Surface morphology of Ceratocanthus beetle elytra was investigated for spike surface texture and its geometry using Scanning Electron Microscopy(SEM).Material properties were analyzed for both surface and cross-sectio...Surface morphology of Ceratocanthus beetle elytra was investigated for spike surface texture and its geometry using Scanning Electron Microscopy(SEM).Material properties were analyzed for both surface and cross-section of elytra using nano-indentation technique.The spike texture was significantly rigid compared with the non-textured zone;a bi-layer system of E and H was identified at the elytra cross-section.Normal load acting on spike texture during free-fall conditions was estimated analytically and deflection equation was derived.The design of spike texture with conical base was studied for minimization of deflection and volume using the Non-dominated Sorting Genetic Algorithm(NSGA-II)optimization technique,confirming the smart design of the natural solution.The frictional behavior of elytra was studied using fundamental tribology test and the role of the oriented spike texture was investigated for frictional anisotropy.Compression resistance of full beetle was evaluated for both conglobated and non-conglobated configuration and tensile strengths were compared using Brazilian test.Puncture and wear resistance of full elytra were characterized and correlated with its defense mechanism.展开更多
The rapid advancement of three-dimensional printed concrete(3DPC)requires intelligent and interpretable frameworks to optimize mixture design for strength,printability,and sustainability.While machine learning(ML)mode...The rapid advancement of three-dimensional printed concrete(3DPC)requires intelligent and interpretable frameworks to optimize mixture design for strength,printability,and sustainability.While machine learning(ML)models have improved predictive accuracy,their limited transparency has hindered their widespread adoption in materials engineering.To overcome this barrier,this study introduces a Random Forests ensemble learning model integrated with SHapley Additive exPlanations(SHAP)and Partial Dependence Plots(PDPs)to model and explain the compressive strength behavior of 3DPC mixtures.Unlike conventional“black-box”models,SHAP quantifies each variable’s contribution to predictions based on cooperative game theory,which enables causal interpretability,whereas PDP visualizes nonlinear and interactive effects between features that offer practical mix design insights.A systematically optimized random forest model achieved strong generalization(R2=0.978 for training,0.834 for validation,and 0.868 for testing).The analysis identified curing age,Portland cement,silica fume,and the water-tobinder ratio as dominant predictors,with curing age exerting the highest positive influence on strength development.The integrated SHAP-PDP framework revealed synergistic interactions among binder constituents and curing parameters,which established transparent,data-driven guidelines for performance optimization.Theoretically,the study advances explainable artificial intelligence in cementitious material science by linking microstructural mechanisms to model-based reasoning,thereby enhancing both the interpretability and applicability of ML-driven mix design for next-generation 3DPC systems.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overco...Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overcoming resistance in granular media when burrowing with forelimbs.In the absence of effective forepaw design strategies,most robotic designs rely on increased power to enhance performance.To address this issue,this paper employs Resistive Force Theory to optimize mole-inspired forepaws,aiming to enhance burrowing efficiency.By analyzing the relationship between geometric parameters and burrowing forces,we propose several forepaw design variations.Through granular resistance assessments,an effective forepaw configuration is identified and further refined using parameters such as longitudinal and transverse curvature.Subsequently,the Particle Swarm Optimization algorithm is applied to determine the optimal forepaw design.In force-loading tests,the optimized forepaw demonstrated a 79.44%reduction in granular lift force and a 22.55%increase in propulsive force compared with the control group.In robotic burrowing experiments,the optimized forepaw achieved the longest burrow displacement(179.528 mm)and the lowest burrowing lift force(0.9355 mm/s),verifying its effectiveness in reducing the lift force and enhancing the propulsive force.展开更多
