Structural Design Optimization Research Articles

The effect of heterogeneous geometry on steady-state heat transfer in extrusion-based 3D printed structures

The 3D printed buildings constructed using rapid manufacturing techniques provide opportunities for structural optimization and performance design, which are beneficial in meeting the vision of digital and sustainable development of the construction industry. However, there are still many research gaps in the heat transfer of 3D printed buildings, impacting the accurate design of their thermal performance. This study quantifies the effect of heterogeneous geometry on heat transfer in extrusion-based 3D printed structures. The experiment reveals that the non-uniform surface temperature distribution primarily originates from geometrical factors, with heterogeneous physical properties caused by cold joints having little influence. Numerical simulations using equivalent geometric models indicate that the local temperature and the convective heat transfer coefficient of raised surfaces vary periodically, corresponding to surface shape. As surface bulges increase, the overall average heat transfer efficiency of the 3D printed structure decreases, while total surface heat transfer increases. These findings help to understand the effect of heterogeneous geometric properties on the heat transfer process of 3D printed structures, thus providing a reference for the accurate design of 3D printed structures with thermal functions.

Fatigue Analysis of Nitinol Peripheral Artery Stents Under Complex Loads

Abstract The complex deformation of a peripheral arterial stent during limb movements is the main reason for its fatigue fracture. The aim of this study is to explore the impact of complex loads on the fatigue behavior and life of lower limb arterial stents. Specifically, the finite element simulation was adopted to compare and analyze the fatigue performance of three stents under five superimposed loads. Besides, the life and the fatigue crack growth life of these stents were predicted. It demonstrated that the bending load superimposed on other loads exerted a significant impact on the fatigue performance of these stents. The “spiral” structure design of the stent helped to improve the fatigue durability under complex deformations. Moreover, the prediction method for fatigue crack growth life is relatively conservative, which accounted for approximately 65–97% of the full life. The work provides important references for the fracture assessment and the optimization design of structure of stents.

Smooth topological design of lightweight vibro-acoustic sandwich structures by maximizing sound transmission loss

The vibro-acoustic coupling mechanism and its optimization design of lightweight sandwich structures are globally hot research topics. The traditional parameter adjustment approach highly relies on the experience of designers, which makes it difficult to achieve lightweight design while regulating the acoustic insulation performance of sandwich structures at a limited cost. This paper proposes a new dynamic three-field floating projection topology optimization (FPTO) method to conduct vibro-acoustic coupling topological design for lightweight insulated sandwich structures, to achieve superior sound insulation performance by maximizing sound transmission loss with a volume constraint. The effectiveness and accuracy of the proposed method were verified on representative 2D and 3D numerical examples and also validated with impedance tube tests. The results show that novel optimized structures with a smooth boundary for practical applications and superior acoustic insulation performance than conventional designs can be obtained based on the proposed method. For instance, at an optimization target frequency of 1200 Hz, the total sound transmission loss, corresponding to the optimized target sound insulation performance of the 3D sandwich case, showed an improvement from 56.68 dB to 70.8 dB, compared to the common closed honeycomb structures in engineering practice under the equal mass conditions. Moreover, the numerical simulation and experimental results showed good agreement. The study suggests that the dynamic three-field FPTO method is promising for optimizing acoustic and vibration performance in lightweight vibro-acoustic sandwich structures.

Optimum Design of Cooling Structure for In-Wheel Motor Drive System

The high-efficient cooling structure is one of the key basic problems in the design of the highly integrated in-wheel motor (IWM) drive system. A 15 kW IWM drive system with the spiral cooling structure is taken as the research object in this article. First, the thermal characteristics under different conditions are analyzed based on the modeling and the heat source determination of the IWM drive system. Second, the highest temperature of insulation and permanent magnet and temperature difference of insulation are taken as optimization objectives. The inlet flow rate, the inlet and outlet diameters, the channel numbers, the channel height, and the channel ribs thickness of cooling structure are taken as optimization parameters to optimize based on the designed experiments, the multivariate linear regression equation and PSO method. Finally, the optimization results are verified by comparing the temperature field before and after optimization. The results show that the optimized structure can achieve better effect. The highest temperature of insulation, the highest temperature of permanent magnet and the temperature difference of insulation of IWM decreased by 9.27%, 9.52%, and 20.93%, respectively. This research work can provide some ideas and methods for the optimization design of cooling structure of IWM drive system.

