Optimization for structural crashworthiness and energy absorption has become an important topic of research attributable to its proven benefits to public safety and social economy. This paper ...provides a comprehensive review of the important studies on design optimization for structural crashworthiness and energy absorption. First, the design criteria used in crashworthiness and energy absorption are reviewed and the surrogate modeling to evaluate these criteria is discussed. Second, multiobjective optimization, optimization under uncertainties and topology optimization are reviewed from concepts, algorithms to applications in relation to crashworthiness. Third, the crashworthy structures are summarized, from generically novel structural configurations to industrial applications. Finally, some conclusions and recommendations are provided to enable academia and industry to become more aware of the available capabilities and recent developments in design optimization for structural crashworthiness and energy absorption.
In the fiber communication domain, people are facing the challenges due to the rapidly growing requirement on the capacity from new functions and services. Multi-hump solitons are therefore noticed ...and studied on the feasibility of improving the capacity of the optical fiber communication. In this paper, we study the vector bright solitons and their interaction properties of the coupled Fokas–Lenells system, which models the femtosecond optical pulses in a birefringent optical fiber. We derive the so-called degenerate and nondegenerate vector solitons associated with the one and two eigenvalues, respectively, and the latter admits the symmetric profile. Asymptotically and graphically, interaction patterns of such solitons are classified as follows: Interactions between the degenerate solitons can be elastic or inelastic, reflecting the intensity redistribution between the two components; Interactions between the degenerate and nondegenerate solitons are inelastic, which make the nondegenerate solitons maintaining or losing the profiles in the different situations; Interactions between the nondegenerate solitons do not cause the intensity redistribution, while their shapes change slightly or remain unchanged.
The Brinell, Vickers, Meyer, Rockwell, Shore, IHRD, Knoop, Buchholz, and nanoindentation methods used to measure the indentation hardness of materials at different scales are compared, and main ...issues and misconceptions in the understanding of these methods are comprehensively reviewed and discussed. Basic equations and parameters employed to calculate hardness are clearly explained, and the different international standards for each method are summarized. The limits for each scale are explored, and the different forms to calculate hardness in each method are compared and established. The influence of elasticity and plasticity of the material in each measurement method is reviewed, and the impact of the surface deformation around the indenter on hardness values is examined. The difficulties for practical conversions of hardness values measured by different methods are explained. Finally, main issues in the hardness interpretation at different scales are carefully discussed, like the influence of grain size in polycrystalline materials, indentation size effects at micro- and nanoscale, and the effect of the substrate when calculating thin films hardness. The paper improves the understanding of what hardness means and what hardness measurements imply at different scales.
During the last few decades, industries such as aerospace and wind energy (among others) have been remarkably influenced by the introduction of high-performance composites. One challenge, however, ...for modeling and designing composites is the lack of computational efficiency of accurate high-fidelity models. For design purposes, using conventional optimization approaches typically results in cumbersome procedures due to huge dimensions of the design space and high computational expense of full-field simulations. In recent years, deep learning techniques have been found to be promising methods to increase the efficiency and robustness of a variety of algorithms in multi-scale modeling and design of composites. In this perspective paper, a short overview of the recent developments in micromechanics-based machine learning for composites is given. More importantly, existing challenges for further model enhancements and future perspectives of the field development are elaborated.
•A brief overview of recent developments of deep learning for composites is provided.•Main challenges for further developments of the field are detailed.•Perspective solutions to address existing challenges are elaborated.•Future potential paths of the field developments are discussed.
