Hybrid Cellular Automaton Method Research Articles

A Harmonic Response Topology Optimization Method Based on Hybrid Cellular Automata

Abstract Hybrid cellular automaton (HCA) method is a topology optimization method with high convergence efficiency. Harmonic response topology optimization problem has been widely researched and common frequency-domain methods have been applied to solve this problem. Despite this, little work has so far been undertaken to utilize the HCA method to improve the calculation efficiency of harmonic response topology optimization. In this article, we present a methodology that applies the HCA method to solve harmonic response topology optimization problem. Mode displacement method (MDM), mode acceleration method (MAM), and full method (FM) are common frequency-domain methods that are utilized as harmonic response analysis methods in this study. The examples under rotating loads demonstrate that feasibility of this methodology at one specific frequency excitation and multiple frequencies excitation. This article presents and implements a high convergence efficiency method for harmonic response topology optimization, and this method can converge in 20–30 iterations. This method can extend the application range of the HCA method and improve the optimization efficiency of harmonic response topology optimization.

Multi-objective topology optimisation design of surface-based lattice structures for energy absorption capacity

The article proposes a multi-objective optimisation method based on Triply Periodic Minimal Surface (TPMS) lattice structures to meet the requirements of stiffness and energy absorption capacity. A bilinear material model is used to predict mechanical properties of lattice elements for optimisation with higher efficiency and accuracy. Considering the multi objective characteristics of optimisation, the Hybrid Cellular Automaton method (HCA) is modified by introducing equivalent loads and weight parameter, without multiple dynamic analyses. To further improve the structural performances, the Conformal Lattice Structures (CLS) are filled in the boundaries of structures based on the CLS construction technique where a strategy of inverse-mapping is proposed. Furthermore, a post-processing method is raised to eliminate the discontinuity of elements’ connection areas for manufacting. The simulation results indicate that the optimised structures achieve a combination of stiffness and energy absorption capacity, and the specimen is manufactured by 3D printing, exposing the feasibility.

3G-optimization of multi-cell crash box cross-section of autobody based on crashworthiness

The cross-section, thickness, and material of the autobody structure determine the crashworthiness and lightweight level. Different from the variables in traditional autobody design that are considered separately, the basic theory of 3G-optimization is to simultaneously consider geometric shape (Geometry), the thickness of structure (Gauge), and material grade (Grade) in structural optimization design, which is conducive to maximizing the lightweight potential of the structure. This paper presents a cross-section optimization method for multi-cell thin-walled structures based on 3G-optimization, which is used in the structural design of crash box. Based on full width frontal collision condition, the cross-section shape, thickness, and material variables of the multi-cell crash box are optimized simultaneously. Multiple sets of optimization schemes show obvious weight reduction effect while ensuring safety. Besides, the sub-system decoupling method and hybrid cellular automaton (HCA) method are applied to 3G-optimization process, which is beneficial to improve the calculation efficiency and provide a theoretical basis for the definition of the initial design space for 3G-optimization.

Topology optimization design of three-dimensional multi-material and multi-body structure based on irregular cellular hybrid cellular automata method

In recent years, Hybrid Cellular Automata Method (HCAM) has been successfully applied to solve structural topology optimization problems. However, there was no report on HCAM research of three-dimensional composite structure composed of multiple materials and multiple bodies. Therefore, in this paper, three-dimensional non-cube cells of irregular size (such as tetrahedral cells with adaptive changes inside length) and Finite Element Method (FEM) are introduced to extend HCAM, which is better and more flexibly to fit complex geometric shapes. Furthermore, a better structure configuration of multi-material and multi-body structure is obtained. The typical example study showed that the proposed topology optimization method could effectively remove the redundant materials of multi-material and multi-body structure, and the optimized structure configuration could still meet the requirements of the original condition after geometric reconstructed. Thus it provided a reference for the intelligent design of other products.