Understanding the Nonradiative Charge Recombination in Organic Photovoltaics: From Molecule to Device

AbstractOrganic photovoltaics (OPVs) have made significant strides with efficiencies now exceeding 20%, positioning them as potential competitors to inorganic solar technologies. One of the most critical challenges toward this goal is the severe open‐circuit voltage (Voc) loss caused by the nonradiative charge recombination (NRCR). Herein, this review comprehensively summarizes the NRCR mechanisms and suppression techniques of OPVs across various scales from molecule to device. Specifically, the origins of NRCR in a single molecule are first summarized, and molecular design principles toward high photoluminescence quantum yield are reviewed following the Marcus theory. Next, the effect of aggregation on NRCR is reviewed, as well as the molecular and processing strategies to modulate the film packing for NRCR suppression. Furthermore, the progresses in the avoidance of nonradiative loss pathways mediated by charge transfer states and triplet states in donor:acceptor bulk heterojunctions are tracked. Besides, the interfacial optimization and device structure design to maximize the electroluminescent quantum efficiency are presented. Finally, several potential pathways toward curtailing NRCR for high‐performance OPVs are outlined. Therefore, this review shows an insightful perspective to understand and mitigate the NRCR at multi‐scales, and is poised to provide a clear roadmap for the next breakthrough of OPVs.

Failure Behavior and Mechanism of Vat Photopolymerization Additively Manufactured Al2O3 Ceramic Lattice Structures

Vat photopolymerization additive manufacturing produces lightweight load-bearing ceramic lattice structures that have flexibility, time-efficiency, and high precision, compared to conventional technology. However, understanding the compression behavior and failure mechanism of such structures under loading remains a challenge. In this study, considering the correlation between the strut angle and bearing capacity, body-centered tetragonal (BCT) lattice structures with varying angles are designed based on a body-centered cubic (BCC) structure. BCT Al2O3 ceramic lattice structures with varying angles are fabricated by vat photopolymerization. The mechanical properties, deformation process, and failure mechanism of the Al2O3 ceramic lattice structures are characterized through a combination of ex- and in-situ X-ray computed tomography (X-CT) compression testing and analyzed using a finite element method (FEM) at macro- and micro-levels. The results demonstrate that as the angle increases, the stress concentration gradually expands from the node to the strut, resulting in an increased load-bearing capacity. Additionally, the failure mode of the Al2O3 ceramic lattice structures is identified as diagonal slip shear failure. These findings provide a greater understanding of ceramic lattice structure failures and design optimization approaches.

Improved krill swarm algorithm and its application in structural optimization

This paper improves and perfects the standard Krill herd algorithm (KH), which has the defects of slow convergence speed, insufficient calculation accuracy and easy to fall into local optimal solution for complex problems. An improved Krill herd algorithm (SDEKH) integrating improved differential evolution operator and S-type adaptive inertia weight is proposed. SDEKH, KH and other intelligent algorithms are compared and tested through a variety of standard test functions to verify the excellent performance of SDEKH; SDEKH is used to optimize the design of truss structure. By comparing the optimization results with other methods, it is verified that the optimization efficiency and accuracy of SDEKH are improved, which provides a more efficient and accurate method for the optimization design of engineering structures.

Current status and challenges of lightweight design and manufacturing technology for aerospace structures

Lightweight technology refers to the technology of reducing the structural mass by optimizing materials, structures and manufacturing processes while meeting the requirements of structural performance. It has become one of the key technologies for the development of the new generation of aerospace equipment. This paper first analyzes the development history of lightweight technology. Secondly, from the perspectives of design principles, composition methods and optimization methods, three types of lightweight design methods are introduced: bionic structure design, cellular structure design and efficient topology optimization design. Then, from the perspective of lightweight manufacturing processes and modes, the application of additive manufacturing, collaborative manufacturing and composite material manufacturing in lightweight manufacturing of aerospace structures is explained. Finally, the challenges and future development of lightweight technology are discussed.

