Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or hig...Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.展开更多
Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numeric...Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.展开更多
Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The...Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The intense vibration during needle punching not only generates huge noise,but also substantially reduces the quality of the preform.It is imperative to perform a dynamic analysis and optimization of the entire needle punching machine.In this paper,the three-dimensional(3D)model of the entire double-shaft-driven needle punching machine for C/C crucible preforms is established.Based on the modal analysis theory,the modal characteristics of the needle punching machine under various operating conditions are analyzed and its natural frequencies and vibration modes are determined.The harmonic response analysis is then employed to obtain the amplitude of the needle plate at different frequencies,and the structural weak points of the needle punching machine are identified and improved.The feasibility of the optimized scheme is subsequently reevaluated and verified.The results indicate that the first six natural frequencies of the machine increase,and the maximum amplitude of the needle plate decreases by 70.3%.The enhanced dynamic characteristics of the machine significantly improve its performance,enabling more efficient needle punching of C/C crucible preforms.展开更多
The optimization of turbine blades is crucial in improving the efficiency of wind energy systems and developing clean energy production models.This paper presented a novel approach to the structural design of smallsca...The optimization of turbine blades is crucial in improving the efficiency of wind energy systems and developing clean energy production models.This paper presented a novel approach to the structural design of smallscale turbine blades using the Artificial Bee Colony(ABC)Algorithm based on the stochastic method to optimize both mass and cost(objective functions).The study used computational fluid dynamics(CFD)and structural analysis to consider the fluid-structure interaction.The optimization algorithm defined several variables:structural constraints,the type of composite material,and the number of composite layers to form a mathematical model.The numerical modeling was performed using the Ansys Fluent software and its Fluid-Structure Interaction(FSI)module.The ANSYS Composite PrePost(ACP)advanced composite modeling method was utilized in the structural design of composite materials.This study showed that the structurally optimized small-scale turbine blades provided a sustainable solution with improved efficiency compared to traditional designs.Furthermore,using CFD,structural analysis,and material characterization techniques first considered in this study highlights the importance of considering structural behavior when optimizing turbine blade designs.展开更多
Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fa...Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.展开更多
Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex str...Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.展开更多
The roller is one of the fundamental elements of ore belt conveyor systems since it supports,guides,and directs material on the belt.This component comprises a body(the external tube)that rotates around a fixed shaft ...The roller is one of the fundamental elements of ore belt conveyor systems since it supports,guides,and directs material on the belt.This component comprises a body(the external tube)that rotates around a fixed shaft supported by easels.The external tube and shaft of rollers used in ore conveyor belts are mostly made of steel,resulting in high mass,hindering maintenance and replacement.Aiming to achieve mass reduction,we conducted a structural optimization of a roller with a polymeric external tube(hereafter referred to as a polymeric roller),seeking the optimal values for two design parameters:the inner diameter of the external tube and the shaft diameter.The optimization was constrained by admissible values for maximum stress,maximum deflection and misalignment angle between the shaft and bearings.A finite element model was built in Ansys Workbench to obtain the structural response of the system.The roller considered is composed of an external tube made of high-density polyethylene(HDPE),bearing seats of polyamide 6(PA6),and a steel shaft.To characterize the polymeric materials(HDPE and PA6),stress relaxation tests were conducted,and the data on shear modulus variation over time were inserted into the model to calculate Prony series terms to account for viscoelastic effects.The roller optimization was performed using surrogate modeling based on radial basis functions,with the Globalized Bounded Nelder-Mead(GBNM)algorithm as the optimizer.Two optimization cases were conducted.In the first case,concerning the roller’s initial material settings,the designs found violated the constraints and could not reduce mass.In the second case,by using PA6 in both bearing seats and the tube,a design configuration was found that respected all constraints and reduced the roller mass by 15.5%,equivalent to 5.15 kg.This study is among the first to integrate experimentally obtained viscoelastic data into the surrogate-based optimization of polymeric rollers,combining methodological innovation with industrial relevance.展开更多
