Superelement Research Articles

Energy absorption characteristics of fractal multi-cell square tubular structures under axial crushing

In this study, a new fractal multi-cell square tube (FMST) based on the fractal design of the Sierpinski carpet is proposed for energy absorption. The dynamic crushing performance and energy absorption characteristics of the FMST are numerically and theoretically investigated. Extensive numerical simulations are carried out for the FMST structures with different fractal orders and masses of the structures. The findings reveal that the specific energy absorption of the 3rd order FMST is significantly higher, exhibiting a remarkable 100 % increase compared to the 0th order FMST. Furthermore, the undulation of the load-carrying capacity of the 3rd order FMST is reduced by up to 88.5 % compared to a conventional square tube, indicating the substantial potential of the FMST for designing highly efficient energy absorbers. Comparative analysis against other hierarchical multi-cell square tubes reported in the literature confirms that the specific energy absorption of the FMST surpasses existing designs. In addition, a theoretical study is presented for the mean crushing force of the proposed FMST, employing the simplified super folding element theory. The theoretical predictions agree well with the numerical results, further validating the effectiveness of the proposed design. This study provides an innovative design of a multi-cell energy absorber with exceptional energy absorption efficiency. The incorporation of fractal principle in the FMST design holds promise for advancing the field of energy absorption, with potential applications in various industries.

In-plane crushing behavior and energy absorption of sponge-inspired lattice structures

Novel energy-absorbing structures were a crucial requirement for the structural crashworthiness design in the automotive and aerospace industries. Inspired by the unique double-diagonal reinforced configuration of deep-sea glass sponge, we proposed a bionic lattice structure (BLS) fabricated by additive manufacturing (AM). In-plane quasi-static compression tests and numerical simulations were conducted on BLS with varying wall thicknesses (t), and two distinct deformation modes were observed: layer-by-layer mode with zero Poisson's ratio (ZPR) and uniform deformation mode with negative Poisson's ratio (NPR). The effects of structural parameters on the crushing behavior of BLS were investigated by numerical method. It was found that BLS with wall thickness (t) of 1.2 mm exhibited better energy absorption performance than 0.45 mm, with the energy absorption (EA), specific energy absorption (SEA), and mean crushing force (Pm) increased by 745.0%, 216.5%, and 744.3%, respectively. The change in crushing mode was caused by the ‘+’ shaped joints changing from buckling to rotation, and the crushing behaviors of BLS could be effectively controlled by adjusting unit size and unit number. Finally, theoretical prediction models were developed using simplified super folding element (SSFE) theory to gain deeper insights into crushing behavior and performance of BLS. The present study provided valuable insights into the in-plane crushing and energy absorption capabilities of BLS. Moreover, it highlighted the potential of the double-diagonal reinforcement design in developing innovative energy-absorbing structures.

Liquefaction-induced large deformation method with automatic time-step mapping and interfacial interpolation improvement: Case study of the San Fernando dam

This study constructed the u-p equation for saturated soil in the meshfree global weak form within the arbitrary Lagrangian-Eulerian (ALE) framework to solve the problem of liquefaction-induced large deformation induced by strong seismic loading. The interpolation improvement in the near-interface zone was achieved using domain truncation optimization and the local nodal refinement algorithm, and the relative error of the shape function was proposed as the judgment criterion for radial basis function (RBF) field variable mapping. Finally, a high precision meshfree liquefaction-induced large deformation method (MFLLDM) with automatic time step mapping and interfacial zone interpolation improvement was established. The MFLLDM achieved the efficient dynamic updating of soil stress state and pore pressure information in space during the deformation process and more accurately depicted the localized large shear deformation characteristics of the soil in the near-interface zone. The proposed method was integrated into a custom-built large-scale finite element method (FEM) computing system (GEODYNA), based on object-oriented and super element program design technology. This enabled the efficient coupled analysis of MFLLDM in the liquefied-induced large deformation zone and FEM in the small deformation zone. Numerical consolidation examples were used to validate the accuracy, convergence, and applicability of the soil elasto-plastic model for MFLLDM. The method was then used to simulate the liquefaction damage of the San Fernando dam, which reproduced the development process of large slip deformation and high-water pressure ratio for the upstream dam slope.