It is known that structural optimization may lead to designs of structures having low stability and sometimes even kinematically unstable designs. This paper presents a robust design method for improving the stability...It is known that structural optimization may lead to designs of structures having low stability and sometimes even kinematically unstable designs. This paper presents a robust design method for improving the stability of opti mized structures. A new approach is proposed, in which cer tain perturbation loads are introduced and the corresponding compliance is added to the objective function as a penaliza tion. The stability of the optimized structures can thus be improved substantially by considering structural responses to the original and the introduced loads. Numerical exam ples show the simplicity and effectiveness of the proposed method.展开更多
Laminated composite is a new type of composite structure which is used to improve the fracture toughness and flexure strength and is good for optimizing the mechanical properties of intermetallics. On the basis of bio...Laminated composite is a new type of composite structure which is used to improve the fracture toughness and flexure strength and is good for optimizing the mechanical properties of intermetallics. On the basis of bionic principle, the optimized design (via establishing the mathematical model, stress intensity factor K_Ⅰ was computed by the finite element method) of Ti/TiAl laminated composite was studied by varying the thickness ratio and layer amounts, then the raw materials of Ti and TiAl were evaporated and deposited alternatively to form laminated metal/intermetallic composites in vacuum chamber by electron beam physical vapor deposition method. The results show that the toughness of TiAl is improved and agrees well with theoretical analysis.展开更多
In this paper,a design is presented for a high-speed,high-power motor for a four-legged robot actuator that was optimized using the weighted sum method(WSM)based on the Taguchi method,and the response surface method(R...In this paper,a design is presented for a high-speed,high-power motor for a four-legged robot actuator that was optimized using the weighted sum method(WSM)based on the Taguchi method,and the response surface method(RSM).First,output torque,torque constant,torque ripple,and efficiency were selected as objective functions for the optimized design.The sampling method was implemented to use a mixed orthogonal array and the single response characteristics of each objective function were compared using the Taguchi method.Moreover,to consider the multi-response characteristic of the objective functions,WSM was applied.Second,the 2D finite element analysis result of the RSM was compared with that using the WSM.Finally,an experiment was carried out on the manufactured motor and the optimized model is presented here.展开更多
The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the rel...The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.展开更多
In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-p...In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.展开更多
Pump chambers, normally used as dominant structures in mining engineering to insure the safety and production of un-derground coal mines, become generally deformed under conditions of deep mining. Given the geology an...Pump chambers, normally used as dominant structures in mining engineering to insure the safety and production of un-derground coal mines, become generally deformed under conditions of deep mining. Given the geology and engineering condition of Qishan Coal Mine in Xuzhou, the failure characteristics of pump chambers at the –1000 m level show that the main cause can be attributed to the spatial effect induced by intersectional chambers, where one pump is constructed per well. We developed an opti-mized design of the pump room, in which the pump wells in the traditional design are integrated into one compounding well. We suggest that the new design can limit the spatial effect of intersectional chambers during construction given our relevant numerical simulation. The new design is able to simplify the structure of the pump chamber and reduce the amount of excavation required. Based on a bolt-mesh-anchor with a rigid gap coupling supporting technology, the stability of pump chamber can be improved greatly.展开更多
The vacuum vessel of the HT-7U superconducting tokamak will be a fully-welded structure with a double-wall. The space between the double-wall will be filled with borated water for neutron shielding. Non-circular cross...The vacuum vessel of the HT-7U superconducting tokamak will be a fully-welded structure with a double-wall. The space between the double-wall will be filled with borated water for neutron shielding. Non-circular cross-section is designed for plasma elongating. Horizontal and vertical ports are designed for diagnosing, vacuum pumping, plasma heating and plasma current driving, etc. The vacuum vessel consists of 16 segments. It will be baked out at 250℃ to obtain a clean wall. When the machine is in operation, both the hot wall (the wall temperature is around 100℃) and the cold wall (wall temperature is in normal equilibrium) are considered. The stress caused by thermal deformation and the electromagnetic (EM) loads caused by 1.5 MA plasma disruption in 3.5 T magnetic field have to be taken into account in the design of the HT-7U vacuum vessel Finite element method was employed for structure analysis of the vacuum vessel.展开更多
Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while...Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.展开更多
The use of microalgae to recover nitrogen and phosphorus from wastewater has garnered significant attention,positioning it as one of the most promising and sustainable strategies in modern wastewater treatment.While v...The use of microalgae to recover nitrogen and phosphorus from wastewater has garnered significant attention,positioning it as one of the most promising and sustainable strategies in modern wastewater treatment.While various photobioreactors(PBRs)configurations have been widely applied for microalgae cultivation,limited research has focused on optimizing PBR design specificallyto enhance nitrogen and phosphorus removal efficiency.The high operational costs of wastewater treatment,combined with the inherent variability of microalgal growth,have prompted the search for advanced solutions that improve nitrogen and phosphorus removal while minimizing resource consumption and enabling predictive process control.Recently,the integration of PBR systems with artificialintelligence and machine learning(AI/ML)modeling has emerged as a transformative approach to enhancing nutrient removal,particularly for nitrogen and phosphorus.This study firstsummarizes existing PBR designs tailored for diverse applications,then outlines strategies for system enhancement through the optimization of mixing methods,construction materials,light intensity,and light source configuration.Furthermore,computational fluiddynamics(CFD)and AI/ML modeling are presented as tools to guide the structural design and operational optimization of microalgae-based nitrogen and phosphorus removal processes.Finally,future research directions and key challenges are discussed.展开更多
Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is...Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.展开更多
Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These ...Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These challenges highlight the need for more precise and efficient design methodologies to ensure structural stability and economic feasibility.This research proposes an innovative automatic optimization inverse design method(AOIDM)that integrates an enhanced genetic algorithm(EGA)with a multiobjective optimization model.By combining advanced computational techniques with engineering principles,this approach improves search efficiency by 30%and enhances deformation control accuracy by 25%.Additionally,the approach exhibits potential for reducing carbon emissions to align with sustainable engineering goals.The effectiveness of this approach was validated through comprehensive data analysis and practical case studies,demonstrating its ability to optimize retaining structure designs under complex asymmetric loading conditions.This research establishes a new standard for precision and efficiency in automated excavation design,with accompanying improvements in safety and cost-effectiveness.Furthermore,it lays the foundation for future geotechnical engineering advancements,offering a robust solution to one of the most challenging aspects of modern excavation projects.展开更多
The application of Low Earth Orbit(LEO)satellite navigation can enhance geometric structure,increase observations and contribute to navigation and positioning.To improve the performance of the navigation constellation...The application of Low Earth Orbit(LEO)satellite navigation can enhance geometric structure,increase observations and contribute to navigation and positioning.To improve the performance of the navigation constellation in China,this study proposes an optimized method of LEO-enhanced navigation constellation for BDS based on Bayesian optimization algorithm.In this paper,four different optimal LEO constellation configurations are designed,and their enhancements to BDS3 navigation performance are analyzed,including Geometric Dilution of Precision(GDOP),the numbers of visible satellites,and the rapid convergence of precision point positioning(PPP).Additionally,the enhancement advantages in China compared to other regions are further discussed.The results demonstrate that regional enhanced constellations with 70,72,80,and 81 satellites at an altitude of 1000 km can significantly improve the navigation performance of the navigation constellation.Globally,the addition of optimized LEO constellations has reduced the hybrid constellation GDOP by 19.0%,18.3%,19.9%,and 20.3%.Similar results can be obtained using the genetic algorithm(GA),but the computational efficiency of Bayesian optimization algorithm is 53.9%higher than that of the genetic algorithm.The number of visible satellites of enhanced constellations in China has increased by more than four on average,which is better than that in other regions.In the PPP experiment,the convergence time of the stations in China and other regions is shortened by 83.0%and 76.2%,respectively,and the navigation performance of hybrid constellations in China is better.展开更多