Based on the Fluent numerical simulation method,this study systematically analyzed the structural parameters of the spiral tube heat exchanger and the influence of the external baffle on its heat transfer performance....Based on the Fluent numerical simulation method,this study systematically analyzed the structural parameters of the spiral tube heat exchanger and the influence of the external baffle on its heat transfer performance.The results show that when the equivalent diameter of the spiral tube increased from 16.68 to 21.23 mm,its surface heat transfer coefficient decreased from 22,040 to 17,230 W/m^(2)⋅K,and the outlet air temperature dropped from 822.3 to 807.3 K.However,the pressure loss decreased from 2.692 to 0.958 kPa.which reveals the contradiction between the heat transfer efficiency and the flow resistance.By adding a baffle to enhance the turbulent disturbance,the wall heat flux density is increased by 21.17%,the surface heat transfer coefficient is increased by 12.1%,and the outlet temperature is optimized,which verifies the significant improvement of the heat transfer performance by the countercurrent design.Comprehensive research shows that the collaborative optimization of spiral tube equivalent diameter parameters and baffle flow control is the key to improve the comprehensive performance of heat exchanger.Theresearch results provide a theoretical basis for energy-saving design of industrial heat exchangers.展开更多
Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-e...Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-energy rockfall protection remains limited due to their relatively low volumetric energy absorption efficiency and the complex fabrication processes of key energy-absorbing components.To address these limitations,this study proposes a novel sandwich structure incorporating mild steel tubes as core energy absorbers to efficiently mitigate highenergy rockfall impacts.A finite element model was developed in LS-DYNA to systematically investigate the deformation and energy absorption behaviors.Comprehensive parametric analyses were conducted to quantify the effects of key design variables,including tube wall thickness,tube spacing(number of tubes),and infill materials.The results demonstrate that increasing tube wall thickness significantly enhances ultimate energy absorption,with 12-mm-thick tubes absorbing 2.2 times more energy than 6-mm-thick tubes.Lateral constraints induced by adjacent tubes improve specific energy absorption per unit displacement by approximately 30%-45%.Furthermore,incorporating infill materials considerably enhances energy absorption,with aluminum foam infills achieving an 81%increase compared to empty tubes.Nevertheless,higher energy absorption capacity typically leads to greater peak impact forces,increasing the number of tubes offers a better balance between energy absorption and impact force,optimizing the structural performance.These findings provide valuable theoretical insights and practical guidelines for designing sandwich structures in civil and infrastructure engineering applications for effective rockfall protection.展开更多
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
To address the neglect of seismic performance in conventional double-girder bridge crane optimization,this paper introduces a time-history analysis-based seismic optimization methodology for crane structures.Using a 2...To address the neglect of seismic performance in conventional double-girder bridge crane optimization,this paper introduces a time-history analysis-based seismic optimization methodology for crane structures.Using a 25-t nuclear power crane as a case study,a bridge frame finite element model is established and validated through static analysis,confirming its accurate representation of the physical entity’s mechanical behavior.Furthermore,with bridge mass reduction as the objective and structural strength,stiffness,stability,and seismic mechanical performance as constraints,an optimization model is developed employing the Whale Optimization Algorithm(WOA).展开更多
Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimizat...Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimization method grounded in the global adjustment of nodal coordinates.First,a build direction is selected to minimize the number of violating struts.Then,an angular-constraint matrix is assembled from strut direction vectors,and analytical sensitivities with respect to nodal coordinates are derived to enable efficient constrained optimization under nonlinear angular inequality constraints.Numerical studies on two complex curved-surface lattices demonstrate that all overhang violations are eliminated while only minor changes are induced in global stiffness and strength.In particular,the maximum displacement of an ergonomic insole varies by only 2.87%after optimization.The results confirm the method’s versatility and engineering robustness,providing a practical approach for additive manufacturing-oriented lattice structure design.展开更多
To develop herbicides with a novel mechanism of action,a series of 1,3,4-oxadiazolpyridine derivatives were designed and synthesized based on active substructure splicing and structure optimization.These derivatives(5...To develop herbicides with a novel mechanism of action,a series of 1,3,4-oxadiazolpyridine derivatives were designed and synthesized based on active substructure splicing and structure optimization.These derivatives(5aa-5bd)were characterized by their melting points,^(1)H and^(13)C nuclear magnetic resonance spectroscopy,and high-resolution mass spectrometry.The configuration of 5 al was determined using single-crystal X-ray diffraction.Additionally,5 al exhibited excellent herbicidal activity at a dosage of 75 g/hm^(2),showing an EC 50 of 4.03 g/hm^(2)against both E.crus-galli and quinclorac-resistant E.crus-galli.At a dosage of 375 g/hm 2,5 al was safe for application on rice and sorghum and showed low toxicity(>200μg/g)towards Apis mellifera.After treatment with 5 al,the lamellae of the chloroplast grana of barnyard grass leaves were stacked disorderly and arranged loosely,and some thylakoids were broken,as observed by transmission electron microscopy.Transcriptomics analysis of E.crus-galli revealed that 5 al affects the defense response,membranes,plasma membranes,and chloroplasts of differentially expressed genes,which alter membrane permeability and energy metabolism,potentially leading to plant death.Thus,we successfully developed a novel molecular scaffold with a new mechanism of action that exhibits herbicidal activity against resistant E.crus-galli.Therefore,further development of lead herbicides based on this scaffold is required.展开更多