Terramechanics Models for Tracked Vehicle Terrain Interaction Analysis A Review

Efficient manoeuvrability of off-road tracked vehicles such as military tanks and rovers is essential in ensuring the success of military/extra-terrestrial operations. To achieve this, in-depth research on vehicle-terrain interaction is crucial. This manuscript deals with reviewing the ways to study terramechanics viz. theoretical, empirical, and field tests, and proposing the merits and demerits of each method. Under the theoretical approach, empirical, numerical, and semi-empirical methods are discussed. Under the empirical approach, the method based onthe vehicle cone index for tracked and wheeled vehicles is discussed. Under the numerical approach, advantages and disadvantages of Finite Element Method (FEM) and Discrete Element Method (DEM) are discussed. Semi-empirical method, based upon a combination of the best features of numerical and empirical approaches discusses terrain response to normal repetitive loads and shear repetitive loads for tracked as well as wheeled vehicles. Pressure sinkage relationship for terrains at various loading conditions and shear stress displacement relationship for different terrains obtained through penetration and shear tests are discussed to determine the vehicle’s mobility parameters under a semi-empirical approach. Further, the Super element model, multi-body simulation model, and ride and cornering vibration model are discussed under computer simulation models. A detailed review of various models customized towards tracked vehicle-terrain interaction discussed in this manuscript helps the authors set up a laboratory for terramechanics at DIAT. Preliminary analysis along with conceptual design of the experimental setup is also discussed. In a nutshell, this paper attempts to summarize the research that has been carried out in the field of tracked vehicle-terrain inter action comprising of VCI, MMP, FEM, DEM, Super element model, Multibody technique, and Semi-empirical methods helping the authors to establish a laboratory of terramechanics for their M. Tech. program on Armament and Combat Vehicles at DIAT Pune.

Crushing performance evaluation of gradient Sierpinski triangular fractal column

Thin-Walled Structures with excellent mechanical properties are the key to the protective system of the vehicle. This paper proposes a novel Sierpinski triangular fractal column with graded thickness (STFC-GT) to improve the crushing stability and energy absorption of Thin-Walled Structures. The crashworthiness of the STFC-GT is investigated through the experimental test and numerical simulation under axial crushing load. The results show that the Sierpinski triangular fractal column contributes to the energy absorption, and the graded thickness design can decrease the initial peak force. Specifically, the energy absorption of STFC-GT improves by 144.22 % from 0th to 2nd. And the initial peak force of 2nd STFC-GT is 55.32 % lower than that of 2nd STFC with uniform thickness. In addition, a theoretical relationship between the parameter configurations and the mean crushing force of STFC-GT are developed using the simplified super folding element theory (SSFE). The maximum error is less than 7.89 % between the theoretical and numerical results. Finally, the influence of gradient types on crushing performance is investigated to determine the optimal gradient configuration and maximize the mechanical performance of the STFC. The research result provides reliable guidance for the design of a new vehicle safety protection device.

An adaptive finite element method for coupled fretting wear and fatigue crack propagation simulation

Fretting wear and fatigue crack propagation often occur at the same time in the service of mechanically connected structures. In order to analyze the effect of fretting wear on the process of fatigue crack propagation, a finite element simulation method for fatigue crack propagation considering fretting wear is proposed. In this method, the Archard model is used to predict the wear process, and the conventional Paris equation is modified based on the wear rate. In order to improve the accuracy of crack propagation prediction, a crack-tip super singular element (CSSE) is used to calculate the singular stress field and fracture control parameters of the crack tip. An adaptive meshing technique that automatically adjusts the mesh density according to the simulation process is designed to ensure the computational efficiency of the algorithm and the accuracy of the numerical results. The smoothing technique used in wear simulation can alleviate the influence of contact stress fluctuation on wear profile prediction. The usage of the new simulation method is introduced through benchmark examples. It is proved that the numerical results of crack propagation obtained by the adaptive finite element method (FEM) have high precision, good convergence and high computational efficiency. It is found that wear reduces the crack growth rate compared with the simulation results without considering wear. This method has a promising application in the coupling analysis of fretting wear and fatigue crack propagation of mechanically connected structures.