Placement optimization is a crucial phase in chip design,involving the strategic arrangement of cells within a limited region to enhance space utilization and reduce wirelength.Chip design enterprises need to optimize...Placement optimization is a crucial phase in chip design,involving the strategic arrangement of cells within a limited region to enhance space utilization and reduce wirelength.Chip design enterprises need to optimize the placement according to design rules to meet customer demands.While mixed-cell-height circuits are widely used in modern chip design,few studies have simultaneously considered the non-overlapping cells,rails alignment,and minimum implantation area constraints in the placement optimization problems.Hence,this study involves preprocessing the non-linear parts and developing a mixed-integer linear programming model to reduce the cost of legalizing chip placements for businesses.Furthermore,this study designs and implements an exact algorithm based on Benders decomposition,utilizing dual theory to obtain an optimal cut and iteratively solve for the coordinates of cells.Numerical experiments across various scales validate the performance of the algorithm.Through a detailed analysis of the shape of the chip region division,the proportion of different types of cells,the total number of cells and bins,and their impact on the placement,we derive some potentially useful design insights that can benefit chip design enterprises.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
The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the to...The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the towing force of a vessel. A multi-objective genetic algorithm based on analytical models of the plow surface has been examined and applied in efforts to obtain optimal design of the plow. For a specific soil condition, the draft force and moldboard surface area which are the key parameters in the working process of the plow are optimized by finding the corresponding optimal values of the plow blade penetration angle and two surface angles of the main cutting blade of the plow. Parameters such as the moldboard side angle of deviation, moldboard lift angle, angular variation of the tangent line, and the spanning length are also analyzed with respect to the force of the moldboard surface along soil flow direction. Results show that the optimized plow has an improved plow performance. The draft forces of the main cutting blade and the moldboard are 10.6% and 7%, respectively, less than the original design. The standard deviation of Gaussian curvature of moldboard is lowered by 64.5%, which implies that the smoothness of the optimized moldboard surface is much greater than the original.展开更多
Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, hold...Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.展开更多
基金supported by Ministero Universitàe Ricerca(MUR-PRIN 20222022ATZCJN AMPHYBIA)CUP N.E53D23003040006Ministero dell'istruzione dell'universitàe della ricerca(MIUR-PON 2018 PROSCAN)CUP N.E96C18000440008European Union NextGenerationEU PNRR Spoke 7 CN00000013 HPC CUP N.E63C22000970007.
文摘Surface morphology of Ceratocanthus beetle elytra was investigated for spike surface texture and its geometry using Scanning Electron Microscopy(SEM).Material properties were analyzed for both surface and cross-section of elytra using nano-indentation technique.The spike texture was significantly rigid compared with the non-textured zone;a bi-layer system of E and H was identified at the elytra cross-section.Normal load acting on spike texture during free-fall conditions was estimated analytically and deflection equation was derived.The design of spike texture with conical base was studied for minimization of deflection and volume using the Non-dominated Sorting Genetic Algorithm(NSGA-II)optimization technique,confirming the smart design of the natural solution.The frictional behavior of elytra was studied using fundamental tribology test and the role of the oriented spike texture was investigated for frictional anisotropy.Compression resistance of full beetle was evaluated for both conglobated and non-conglobated configuration and tensile strengths were compared using Brazilian test.Puncture and wear resistance of full elytra were characterized and correlated with its defense mechanism.