As the central template for protein expression,messenger ribonucleic acid(mRNA)holds immense potential for novel therapeutic strategies.Over the past few decades,mRNA-based therapeutics have demonstrated remarkable ef...As the central template for protein expression,messenger ribonucleic acid(mRNA)holds immense potential for novel therapeutic strategies.Over the past few decades,mRNA-based therapeutics have demonstrated remarkable efficacy in a range of applications,including epidemic vaccine,cancer vaccine,protein replacement therapy,cytokine therapy,cell therapy and gene editing.Due to the inherent instability of mRNA,the rational design of mRNA structure is the prerequisite for therapeutic utility while effective delivery systems are also essential for in vivo applications.This review focuses on the optimization of mRNA structure and highlights key delivery strategies.It also provides a comprehensive overview of the major applications of mRNA-based strategies.In addition,it highlights the persistent challenges in m RNA therapeutics,particularly in terms of stability,immunogenicity,delivery efficiency and safety.By examining recent advances in mRNA design,delivery and application,this review aims to support ongoing research and development in the field of mRNA-based therapeutics.展开更多
Rising global change intensifies water scarcity in China’s vital Yellow River Basin grain region,which mounts the need for precise spatial water management.In this study,we investigated the irrigation water demand fo...Rising global change intensifies water scarcity in China’s vital Yellow River Basin grain region,which mounts the need for precise spatial water management.In this study,we investigated the irrigation water demand for seven major crops in cities at the prefecture level between 2000 and 2019.Using Logarithmic Mean Divisia Index(LMDI)decomposition and k-means clustering,we quantified how yield,area,water use efficiency,and cropping patterns affect water demand and identified five irrigation development clusters.Key water-saving areas were identified by tracking transitions among clusters,and NSGA-II was applied to optimize crop structure.The results revealed that the total irrigation demand in the Yellow River Basin averaged 50.09 billion m3/year,with wheat accounting for 54.7%.The increase in yield and area increased demand by 15.2 and 5.5 billion m3,respectively,which was partly offset by changes in water use efficiency and cropping pattern(−7.0 and−1.8 billion m^(3),respectively).Regions in the upper reaches,particularly within the Lanzhou-Toudaoguai section,were identified as critical for water conservation.Optimization of the cropping structure in key regions can reduce annual irrigation water demand by 280 million m3,which accounts for 4.9%of the total demand in these areas,with minimal impact on crop production.This study provides a spatially explicit basis for targeted water conservation strategies in water-scarce agricultural regions.展开更多
With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competi...With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competitive products.This paper presents a brief description of the current status of structural optimization by reviewing some significant progress made in the last decades.Potential research topics are also discussed.The entire literatures of the field are not covered due to the limitation of the length of paper.The scope of this review is limited and closely related to the authors'own research interests.展开更多
A concept of the independent-continuous topological variable is proposed to establish its corresponding smooth model of structural topological optimization. The method can overcome difficulties that are encountered in...A concept of the independent-continuous topological variable is proposed to establish its corresponding smooth model of structural topological optimization. The method can overcome difficulties that are encountered in conventional models and algorithms for the optimization of the structural topology. Its application to truss topological optimization with stress and displacement constraints is satisfactory, with convergence faster than that of sectional optimizations.展开更多
Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to s...Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.展开更多
In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of sh...In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.展开更多
Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization...Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.52271309Natural Science Foundation of Heilongjiang Province of China under Grant No.YQ2022E104.
文摘Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.
基金Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120funded by the Research Council of Lithuania.
文摘Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.