Using In situ Transmission Electron Microscopy to Study Strong Metal-Support Interactions in Heterogeneous Catalysis.

Precisely controlling the microstructure of supported metal catalysts and regulating metal-support interactions at the atomic level are essential for achieving highly efficient heterogeneous catalysts. Strong metal-support interaction (SMSI) not only stabilizes metal nanoparticles and improves their resistance to sintering but also modulates the electrical interaction between metal species and the support, optimizing the catalytic activity and selectivity. Therefore, understating the formation mechanism of SMSI and its dynamic evolution during the chemical reaction at the atomic scale is crucial for guiding the structural design and performance optimization of supported metal catalysts. Recent advancements in in situ transmission electron microscopy (TEM) have shed new light on these complex phenomena, providing deeper insights into the SMSI dynamics. Here, the research progress of in situ TEM investigation on SMSI in heterogeneous catalysis is systematically reviewed, focusing on the formation dynamics, structural evolution during the catalytic reactions, and regulation methods of SMSI. The significant advantages of in situ TEM technologies for SMSI research are also highlighted. Moreover, the challenges and probable development paths of in situ TEM studies on the SMSI are also provided.

A mechanics-based data-free Problem Independent Machine Learning (PIML) model for large-scale structural analysis and design optimization

Machine learning (ML) enhanced fast structural analysis and design recently attracted considerable attention. In most related works, however, the generalization ability of the ML model and the massive cost of dataset generation are the two most criticized aspects. This work combines the advantages of the universality of the substructure method and the superior predictive ability of the operator learning architecture. Specifically, using a novel mechanics-based loss function, lightweight neural network mapping from the material distribution inside a substructure and the corresponding continuous multiscale shape function is well-trained without preparing a dataset. In this manner, a problem machine learning model (PIML) that is generally applicable for efficient linear elastic analysis and design optimization of large-scale structures with arbitrary size and various boundary conditions is proposed. Several examples validate the effectiveness of the present work on efficiency improvement and different kinds of optimization problems. This PIML model-based design and optimization framework can be extended to large-scale multiphysics problems.

New shape optimization method for tree structures based on BP neural network

To realize the intelligent optimization for the tree structures supporting freeform surface roof or bearing uneven load, a new shape optimization method based on the back-propagation (BP) neural network is proposed. This method enables the intelligent positioning of hierarchical nodes through a recursive approach from top-down, with the aim of satisfying the zero bending moment and structural stability. Using three-dimensional tree structures as an example, this study provides a detailed description of the implementation method and steps of intelligent shape optimization, along with a comparative analysis with the reverse-hang recursive approach. Results indicate that the proposed approach effectively addresses the challenge of locating load-bearing centers in tree structures with uneven loads or freeform surface roofs. It not only demonstrates universality for tree structures under complex engineering conditions, but also enhances efficiency and intelligence in the structure optimization design.

مقارن تحليلة للتصميم الأمثل مقابل التصميم المناسب للمنشآت المستدامة

The growing urgency for sustainable construction practices has necessitated a reevaluation of traditional design approaches in favor of more environmentally responsible methodologies. This paper presents a comparative analysis between optimal and adequate structural design within the context of sustainable construction. Focusing on two case studies—a cutting-edge, sustainably designed commercial building (the Bullitt Center) and a conventional mid-rise residential building in Chicago—the research explores how different design philosophies impact material efficiency, environmental footprint, economic performance, and occupant satisfaction.Through detailed life cycle assessments (LCA) and life cycle energy analyses (LCEA), the study quantifies the advantages of optimal design, which integrates advanced materials, renewable energy systems, and water conservation technologies. The findings demonstrate that while optimal design requires a higher initial investment, it significantly reduces long-term operational costs and environmental impact, achieving a net-zero energy status and greatly improving occupant well-being. In contrast, the conventional building, which adheres to standard design practices, exhibits higher embodied energy, greater environmental degradation, and lower occupant satisfaction.The paper concludes that optimal structural design is not only more sustainable but also economically viable over the building's life span. It emphasizes the importance of integrating sustainability from the earliest stages of design to achieve meaningful environmental and economic benefits. The study calls for the adoption of policy incentives and advanced modeling tools to facilitate the widespread implementation of optimal design principles in the construction industry. Keywords: Sustainable Construction, Optimal Structural Design, Adequate Design, Building Performance, Embodied Energy, Environmental Impact, Economic Viability, Material Efficiency