Multi-objective optimization of crashworthiness of vehicle front longitudinal beam

Front longitudinal beam (FLB) is an important structure for the analysis of force transmission and energy absorption path in different crashing scenarios. In the present paper, the finite element (FE) model of a full-scale vehicle yun-100 Zotye is employed to explore the energy absorption of FLB, and aiming at its poor energy absorption problem, circular beam was used as the original topology optimization space of FLB. The advantages of both static and dynamic topology optimization methods are fully considered, and a variable density method is combined with a hybrid cellular automaton (HCA) method. The substructure dissipated energy and force for frontal crash in a full-scale vehicle are obtained at a speed of 13.8 m/s. The maximum stiffness in axial is obtained through the static topology optimization method and the maximum energy-absorbing structure of FLB which is satisfied with axial strength obtained through the dynamic topology optimization method. According to the results of topology optimization, a multi-cell thin-walled structure is interpreted as the novel FLB. A parametric study on geometric parameters is also performed to explore their effects on crashing characteristics of novel FLB, and it is found that they significantly influenced the crashworthiness of multi-cell thin-walled structure (especially the absorption of energy). Furthermore, in order to maximize the characteristics of novel FLB, a multi-objective optimization process is carried out using non-dominated sorting genetic algorithm (NSGA-II). The optimized FLB after multi-objective optimization is applied to Zotye of 100% vehicle frontal crash. The results showed that the peak value of acceleration decreased by 10.3% and the mass of the optimized FLB reduced to 0.59 kg. It indicated that the optimized FLB manifested excellent crashworthiness and better protective characteristics.

Microscopic mechanical model of the main structural element of Bazhenov Suite reservoir rocks

We propose a microscale model of the main structural element (“bearing” layers) of kerogen-clay-carbonate-siliceous rocks of the Bazhenov formation. The model treats the rock as a composite material with inorganic clay matrix and different content of organic inclusions (up to 25%) and micropores filled with low-viscous fluid (light hydrocarbon fractions). A computer simulation of the mechanical behavior of representative samples of structural elements of the studied rock under triaxial compression was carried out using the hybrid cellular automaton method and a coupled mechanical model that takes into account the mutual influence of porous rock deformation and filtration of a pore fluid. It is shown that the mechanical behavior of the “bearing” layer of rock at side pressures that meet the characteristic conditions of occurrence is satisfactorily described by rock plasticity models with two-parameter flow functions.

Research on Thermal Topology Design Method of Spindle Based on HCAM

Spindle thermal error is one of the key factors in the machining accuracy of CNC machine tool. In order to reduce the thermal error of the spindle and improve the machining precision of the CNC machine tool, the idea of the thermal topology design based on the hybrid cellular automaton method (HCAM) is proposed. In this paper, the existing research results of hybrid cellular automaton are summarized, and the main achievements of domestic and foreign research work are analysed and reviewed from the aspects of structural topology optimization. Finally, the realization and prospect of HCAM self-optimizing thermal topology design method for spindle are presented.

Simulation of Deformation and Fracture of Fluid-saturated Porous Media with Hybrid Cellular Automaton Method

In the paper we propose the method of numerical simulation of fluid-saturated porous media, that represents the combination of particle method and finite-difference method, namely hybrid cellular automaton method. It allows explicit taking into the account inelastic deformation, dilation and fracture of solid skeleton as well as the influence of pore pressure on the stress state of the skeleton and the redistribution of a fluid in filtration volume of porous medium. We applied the method to study the influence of viscous compressible liquid in pores of material to its strength and fracture. It has been shown that the influence of the liquid in pores significantly depends on elastic-plastic properties of material of solid skeleton.

Sewer Networks Optimization Using Cellular Automata

The Hybrid Cellular Automata (HCA) method is used in this paper for the optimal design of sewer network problems with the fixed layout. The HCA method decomposes the problem into two sub-problems with considering the pipe diameters and nodal cover depths as decision variables. Two stages are solved iteratively for determining the decision variables in a manner to minimize the total cost of the sewer network subject to the operational constraints. The HCA method is used to optimally solve three benchmark examples with different sizes and the results are presented and compared to those of the existing methods. The results indicate that the HCA method is more efficient and effective than the alternative methods.

Topology Optimization of Thermo-Mechanical Structure Using the Hybrid Celluar Automata Method

Topology optimization of thermo-elastic structures using the hybrid cellular automata method is investigated in this paper. The objective is to minimize the mean compliance of a structure with a single material volume constraint. The hybrid cellular automata method is used to solve the optimization problem. The local change in the design variable is determined by a local rule based on the proportional control law. The numerical example is presented to show the feasibility of the present approach.