基金Open Project of Shanghai Key Laboratory of Lightweight Composite,China(No.2232021A4-04)。
文摘Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The intense vibration during needle punching not only generates huge noise,but also substantially reduces the quality of the preform.It is imperative to perform a dynamic analysis and optimization of the entire needle punching machine.In this paper,the three-dimensional(3D)model of the entire double-shaft-driven needle punching machine for C/C crucible preforms is established.Based on the modal analysis theory,the modal characteristics of the needle punching machine under various operating conditions are analyzed and its natural frequencies and vibration modes are determined.The harmonic response analysis is then employed to obtain the amplitude of the needle plate at different frequencies,and the structural weak points of the needle punching machine are identified and improved.The feasibility of the optimized scheme is subsequently reevaluated and verified.The results indicate that the first six natural frequencies of the machine increase,and the maximum amplitude of the needle plate decreases by 70.3%.The enhanced dynamic characteristics of the machine significantly improve its performance,enabling more efficient needle punching of C/C crucible preforms.
基金Scientific Research Projects Unit of Erciyes University under the contract numbers:FDK-2019-8616 and FDK-2025-14774(https://bap.erciyes.edu.tr/,accessed on 12 October 2025)The Scientific and Technological Research Council of Turkey(TUB˙ITAK)for the Doctoral Scholarship for Priority Areas 2211/C for Ramazan OZKAN(https://tubitak.gov.tr,accessed on 12 October 2025).
文摘The optimization of turbine blades is crucial in improving the efficiency of wind energy systems and developing clean energy production models.This paper presented a novel approach to the structural design of smallscale turbine blades using the Artificial Bee Colony(ABC)Algorithm based on the stochastic method to optimize both mass and cost(objective functions).The study used computational fluid dynamics(CFD)and structural analysis to consider the fluid-structure interaction.The optimization algorithm defined several variables:structural constraints,the type of composite material,and the number of composite layers to form a mathematical model.The numerical modeling was performed using the Ansys Fluent software and its Fluid-Structure Interaction(FSI)module.The ANSYS Composite PrePost(ACP)advanced composite modeling method was utilized in the structural design of composite materials.This study showed that the structurally optimized small-scale turbine blades provided a sustainable solution with improved efficiency compared to traditional designs.Furthermore,using CFD,structural analysis,and material characterization techniques first considered in this study highlights the importance of considering structural behavior when optimizing turbine blade designs.
文摘Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.
文摘Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.
基金funded by Vale S.A.company(www.vale.com)and the Institute of Technology Vale(ITV—www.itv.org),grant number SAP 4600048682.
文摘The roller is one of the fundamental elements of ore belt conveyor systems since it supports,guides,and directs material on the belt.This component comprises a body(the external tube)that rotates around a fixed shaft supported by easels.The external tube and shaft of rollers used in ore conveyor belts are mostly made of steel,resulting in high mass,hindering maintenance and replacement.Aiming to achieve mass reduction,we conducted a structural optimization of a roller with a polymeric external tube(hereafter referred to as a polymeric roller),seeking the optimal values for two design parameters:the inner diameter of the external tube and the shaft diameter.The optimization was constrained by admissible values for maximum stress,maximum deflection and misalignment angle between the shaft and bearings.A finite element model was built in Ansys Workbench to obtain the structural response of the system.The roller considered is composed of an external tube made of high-density polyethylene(HDPE),bearing seats of polyamide 6(PA6),and a steel shaft.To characterize the polymeric materials(HDPE and PA6),stress relaxation tests were conducted,and the data on shear modulus variation over time were inserted into the model to calculate Prony series terms to account for viscoelastic effects.The roller optimization was performed using surrogate modeling based on radial basis functions,with the Globalized Bounded Nelder-Mead(GBNM)algorithm as the optimizer.Two optimization cases were conducted.In the first case,concerning the roller’s initial material settings,the designs found violated the constraints and could not reduce mass.In the second case,by using PA6 in both bearing seats and the tube,a design configuration was found that respected all constraints and reduced the roller mass by 15.5%,equivalent to 5.15 kg.This study is among the first to integrate experimentally obtained viscoelastic data into the surrogate-based optimization of polymeric rollers,combining methodological innovation with industrial relevance.
基金supported by the Jing-Jin-Ji Regional Integrated Environmental Improvement-National Science and Technology Major Project(No.2024ZD1200400).
文摘Based on the Fluent numerical simulation method,this study systematically analyzed the structural parameters of the spiral tube heat exchanger and the influence of the external baffle on its heat transfer performance.The results show that when the equivalent diameter of the spiral tube increased from 16.68 to 21.23 mm,its surface heat transfer coefficient decreased from 22,040 to 17,230 W/m^(2)⋅K,and the outlet air temperature dropped from 822.3 to 807.3 K.However,the pressure loss decreased from 2.692 to 0.958 kPa.which reveals the contradiction between the heat transfer efficiency and the flow resistance.By adding a baffle to enhance the turbulent disturbance,the wall heat flux density is increased by 21.17%,the surface heat transfer coefficient is increased by 12.1%,and the outlet temperature is optimized,which verifies the significant improvement of the heat transfer performance by the countercurrent design.Comprehensive research shows that the collaborative optimization of spiral tube equivalent diameter parameters and baffle flow control is the key to improve the comprehensive performance of heat exchanger.Theresearch results provide a theoretical basis for energy-saving design of industrial heat exchangers.
