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1 – 10 of 18Xiangyun Li, Liuxian Zhu, Shuaitao Fan, Yingying Wei, Daijian Wu and Shan Gong
While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential…
Abstract
Purpose
While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.
Design/methodology/approach
To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.
Findings
The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.
Originality/value
In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.
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Muhammed Kofoğlu, Doruk Erdem Yunus and Necati Ercan
Lattice structures are widely used for achieving optimal topology in additive manufacturing. However, the use of different lattices in a single design can result in stress…
Abstract
Purpose
Lattice structures are widely used for achieving optimal topology in additive manufacturing. However, the use of different lattices in a single design can result in stress concentrations at the transition points. This study aims to investigate the influence of Bezier curves on mechanical properties during the transformation from one lattice structure to another. It specifically focuses on the transition from a hexagonal to diamond lattice, using Bezier curves of various orders.
Design/methodology/approach
The curves were designed by passing them through the same control points for different orders, such as third, fifth and seventh. The samples were sliced for 3D printing, and a tensile test was conducted. Young’s modulus and energy absorption abilities were measured to compare the mechanical properties of the models created with Bezier curves for the transformation between hexagonal and diamond models.
Findings
The analysis revealed a gradual change in mechanical properties from the hexagonal to the diamond lattice. Moreover, different orders of Bezier curves exhibited varying mechanical properties during the transformation between the two lattices. As the order of the Bezier curve increased, the mechanical properties smoothly changed from the hexagonal to diamond lattice. This prevented stress concentrations or mechanical behavior mismatch caused by sudden deformations at the transitions between the curves used in the design.
Originality/value
The study’s innovative use of Bezier curves of different orders to smoothly transformation between hexagonal and diamond lattices in additive manufacturing offers a practical solution to prevent stress concentrations and mechanical inconsistencies during such design transitions.
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Sami Barmada, Nunzia Fontana, Leonardo Sandrolini and Mattia Simonazzi
The purpose of this paper is to gain a better understanding on how metasurfaces behave, in terms of currents in each unit cell. A better knowledge of their behavior could lead to…
Abstract
Purpose
The purpose of this paper is to gain a better understanding on how metasurfaces behave, in terms of currents in each unit cell. A better knowledge of their behavior could lead to an ad-hoc design for specific applications.
Design/methodology/approach
The methodology used is both theoretical and numerical; it is based on circuit theory and on an optimization procedure.
Findings
The results show that when the knowledge of the current in each unit cell of a metasurface is needed, the most common approximations currently used are often not accurate. Furthermore, a procedure for the termination of a metasurface, with application-driven goals, is given.
Originality/value
This paper investigates the distribution of the currents in a 2D metamaterial realized with magnetically coupled resonant coils. Different models for the analysis of these structures are illustrated, and the effects of the approximations they introduce on the current values are shown and discussed. Furthermore, proper terminations of the resonators on the boundaries have been investigated by implementing a numerical optimization procedure with the purpose of achieving a uniform distribution of the resonator currents. The results show that the behavior of a metasurface (in terms of currents in each single resonator) depends on different properties; as a consequence, their design is not a trivial task and is dependent on the specific applications they are designed for. A design strategy, with lumped impedance termination, is here proposed.
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Dong Li, Yu Zhou, Zhan-Wei Cao, Xin Chen and Jia-Peng Dai
This paper aims to establish a lattice Boltzmann (LB) method for solid-liquid phase transition (SLPT) from the pore scale to the representative elementary volume (REV) scale. By…
Abstract
Purpose
This paper aims to establish a lattice Boltzmann (LB) method for solid-liquid phase transition (SLPT) from the pore scale to the representative elementary volume (REV) scale. By applying this method, detailed information about heat transfer and phase change processes within the pores can be obtained, while also enabling the calculation of larger-scale SLPT problems, such as shell-and-tube phase change heat storage systems.
Design/methodology/approach
Three-dimensional (3D) pore-scale enthalpy-based LB model is developed. The computational input parameters at the REV scale are derived from calculations at the pore scale, ensuring consistency between the two scales. The approaches to reconstruct the 3D porous structure and determine the REV of metal foam were discussed. The implementation of conjugate heat transfer between the solid matrix and the solid−liquid phase change material (SLPCM) for the proposed model is developed. A simple REV-scale LB model under the local thermal nonequilibrium condition is presented. The method of bridging the gap between the pore-scale and REV-scale enthalpy-based LB models by the REV is given.
Findings
This coupled method facilitates detailed simulations of flow, heat transfer and phase change within pores. The approach holds promise for multiscale calculations in latent heat storage devices with porous structures. The SLPT of the heat sinks for electronic device thermal control was simulated as a case, demonstrating the efficiency of the present models in designing and optimizing SLPT devices.
Originality/value
A coupled pore-scale and REV-scale LB method as a numerical tool for investigating phase change in porous materials was developed. This innovative approach allows for the capture of details within pores while addressing computations over a large domain. The LB method for simulating SLPT from the pore scale to the REV scale was given. The proposed method addresses the conjugate heat transfer between the SLPCM and the solid matrix in the enthalpy-based LB model.