Axial Crushing Theory and Optimization of Lattice-Filled Multicellular Square Tubes.

A lattice-filled multicellular square tube features a regular cross-sectional shape, good energy consumption, and good crashworthiness, which is suitable for the design of energy absorbers in various protection fields such as automobiles, aerospace, bridges, etc. Based on the super folding theory, two reference planes are set to refine the energy consumption zone of the super folding element in this study. The energy consumption calculation of convex panel stretching is involved, and the critical crushing force formula is introduced in this study. Meanwhile, the calculation method from a single-cell square tube to a multicellular thin-walled square tube is extended and the structural optimization is investigated, in which the NSGAII algorithm is used to obtain the Pareto front (PF) of the crashworthiness performance index of the square multicellular tubes, the Normal Boundary Intersection (NBI) method is adopted to select knee points, and the influence of different cross-sectional widths on the number, as well as the thickness, of cells are discussed. This study's results indicate that the theoretical value is consistent with that obtained from the numerical simulation, meaning that the improved theoretical model can be applied to predict the crashworthiness of multicellular square cross-sectional tubes. Also, the optimization method and study results proposed in this study can provide a reference for the design of square lattice multicellular tubes.

Numerical and theoretical analysis of the out-of-plane crushing behavior of a sinusoidal-shaped honeycomb structure with tunable mechanical properties

Honeycomb structures are widely utilized for energy absorption in engineering, showing superior crushing strength and energy absorption in the vertical direction, yet their potential as energy absorbers is limited due to a high initial peak force (IPF) in that direction. In this study, a novel honeycomb structure with tunable out-of-plane mechanical properties is developed by incorporating sinusoidal-shaped features into traditional vertically straight-walled cells. Crushing behavior and energy absorption performance of sinusoidal-shaped honeycomb structure (SSHS) under quasi-static out-of-plane compression are investigated numerically and theoretically. Results demonstrate that the IPF and the fluctuation of crushing response of SSHS can be effectively reduced for the introduction of sinusoidal-curved configuration. The predictable collapse mode of SSHS could be achieved for the buckling-induced features of trough and peak of sinusoidal waves. Parametric analyses were carried out to explore the influence of the geometrical topology of sinusoidal waves, namely, wave amplitude (A = 0.6–1.6 mm), wave number (N = 1–6) and the relative density (ρ = 0.05–0.25) on the out-of-plane mechanical properties of SSHS, including IPF, mean crushing force (MCF), specific energy absorption (SEA) and crushing force efficiency (CFE). The results imply properly adjusting topology parameters can determine the collapse patterns and the stress distribution, thereby substantially improving the mechanical properties. Moreover, theoretical investigation was also performed based on the simplified super folding element theory. The calculation of MCF shows a good agreement between the theoretical predictions and the numerical results. The sinusoidally curved-walled topology design strategy provides insights into the development of lightweight structures with controllable and improved crushing performance.

Design optimization of the bamboo-inspired foam-filled tube for high-speed train collision energy absorption

This study first developed a novel bamboo-inspired foam-filled tube (BFFT) for potential application in high-speed trains, considering the practical use conditions. The BFFT was initially designed by mimicking the macro and micro characteristics of bamboo culms and understanding their axial crushing mechanical behavior. The key bionic parameters are drawn based on the crashworthiness indices of natural bamboos with various geometric sizes and growth ages. The numerical simulation model of the BFFT under axial impact load was established and verified using simplified super folding element (SSFE) theory and drop-weight experiments. A multi-objective optimization on the BFFT was conducted to find the optimal parameter alternative, integrating experimental design method of the optimal Latin hypercube, the response surface agent model and the non-dominated sorting genetic algorithm (NSGA-II). The crashworthiness performance of the optimized BFFT was compared with the initial design scheme, a conventional circular tube and other existing energy absorbers of rail vehicles. The results indicated that the EA, SEA and IPCF values of the optimized BFFT can be improved by 150.2 %, 63.3 %, and 48.5 %, respectively, when considering the single target requirement. In comparison to the initial design scheme and conventional circular tube, the SEA value of the final optimized BFFT increased by 44.7 % and 53.0 %, respectively. The proposed novel BFFT demonstrated a superior crashworthiness, providing inspiration for enhancing and optimizing passive safety performance of high-speed trains.