基金supported by the National Key R&D Program of China(Grant No.2019YFC1509703)the Tianjin Science and Technology Program Project(Grant No.23YFYSHZ00130)。
文摘Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-energy rockfall protection remains limited due to their relatively low volumetric energy absorption efficiency and the complex fabrication processes of key energy-absorbing components.To address these limitations,this study proposes a novel sandwich structure incorporating mild steel tubes as core energy absorbers to efficiently mitigate highenergy rockfall impacts.A finite element model was developed in LS-DYNA to systematically investigate the deformation and energy absorption behaviors.Comprehensive parametric analyses were conducted to quantify the effects of key design variables,including tube wall thickness,tube spacing(number of tubes),and infill materials.The results demonstrate that increasing tube wall thickness significantly enhances ultimate energy absorption,with 12-mm-thick tubes absorbing 2.2 times more energy than 6-mm-thick tubes.Lateral constraints induced by adjacent tubes improve specific energy absorption per unit displacement by approximately 30%-45%.Furthermore,incorporating infill materials considerably enhances energy absorption,with aluminum foam infills achieving an 81%increase compared to empty tubes.Nevertheless,higher energy absorption capacity typically leads to greater peak impact forces,increasing the number of tubes offers a better balance between energy absorption and impact force,optimizing the structural performance.These findings provide valuable theoretical insights and practical guidelines for designing sandwich structures in civil and infrastructure engineering applications for effective rockfall protection.
基金supported by Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
文摘To address the neglect of seismic performance in conventional double-girder bridge crane optimization,this paper introduces a time-history analysis-based seismic optimization methodology for crane structures.Using a 25-t nuclear power crane as a case study,a bridge frame finite element model is established and validated through static analysis,confirming its accurate representation of the physical entity’s mechanical behavior.Furthermore,with bridge mass reduction as the objective and structural strength,stiffness,stability,and seismic mechanical performance as constraints,an optimization model is developed employing the Whale Optimization Algorithm(WOA).
基金supported by the National Natural Science Foundation of China(Grant Nos.12432005 and 12472116)the Fundamental Research Funds for the Central Universities(DUTZD25240).
文摘Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimization method grounded in the global adjustment of nodal coordinates.First,a build direction is selected to minimize the number of violating struts.Then,an angular-constraint matrix is assembled from strut direction vectors,and analytical sensitivities with respect to nodal coordinates are derived to enable efficient constrained optimization under nonlinear angular inequality constraints.Numerical studies on two complex curved-surface lattices demonstrate that all overhang violations are eliminated while only minor changes are induced in global stiffness and strength.In particular,the maximum displacement of an ergonomic insole varies by only 2.87%after optimization.The results confirm the method’s versatility and engineering robustness,providing a practical approach for additive manufacturing-oriented lattice structure design.
基金supported by the National Key Research and Development Program of China(2023YFD1400504)Natural Science Foundation of Hunan Province(2024JJ2036)+3 种基金Natural Science Foundation of China(32172433)Foundation for Tobacco Science of China National Tobacco Corporation(110202401015,(LS-05))Scientific-Innovative of Hunan Agricultural Sciences and Technology(2024CX69)China Agriculture Research System of MOF and MARA(CARS-16-E19)。
文摘To develop herbicides with a novel mechanism of action,a series of 1,3,4-oxadiazolpyridine derivatives were designed and synthesized based on active substructure splicing and structure optimization.These derivatives(5aa-5bd)were characterized by their melting points,^(1)H and^(13)C nuclear magnetic resonance spectroscopy,and high-resolution mass spectrometry.The configuration of 5 al was determined using single-crystal X-ray diffraction.Additionally,5 al exhibited excellent herbicidal activity at a dosage of 75 g/hm^(2),showing an EC 50 of 4.03 g/hm^(2)against both E.crus-galli and quinclorac-resistant E.crus-galli.At a dosage of 375 g/hm 2,5 al was safe for application on rice and sorghum and showed low toxicity(>200μg/g)towards Apis mellifera.After treatment with 5 al,the lamellae of the chloroplast grana of barnyard grass leaves were stacked disorderly and arranged loosely,and some thylakoids were broken,as observed by transmission electron microscopy.Transcriptomics analysis of E.crus-galli revealed that 5 al affects the defense response,membranes,plasma membranes,and chloroplasts of differentially expressed genes,which alter membrane permeability and energy metabolism,potentially leading to plant death.Thus,we successfully developed a novel molecular scaffold with a new mechanism of action that exhibits herbicidal activity against resistant E.crus-galli.Therefore,further development of lead herbicides based on this scaffold is required.