Lower limb rehabilitation exoskeleton robots integrate sensing, control, and other technologies and exhibit the characteristics of bionics, robotics, information and control science, medicine, and ...other interdisciplinary areas. In this review, the typical products and prototypes of lower limb exoskeleton rehabilitation robots are introduced and state-of-the-art techniques are analyzed and summarized. Because the goal of rehabilitation training is to recover patients’ sporting ability to the normal level, studying the human gait is the foundation of lower limb exoskeleton rehabilitation robot research. Therefore, this review critically evaluates research progress in human gait analysis and systematically summarizes developments in the mechanical design and control of lower limb rehabilitation exoskeleton robots. From the performance of typical prototypes, it can be deduced that these robots can be connected to human limbs as wearable forms; further, it is possible to control robot movement at each joint to simulate normal gait and drive the patient’s limb to realize robot-assisted rehabilitation training. Therefore human–robot integration is one of the most important research directions, and in this context, rigid-flexible-soft hybrid structure design, customized personalized gait generation, and multimodal information fusion are three key technologies.
The question of how methods from the field of artificial intelligence can help improve the conventional frameworks for topology optimisation has received increasing attention over the last few years. ...Motivated by the capabilities of neural networks in image analysis, different model-variations aimed at obtaining iteration-free topology optimisation have been proposed with varying success. Other works focused on speed-up through replacing expensive optimisers and state solvers, or reducing the design-space have been attempted, but have not yet received the same attention. The portfolio of articles presenting different applications has as such become extensive, but few real breakthroughs have yet been celebrated. An overall trend in the literature is the strong faith in the “magic”of artificial intelligence and thus misunderstandings about the capabilities of such methods. The aim of this article is therefore to present a critical review of the current state of research in this field. To this end, an overview of the different model-applications is presented, and efforts are made to identify reasons for the overall lack of convincing success. A thorough analysis identifies and differentiates between problematic and promising aspects of existing models. The resulting findings are used to detail recommendations believed to encourage avenues of potential scientific progress for further research within the field.
Since their inception, computational homogenization methods based on the fast Fourier transform (FFT) have grown in popularity, establishing themselves as a powerful tool applicable to complex, ...digitized microstructures. At the same time, the understanding of the underlying principles has grown, in terms of both discretization schemes and solution methods, leading to improvements of the original approach and extending the applications. This article provides a condensed overview of results scattered throughout the literature and guides the reader to the current state of the art in nonlinear computational homogenization methods using the fast Fourier transform.
Closed cavity is a common design feature in topology optimization, but quite unfavorable for fabrication, even for highly flexible powder-based additive manufacturing (AM) technology. This is due to ...the fact that the temporary support material and unmelted powder inside the closed cavity are impossible to remove without damaging the optimized structure, yet would degrade design performance if left in the structure. Thus, this paper presents an AM-driven topological design method to solve the fabrication issues caused by closed cavities, while reducing the effect of manufacturing constraints on design freedom. Specifically, a sequential strategy integrated with self-support topology and connectivity design is developed to tackle the unprintable overhang features and trapped powder problem, rather than directly restricting the generation of closed cavities. Firstly, the closed cavities in the optimized structure are identified by introducing a connected component labeling algorithm, and then the overhang features and connectivity can be evaluated. The self-support topology is achieved by eliminating the overhang elements based on the proposed hybrid modification scheme. On the other hand, the connectivity design is formulated as finding the optimal paths connecting the closed cavities to the structural outside, in which the elements on the paths are deleted as the channels for removing residual powder. To illustrate the effectiveness of the proposed method, multiple 3D numerical examples and manufacturing experiments are conducted. The outcomes consistently demonstrate the advantage of the sequential strategy in achieving printable structures while minimizing any potential performance degradation.Please check and confirm the author names and initials are correct. Also, kindly confirm the details in the metadata are correct.No problem.
Additive manufacturing (AM) offers exciting opportunities to manufacture parts of unprecedented complexity. Topology optimization is essential to fully exploit this capability. However, AM processes ...have specific limitations as well. When these are not considered during design optimization, modifications are generally needed in post-processing, which add costs and reduce the optimized performance. This paper presents a filter that incorporates the main characteristics of a generic AM process, and that can easily be included in conventional density-based topology optimization procedures. Use of this filter ensures that optimized designs comply with typical geometrical AM restrictions. Its performance is illustrated on compliance minimization problems, and a 2D Matlab implementation is provided.
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