Core Technologies of Sugarcane Chopper Harvester Extractor: A Critical Review

This review has systematically assessed the critical technologies of impurity removal fans in segmental sugarcane harvesters, highlighting their impact on minimizing harvester impurity rates. The analysis was conducted from three perspectives: Firstly, the physical properties of flexible sheet-like materials were thoroughly examined, including the methodologies for material parameter measurement, the utilization of technical approaches, and the constraints of existing methods. Secondly, the operational mechanisms of impurity removal fans were elucidated, encompassing their working principles, research subjects, and technical methodologies, and compared with the mechanisms of analogous fluid machinery. Lastly, a review of the structural design and parameters of impurity removal fans was undertaken, analyzing the interplay between operational modes, structural optimization designs, and aerodynamic characteristics. The review identified key issues in the design and performance of impurity removal fans and recognized the challenges in technological advancement. Through this triadic analytical framework, the review has identified salient design and performance deficiencies within existing impurity expulsion fan technologies and has underscored the formidable challenges confronting technological evolution in this domain. Synthesizing these insights, the review proffered prospective research vectors and avant-garde technological interventions poised to augment the operational efficacy of impurity expulsion fans, with the overarching goal of enhancing the operational proficiency of sugarcane harvesting machinery.

Optimization design of composite cap-shape pillar structure based on gaussian process of combined kernel function

Abstract To quickly realize the optimal design of the cap-shaped structure, an optimization design method of composite cap-shaped pillar structure based on combined kernel function Gaussian process was proposed. First, the shortcomings of two kernel functions representing different linear characteristics of data in model construction were analyzed, on which a new combined kernel function was constructed. Based on the finite element numerical simulation results, a database with the web thickness, web height, fiber volume, and ultimate bearing capacity of the cap-shaped structure was constructed. Then, a Gaussian process model based on the combined kernel function was established and the model parameters were trained by the maximum likelihood method. Finally, taking the ultimate bearing capacity per unit volume as the optimization objective, the artificial fish swarm algorithm was used to quickly obtain the structure design parameters under the optimal objective function, and the simulation results were compared with the initial design parameters. The results showed that the method proposed in this paper can optimize the structure performance, improve the design efficiency, and meet the engineering design requirements.

Stochastic design optimization of nonlinear structures under random seismic excitations using incremental dynamic analysis

The increasing demand for mitigating earthquake hazards has prompted substantial research attention towards performance-based seismic design of civil structures. Nevertheless, there remains limited exploration into optimizing complex structures while accounting for seismic uncertainties. This study seeks to address this gap by introducing an effective approach for optimizing designs of nonlinear structures under random seismic excitations. The key innovation lies in approximating structural failure probability through incremental dynamic analysis (IDA), leading to the development of a novel double-loop optimization method tailored for designing nonlinear structures exposed to stochastic seismic loading conditions. In the outer loop, geometric variables of structures are optimized using sequential quadratic programming; within the inner loop, IDA is adopted for structural analysis to quantify seismic uncertainty, and the resulting failure probability is then served as the optimization constraint for the outer loop. To validate its accuracy and efficacy, numerical investigations have been performed on two representative case studies utilizing OpenSees: a reinforced concrete column and a three-story steel frame. The findings affirm that IDA can precisely estimate failure probabilities associated with nonlinear structures experiencing random ground motions and demonstrate that this proposed methodology can effectively determine optimal geometries aimed at enhancing structural resilience against earthquakes across various levels of failure probabilities and bound constraints.