Hybrid cellular automata method. Application to research on mechanical response of contrast media

In the work, a hybrid cellular automata method was developed to study behavioral peculiarities of heterogeneous materials and contrast media. The method is a combination of two approaches: classical and movable cellular automata methods. The method was verified through comparing simulation data on sorption of carbon dioxide in lignite and corresponding experimental data provided by researchers from Velenje Lignite Mine (Slovenia). The obtained estimates of model parameters were used in numerical simulation of the gas phase on the strength and fracture of lignite samples. It is shown that the presence of the gaseous atmosphere even of pressure 0.1 MPa changes the effective strength of the lignite sample and the character of their fracture. The developed method can be used to study behavioral peculiarities of complex multicomponent media such as coal beds in mine zones.

Two-material optimization of plate armour for blast mitigation using hybrid cellular automata

With the increased use of improvised explosive devices in regions at war, the threat to military and civilian life has risen. Cabin penetration and gross acceleration are the primary threats in an explosive event. Cabin penetration crushes occupants, damaging the lower body. Acceleration causes death at high magnitudes. This investigation develops a process of designing armour that simultaneously mitigates cabin penetration and acceleration. The hybrid cellular automaton (HCA) method of topology optimization has proven efficient and robust in problems involving large, plastic deformations such as crash impact. Here HCA is extended to the design of armour under blast loading. The ability to distribute two metallic phases, as opposed to one material and void, is also added. The blast wave energy transforms on impact into internal energy (IE) inside the solid medium. Maximum attenuation occurs with maximized IE. The resulting structures show HCA's potential for designing blast mitigating armour structures.

Topometry optimisation for crashworthiness design using hybrid cellular automata

An objective in crashworthiness design is to obtain energy-absorbing components. This task has been efficiently undertaken using the Hybrid Cellular Automaton method. This method combines the CA paradigm with nonlinear, dynamic finite element analysis. Lightweight, energy-absorbing topology concepts have been obtained with this approach. This paper furthers the development of the HCA method to an efficient tool for synthesising shell structures using topometry optimisation. The objective is to find the thickness distribution that uniformly distributes the structure’s internal energy density. This approach addresses problems involving collisions, large displacement and material plastic hardening. The final designs meet manufacturing and performance constraints.

Comparative Study of Topology Optimization Techniques

This paper presents a comparison between three continuum-based topology optimization methods: the hybrid cellular automaton method, the optimality criteria method, and the method of moving asymptotes. The purpose of the study is to highlight the differences between the three. The optimality criteria method and the method of moving asymptotes are well established in topology optimization. The hybrid cellular automaton method is a recently developed gradient-free technique that combines both local design rules based on the cellular automaton paradigm and the finite element analysis. The closed-loop controllers used in the hybrid cellular automaton method are used to modify the mass distribution in the design domain to find an optimum material layout. The hybrid cellular automaton and optimality criteria methods and the method of moving asymptotes are described and applied in a comparative study to three sample problems. The influence of different algorithm control parameters is shown in this work. The paper demonstrates that, for the sample problems presented, the hybrid cellular automaton method generally required the fewest number of iterations to converge to a solution compared with the optimality criteria method and the method of moving asymptotes. The final topologies generated using the hybrid cellular automaton method typically had the lowest compliance and exhibited the fewest number of intermediate densities at the solution.

Optimality Conditions of the Hybrid Cellular Automata for Structural Optimization

The hybrid cellular automaton method has been successfully applied to topology optimization using a uniform strain energy density distribution approach. In this work, a new set of design rules is derived from the first-order optimality conditions of a multi-objective problem. In this new formulation, the final topology is derived to minimize both mass and strain energy. In the hybrid cellular automaton algorithm, local design rules based on the cellular automaton paradigm are used to efficiently drive the design to optimality. In addition to the control-based techniques previously introduced, a new ratio technique is derived in this investigation. This work also compares the performance of the control strategies and the ratio technique.

Topology Optimization Using a Hybrid Cellular Automaton Method With Local Control Rules

The hybrid cellular automaton (HCA) algorithm is a methodology developed to simulate the process of structural adaptation in bones. This methodology incorporates a distributed control loop within a structure in which ideally localized sensor cells activate local processes of the formation and resorption of material. With a proper control strategy, this process drives the overall structure to an optimal configuration. The controllers developed in this investigation include two-position, proportional, integral and derivative strategies. The HCA algorithm combines elements of the cellular automaton (CA) paradigm with finite element analysis (FEA). This methodology has proved to be computationally efficient to solve topology optimization problems. The resulting optimal structures are free of numerical instabilities such as the checkerboarding effect. This investigation presents the main features of the HCA algorithm and the influence of different parameters applied during the iterative optimization process.