Topology Optimization of Shape Memory Alloy Actuators for Prescribed Two-Way Transforming Shapes

This paper proposes a new topology optimization formulation for obtaining shape memory alloy actuators which are designed with prescribed two-way transforming shapes. The actuation behaviors of shape memory alloy structures are governed by austenite-martensite phase transformations effected by thermal-mechanical loading processes; therefore, to realize the precise geometric shape variations of shape memory alloy actuators, traditional methods involve iteration processes including heuristic structural design, numerical predictions and experimental validation. Although advanced structural optimization methods such as topology optimization have been used to design three-dimensional (3D) shape memory alloy actuators, the maximization/minimization of quantities such as structural compliance or inaccurate stroke distances has usually been selected as the optimization objective to obtain feasible solutions. To bridge the gap between precise shape-morphing requirements and efficient shape memory alloy actuator designs, this paper formulates optimization criteria with quantitatively desired geometric shapes, and investigates the automatic designs of two-way prescribed shape morphing shape memory alloy structures based on the proposed topology optimization method. The super element method and adjoint method are used to derive the analytical sensitivities of the objective functions with respect to the design variables. Numerical examples demonstrate that the proposed method can obtain 3D actuator designs that have the desired two-way transforming shapes.

Effect of cross-sectional shape evolvement on the energy absorption performances of multicellular square tube

This study systematically investigated the effect of position evolvement of four ribs in multicellular square tube on its crashworthiness performance. Results show that the multicellular square tubes with the shape factors of k = 0.25 and k = 0.75 have better energy absorption performances than other multicellular square tubes under the same wall thickness or the same mass. The mean crush force is derived through the simplified super folding element theory. Moreover, multi-objective optimization of multicellular square tube is carried out and the optimal result is validated by the finite element model.

Constructing artificial boundary condition of dispersive wave systems by deep learning neural network

To solve one dimensional dispersive wave systems in an unbounded domain, a uniform way to establish localized artificial boundary conditions is proposed. The idea is replacing the half-infinite interval outside the region of interest with a super element which exhibits the same dynamics response. Instead of designing the detailed mechanical structures of the super element, we directly reconstruct its stiffness, mass, and damping matrices by matching its frequency-domain reaction force with the expected one. An artificial neural network architecture is thus specifically tailored for this purpose. It comprises a deep learning part to predict the response of generalized degrees of freedom under different excitation frequencies, along with a simple linear part for computing the external force vectors. The trainable weight matrices of the linear layers correspond to the stiffness, mass, and damping matrices we need for the artificial boundary condition. The training data consists of input frequencies and the corresponding expected frequency domain external force vectors, which can be readily obtained through theoretical means. In order to achieve a good result, the neural network is initialized based on an optimized spring-damper-mass system. The adaptive moment estimation algorithm is then employed to train the parameters of the network. Different kinds of equations are solved as numerical examples. The results show that deep learning neural networks can find some unexpected optimal stiffness/damper/mass matrices of the super element. By just introducing a few additional degrees of freedom to the original truncated system, the localized artificial boundary condition works surprisingly well.