Improving dynamic energy absorption performance and stability loss prediction of an all-PET sandwich structure through artificial neural networks

Abstract One key characteristic that is frequently studied in composite sandwich structure mechanics is low-velocity impact performance. Single polymer composites present higher ductility when compared to traditional glass fibre and carbon fibre reinforced plastic composites (GFRP, CFRP), which makes them strong candidates for impact energy absorption. These lightweight structures are also fully recyclable due to their all-PET constituents, an important aspect when considering possible applications. In this paper an existing second order composite SrPET and PET foam sandwich structure (self-reinforced poly-ethylene terephthalate matrix and fibre) is numerically investigated for optimal structural design configuration under out-ofplane, low velocity, dynamic loading. The study explores the parametric geometry interdependencies of the structure’s configuration with respect to its energy absorption potential. The results are then compared to the quasi-static loading performance behaviour studied by M.N. Velea et all [1]. This work provides a deeper understanding of how geometry configurations can influence energy absorption capabilities highlighting structural strengths and weaknesses while exploring non-equilateral triangle configurations. The Design Space Exploration (DSE) is carried out by using an optimization algorithm for a dynamic out of plane 3D impact simulation based on the finite element (FE) method software. The synergy between DSE and FE generates a guided simulation loop that can successfully be used to train a neural network to predict the dynamic behaviour of different geometric configurations from the exploration space. Based on the data samples obtained, an artificial neural network (ANN) is built to predict the energy absorption capacity for a given set of structural design parameters, useful in experimental validation test cases.

Application and structural optimization design of magnetic fluid sealing in valve plate pairs of plunger pumps

Application and structural optimization design of magnetic fluid sealing in valve plate pairs of plunger pumps

Structure optimal design of 500 kV dry-type air-core shunt reactor based on response surface method

The hotspot temperature of the reactor is one of the important indices in reactor design, and the appropriate hotspot value can ensure that the reactor will not overheat failure and threaten the safety of the power system. In this paper, the temperature field simulation model of a 500 kV dry-type air-core shunt reactor is established, and the hotspot temperature of the reactor is obtained by COMSOL software. Then, the radial basis function response surface function is used to construct the response surface function of the hotspot temperature and its related variables, and the applicability of the response surface function is tested to analyze the rationality and accuracy of the response surface function. Finally, the optimal solution of the response surface function under the coordination of variables and related constraints is obtained by using the constrained simulated annealing algorithm. The results show that the hotspot temperature of the reactor envelope winding decreases obviously after optimization.

Truss sizing optimum design using a metaheuristic approach: Connected banking system

Several methods have been used to solve structural optimum design problems since the creation of a need for light weight design of structures and there is still no single method for solving the optimum design problems in structural engineering field that is capable of providing efficient solutions to all of the structural optimum design problems. Therefore, there are several proposed and utilized methods to deal with optimum design issues and problems, that sometimes give promising results and sometimes the solutions are quite unacceptable. This issue with metaheuristic algorithms, which are suitable approaches to solve these set of problems, is quite usual and is supported by the “No Free Lunch theorem”. Researchers try harder than the past to propose methods capable of presenting robust and optimal solutions in a wider range of structural optimum design problems, so that to find an algorithm that can cover a wider range of structural optimization problems and obtain a better optimum design. Truss structures are one of these problems which have extremely complex search spaces to conduct search procedures by metaheuristic algorithms. This paper proposes a method for optimum design of truss sizing problems. The presented method is used against 6 well-known benchmark truss structures (10 bar, 17 bar, 18 bar, 25 bar, 72 bar and 120 bar) and its results are compared with some of the available studies in the literature. The performance of the presented algorithm can be considered as very acceptable.

Structural Optimization Design and Adaptability Analysis of a Novel Axial-Flow Cyclone

Structural Optimization Design and Adaptability Analysis of a Novel Axial-Flow Cyclone