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Fay Rhianna Claybrook, Darren John Southee and Mazher Mohammed
Cushioning is a useful material property applicable for a range of applications from medical devices to personal protective equipment. The current ability to apply cushioning in a…
Abstract
Purpose
Cushioning is a useful material property applicable for a range of applications from medical devices to personal protective equipment. The current ability to apply cushioning in a product context is limited by the appropriateness of available materials, with polyurethane foams being the current gold standard material. The purpose of this study is to investigate additively manufactured flexible printing of scaffold structures as an alternative.
Design/methodology/approach
In this study, this study investigates triply periodic minimal surface (TPMS) structures, including Gyroid, Diamond and Schwarz P formed in thermoplastic polyurethane (TPU), as a possible alternative. Each TPMS structure was fabricated using material extrusion additive manufacturing and evaluated to ASTM mechanical testing standard for polymers. This study focuses attention to TPMS structures fabricated for a fixed unit cell size of 10 mm and examine the compressive properties for changes in the scaffold porosity for samples fabricated in TPU with a shore hardness of 63A and 90A.
Findings
It was discovered that for increased porosity there was a measured reduction in the load required to deform the scaffold. Additionally, a complex relationship between the shore hardness and the stiffness of a structure. It was highlighted that through the adjustment of porosity, the compressive strength required to deform the scaffolds to a point of densification could be controlled and predicted with high repeatability.
Originality/value
The results indicate the ability to tailor the scaffold design parameters using both 63A and 90A TPU material, to mimic the loading properties of common polyurethane foams. The use of these structures indicates a next generation of tailored cushioning using additive manufacturing techniques by tailoring both geometry and porosity to loading and compressive strengths.
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Kunpeng Shi, Guodong Jin, Weichao Yan and Huilin Xing
Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel…
Abstract
Purpose
Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.
Design/methodology/approach
A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.
Findings
The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R2) is 0.93 for the validation set, and the R2 for the test set A and test set B are 0.93 and 0.94, respectively.
Originality/value
This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.
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Hesham Mohsen Hussein Omar, Mohamed Fawzy Aly Mohamed and Said Megahed
The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper…
Abstract
Purpose
The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.
Design/methodology/approach
After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.
Findings
The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.
Research limitations/implications
The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.
Originality/value
This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.
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Vaishali Rajput, Preeti Mulay and Chandrashekhar Madhavrao Mahajan
Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired…
Abstract
Purpose
Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.
Design/methodology/approach
Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.
Findings
The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.
Originality/value
The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.
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Na Xu, Yanxiang Liang, Chaoran Guo, Bo Meng, Xueqing Zhou, Yuting Hu and Bo Zhang
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a…
Abstract
Purpose
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.
Design/methodology/approach
Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.
Findings
Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.
Originality/value
This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.
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Muhammad Hakeem Mohammad Nazri, Tan Chou Yong, Farazila B. Yusof, Gregory Soon How Thien, Chan Kah Yoong and Yap Boon Kar
Die edge quality with its corresponding die strength are two important factors for excellent dicing quality especially for low-k wafers due to their weak mechanical properties and…
Abstract
Purpose
Die edge quality with its corresponding die strength are two important factors for excellent dicing quality especially for low-k wafers due to their weak mechanical properties and fragile structures. It is shown in past literatures that laser dicing or grooving does yield good dicing quality with the elimination of die mechanical properties. This is due to the excess heat energy that the die absorbs throughout the procedure. Within the internal structure, the mechanical properties of low-k wafers can be further enhanced by modification of the material. The purpose of this paper is to strengthen the mechanical properties of wafers through the heat-treatment process.
Design/methodology/approach
The methodology of this approach is by heat treating several low-k wafers that are scribed with different laser energy densities with different laser micromachining parameters, i.e. laser power, frequency, feed speed, defocus reading and single/multibeam setup. An Nd:YAG ultraviolet laser diode that is operating at 355 nm wavelength was used in this study. The die responses from each wafer are thoroughly visually inspected to identify any topside chipping and peeling. The laser grooving profile shape and deepest depth are analysed using a laser profiler, while the sidewalls are characterized by scanning electron microscopy (SEM) to detect cracks and voids. The mechanical strength of each wafer types then undergoes three-point bending test, and the performance data is analyzed using Weibull plot.
Findings
The result from the experiment shows that the standard wafers are most susceptible to physical defects as compared to the heat-treated wafers. There is improvement for heat-treated wafers in terms of die structural integrity and die strength performance, which revealed a 6% increase in single beam data group for wafers that is processed using high energy density laser output but remains the same for other laser grooving settings. Whereas for multibeam data group, all heat-treated wafer with different laser settings receives a slight increase at 4% in die strength.
Originality/value
Heat-treatment process can yield improved mechanical properties for laser grooved low-k wafers and thus provide better product reliability.
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