Landscape of enhancer disruption and functional screen in melanoma cells

BackgroundThe high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma.ResultsHere, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions.ConclusionsOur study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

Fault diagnosis of low-speed heavy load super large rolling bearing based on deep learning

The conventional eigenvalue alarm mode has a high rate of false alarm and missed alarm for the low-speed heavy load super large rolling bearing. Besides, the traditional signal processing method such as envelope spectral analysis is difficult to extract its fault characteristic frequencies, resulting in a high rate of false diagnosis and missed diagnosis. In order to solve the above problems, an intelligent diagnosis method for the low-speed heavy load super large rolling bearing based on deep learning is proposed. The proposed method mainly utilizes the strong robustness of deep learning algorithm to the quality of original vibration data in the field of fault diagnosis. Firstly, an effective signal acquisition scheme is designed to solve the problem that the signal characteristics of low-speed heavy load super large rolling element bearing are difficult to be acquired. Then, the collected data are randomly divided into training sets, verification sets and test sets by using data enhancement technology. Subsequently, input the divided training set samples into 1-dimensional convolution neural network (1DCNN) deep learning model for learning and training to construct the 1DCNN learning model and set network structure parameters. Meanwhile, the optimal training model is obtained by validating the updating effect of model parameters through validation set. Finally, the test data is input into the trained model to realize intelligent diagnosis. Effectiveness of the proposed method is verified by the vibration data of a wind power main bearing.

Integrated design and additive manufacturing of lattice-filled multi-cell tubes

In this paper, 3D printed lattice-filled multi-cell tubes, fabricated using chopped carbon-fiber-reinforced polyamide, were proposed to modify the deformation modes and improve the crashworthiness. Compression responses and energy absorption characteristics of the multi-cell tubes were investigated by quasi-static compression tests. The deformation and synergistic effect mechanisms of lattice-filled tubes were studied by observing the longitudinal sections of specimens. It was found that filling the lattice into multi-cell tubes exhibited an increase in the number of folds. When the lattice-filled tubes were fabricated integrally, multi-cell tubes changed from an asymmetrical to a symmetrical folding deformation mode due to the stronger and symmetrical interactions from the internal-filled lattice. Under the influence of the synergistic effect, the total energy absorption of the lattice-filled tubes with two different combination strategies presented increases of 55.6% and 83.8% compared with the sum of the empty multi-cell tube and pure lattice. In addition, a theoretical analysis for the mean crushing force of composite lattice-filled tubes was conducted based on simplified super folding element (SSFE) theory and bending deformation mechanism of the struts. The theoretical results were in good agreement with experimental studies and could be extended for lattice-filled tubes with other different filling configurations.

Application of Macro Element Method (MEM) for faster automotive crash safety design during concept stage

The non-linear nature of vehicle crash safety simulations using the Finite Element Method (FEM) usually requires a significant investment in computational time and resources, in addition to the requirement of full CAD (Computer Aided Design) data availability, which is challenging to obtain during the concept stage. The current work explores the usage of Macro Element Method (MEM) based on simplified Super Beam Element (SBE), for which the shape functions are developed based on experimental observations rather than algebraic equations. MEM crash analysis run time doesn’t exceed several seconds and is one of the underutilised analytical models which can be used to quickly explore new design directions during the early concept stage of the vehicle and has higher potential to speed up the product development process. In this paper, initially, a calibration study was done to validate the MEM at a component level to compare the results with FEM and experimental values. FEM and MEM simulation models were developed and evaluated for a metallic thin-walled square frusta with varying semi-apical angles subjected to axial compression. The results were compared, and it was found that MEM results show more than 97% correlation compared to FEM and experimental results. Subsequently, a design modification was introduced in the component and the results show close degree of correlation between MEM and FEM. Similar process was followed for full vehicle level simulations, such as full width frontal crash, side pole crash analyses to understand the robustness of the method in applying it to product development environment.

