the path-engulfment method enhances the structural stiffness and strength while reducing its mass, confirming its precision and efficacy in structural optimization. The path-engulfment method was implemented on a truck crane frame, resulting in an optimized structure with increased stiffness and strength and reduced mass compared to the original design. Furthermore, this method eliminates the need for establishing and solving complex mathematical models while addressing issues related to checkerboards and gray-scale elements. A smooth boundary approach was introduced by leveraging the engulfment algorithm, enabling the direct application of the optimized structure for manufacturing purposes, particularly in engineering applications.