基金supported by the National Key Research and Development Program of China(No.2023YFA0915400)the National Natural Science Foundation of China(No.22277072,22407099 and 32401161)+3 种基金Shanghai Oriental Talents(QNWS2024055)Shanghai Municipal Science and Technology Commission(No.24ZR1462700)the Science and Technology Development Fund of Pudong Health Bureau of Shanghai(No.PKJ2024-Y40)“Clinic Plus”Outstanding Project(No.2021ZYB009 and No.2021ZYB003)from Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine,and Innovative research team of high-level local universities in Shanghai。
文摘As the central template for protein expression,messenger ribonucleic acid(mRNA)holds immense potential for novel therapeutic strategies.Over the past few decades,mRNA-based therapeutics have demonstrated remarkable efficacy in a range of applications,including epidemic vaccine,cancer vaccine,protein replacement therapy,cytokine therapy,cell therapy and gene editing.Due to the inherent instability of mRNA,the rational design of mRNA structure is the prerequisite for therapeutic utility while effective delivery systems are also essential for in vivo applications.This review focuses on the optimization of mRNA structure and highlights key delivery strategies.It also provides a comprehensive overview of the major applications of mRNA-based strategies.In addition,it highlights the persistent challenges in m RNA therapeutics,particularly in terms of stability,immunogenicity,delivery efficiency and safety.By examining recent advances in mRNA design,delivery and application,this review aims to support ongoing research and development in the field of mRNA-based therapeutics.
基金National Natural Science Foundation of China,No.42041007。
文摘Rising global change intensifies water scarcity in China’s vital Yellow River Basin grain region,which mounts the need for precise spatial water management.In this study,we investigated the irrigation water demand for seven major crops in cities at the prefecture level between 2000 and 2019.Using Logarithmic Mean Divisia Index(LMDI)decomposition and k-means clustering,we quantified how yield,area,water use efficiency,and cropping patterns affect water demand and identified five irrigation development clusters.Key water-saving areas were identified by tracking transitions among clusters,and NSGA-II was applied to optimize crop structure.The results revealed that the total irrigation demand in the Yellow River Basin averaged 50.09 billion m3/year,with wheat accounting for 54.7%.The increase in yield and area increased demand by 15.2 and 5.5 billion m3,respectively,which was partly offset by changes in water use efficiency and cropping pattern(−7.0 and−1.8 billion m^(3),respectively).Regions in the upper reaches,particularly within the Lanzhou-Toudaoguai section,were identified as critical for water conservation.Optimization of the cropping structure in key regions can reduce annual irrigation water demand by 280 million m3,which accounts for 4.9%of the total demand in these areas,with minimal impact on crop production.This study provides a spatially explicit basis for targeted water conservation strategies in water-scarce agricultural regions.
基金supported by the National Natural Science Foundation of China(10472022,10925209,90816025,10802016 and 10902018)the 973 Program of China(2010CB832703).
文摘With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competitive products.This paper presents a brief description of the current status of structural optimization by reviewing some significant progress made in the last decades.Potential research topics are also discussed.The entire literatures of the field are not covered due to the limitation of the length of paper.The scope of this review is limited and closely related to the authors'own research interests.
基金The project supported by State Key Laboratory of Structural Analyses of Industrial Equipment
文摘A concept of the independent-continuous topological variable is proposed to establish its corresponding smooth model of structural topological optimization. The method can overcome difficulties that are encountered in conventional models and algorithms for the optimization of the structural topology. Its application to truss topological optimization with stress and displacement constraints is satisfactory, with convergence faster than that of sectional optimizations.
文摘Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.
基金Supported by the Project of Ministry of Education and Finance (No.200512)the Project of the State Key Laboratory of Ocean Engineering (GKZD010053-10)
文摘In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.
基金supported by National Natural Science Foundation of China(Grant No.51175086)
文摘Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.