Train/track coupled dynamics model of long heavy haul train based on substructure and parallel computing

To consider the coupled effect on the running safety between elastic track and longitudinal impulse of Long Heavy Haul Train(LHHT), a train/track coupled dynamics model is established by using connection substructure theory. The ballasted track is divided into several segments called sub-tracks: a sub-track includes rail, sleepers and ballast. In the sub-track model, the sleepers and ballast are modelled as lumped mass. The rail is divided into the contact and connection rail. The contact rail is modelled as an Euler beam to reflect the wheel/rail interaction and the flexible vibration of the rail. The connection rail is modelled as a super element to reflect the interaction between adjacent contact rail. To increase the simulation speed, a new parallel computing method is proposed: a train/track coupled dynamics model is divided into different submodule, a submodule includes a sub-track and a vehicle on the sub-track. A submodule is calculated by a single computer core. The submodule is connected by connection rail, couplers and ballast. The advantage of this parallel method is that the load of each computer core is almost uniform. The simulation speed depends on the number of parallel computing cores instead of one core with a particularly large load. Finally, taking the 10,000-ton train as an example, the distribution of coupler force, the derailment coefficient and wheel unloading rate are given during the train braking on a curve, which shows the application and necessity of the train/track coupled dynamics model based on substructure and parallel computing.

Energy absorption characteristics of a super hexagonal honeycomb under out-of-plane crushing

Designing innovative honeycomb materials with improved energy absorption capacity is a long-term pursuit to provide adequate impact protection for crucial structural components. The edge-based design has been regarded as an effective strategy to enhance the mechanical properties and energy absorption of honeycomb materials. This paper proposes a novel super hexagonal honeycomb (SHH) structure to pursue better energy absorption capacities. Its geometry is derived from the outline of a hexagonal honeycomb. The crushing performance of the SHH is investigated based on the out-of-plane compression experiments, and an explicit finite element model is established to explore the crashworthiness characteristics of the structure. Furthermore, a theoretical model based on the simplified super folding element (SSFE) method is established to predict the mean crushing force during the crushing process. The comparison with the experimental and numerical results verifies its accuracy. Besides, the crushing mechanisms and collapse modes of the constitutive Y and V elements in the SHH are discussed. The parametric analysis of the crashworthiness of the SHH is conducted in terms of the cell-wall length ratio, sub-corner angle and hierarchy. The results reveal that the crashworthiness of SHH is much superior to traditional hexagonal honeycomb and presents 106%, 62%, 104% and 162% improvement in the mean crushing force, crushing force efficiency, specific energy absorption and volumetric energy absorption, respectively. This work can inspire future research on lightweight edge-based honeycombs with excellent energy absorption capacity.

Reassessment of Minimum Facilities Wellhead Platform due to Installation of Extension Compressors against Earthquake Loads

For increasing the production capacity of existing oil and gas wells, adding, or modifying the equipment with more sophisticated process equipment is necessary. One effort is by the addition of compressors such as on a minimum wellhead platform facility, which are installed on the top side of the platform. In addition to increasing the weight of the topside, which must be supported by the jacket, this installation makes the platform become more sensitive to seismic loads. This paper discusses the reassessment of the platform to determine the structural integrity due to the installation of the extension compressor to earthquake loads based on the API code RP 2A-WSD 22nd 2014 and RP 2SIM. Seismic analysis methods performed in this study include super element analysis, eigenvalue analysis, dynamic response analysis, earthquake analysis, post analysis, and single pile analysis. According to the code and company specifications, the analysis shows promising results in terms of the unity check, natural period, and displacement check, so the structural integrity is still acceptable for further operation.

Topology Optimization of Self-supporting Porous Structures Based on Triply Periodic Minimal Surfaces

With the advent of additive manufacturing (AM), topology optimization (TO) has become increasingly important in structural design. A key component of structural design is generating the interior shape of an object under predefined force conditions and specific constraints. Fabricating such models by layer-based AM suffers from the problem of adding and removing interior supporting structures, which can produce artifacts in the final product. In this paper, we propose an algorithm to design a self-supporting porous structure by integrating overhang constraints into the topology optimization framework. A minimum thickness constraint is also built into the optimization process to automatically enforce printability of the resulting structures. We utilize triply periodic minimal surfaces (TPMSs) to represent interior structures which can be analyzed, optimized and stored directly using analytical functions. We apply several acceleration methods including super element strategy, multigrid algorithm and GPU-based solver to handle models comprising of several million of elements efficiently. Numerical results indicate that the optimized interior structures obtained by our approach exhibit improved printability as they largely satisfy manufacturing requirements on overhang angles and minimal thicknesses.