基金supported by the Ongoing Research Funding Program(Grant No.ORFFT-2025-025-4)at King Saud University,Riyadh,Saudi Arabia.The grant was awarded to Yassir M.Abbas。
文摘The rapid advancement of three-dimensional printed concrete(3DPC)requires intelligent and interpretable frameworks to optimize mixture design for strength,printability,and sustainability.While machine learning(ML)models have improved predictive accuracy,their limited transparency has hindered their widespread adoption in materials engineering.To overcome this barrier,this study introduces a Random Forests ensemble learning model integrated with SHapley Additive exPlanations(SHAP)and Partial Dependence Plots(PDPs)to model and explain the compressive strength behavior of 3DPC mixtures.Unlike conventional“black-box”models,SHAP quantifies each variable’s contribution to predictions based on cooperative game theory,which enables causal interpretability,whereas PDP visualizes nonlinear and interactive effects between features that offer practical mix design insights.A systematically optimized random forest model achieved strong generalization(R2=0.978 for training,0.834 for validation,and 0.868 for testing).The analysis identified curing age,Portland cement,silica fume,and the water-tobinder ratio as dominant predictors,with curing age exerting the highest positive influence on strength development.The integrated SHAP-PDP framework revealed synergistic interactions among binder constituents and curing parameters,which established transparent,data-driven guidelines for performance optimization.Theoretically,the study advances explainable artificial intelligence in cementitious material science by linking microstructural mechanisms to model-based reasoning,thereby enhancing both the interpretability and applicability of ML-driven mix design for next-generation 3DPC systems.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金financially supported in-part by the National Natural Science Foundation of China(52275011)the Natural Science Foundation of Guangdong Province(2023B1515020080)+3 种基金the Natural Science Foundation of Guangzhou(2024A04J2552)the Fundamental Research Funds for the Central Universities,the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(CAST)(2021QNRC001)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011253)the Higher Education Institution Featured Innovation Project of Department of Education of Guangdong Province(GrantNo.2023KTSCX138).
文摘Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overcoming resistance in granular media when burrowing with forelimbs.In the absence of effective forepaw design strategies,most robotic designs rely on increased power to enhance performance.To address this issue,this paper employs Resistive Force Theory to optimize mole-inspired forepaws,aiming to enhance burrowing efficiency.By analyzing the relationship between geometric parameters and burrowing forces,we propose several forepaw design variations.Through granular resistance assessments,an effective forepaw configuration is identified and further refined using parameters such as longitudinal and transverse curvature.Subsequently,the Particle Swarm Optimization algorithm is applied to determine the optimal forepaw design.In force-loading tests,the optimized forepaw demonstrated a 79.44%reduction in granular lift force and a 22.55%increase in propulsive force compared with the control group.In robotic burrowing experiments,the optimized forepaw achieved the longest burrow displacement(179.528 mm)and the lowest burrowing lift force(0.9355 mm/s),verifying its effectiveness in reducing the lift force and enhancing the propulsive force.
基金supported by State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian University of Technology,China(GZ1305)the National Natural Science Foundation of China(11002058 and 11372004)
文摘It is known that structural optimization may lead to designs of structures having low stability and sometimes even kinematically unstable designs. This paper presents a robust design method for improving the stability of opti mized structures. A new approach is proposed, in which cer tain perturbation loads are introduced and the corresponding compliance is added to the objective function as a penaliza tion. The stability of the optimized structures can thus be improved substantially by considering structural responses to the original and the introduced loads. Numerical exam ples show the simplicity and effectiveness of the proposed method.
文摘Laminated composite is a new type of composite structure which is used to improve the fracture toughness and flexure strength and is good for optimizing the mechanical properties of intermetallics. On the basis of bionic principle, the optimized design (via establishing the mathematical model, stress intensity factor K_Ⅰ was computed by the finite element method) of Ti/TiAl laminated composite was studied by varying the thickness ratio and layer amounts, then the raw materials of Ti and TiAl were evaporated and deposited alternatively to form laminated metal/intermetallic composites in vacuum chamber by electron beam physical vapor deposition method. The results show that the toughness of TiAl is improved and agrees well with theoretical analysis.
基金supported by the Industrial Strategic Technology Development Program(10070171,Development of core technology for advanced locomotion/manipulation based on high-speed/power robot platform and robot intelligence)funded By the Ministry of Trade,Industry&Energy(MI,Korea).
文摘In this paper,a design is presented for a high-speed,high-power motor for a four-legged robot actuator that was optimized using the weighted sum method(WSM)based on the Taguchi method,and the response surface method(RSM).First,output torque,torque constant,torque ripple,and efficiency were selected as objective functions for the optimized design.The sampling method was implemented to use a mixed orthogonal array and the single response characteristics of each objective function were compared using the Taguchi method.Moreover,to consider the multi-response characteristic of the objective functions,WSM was applied.Second,the 2D finite element analysis result of the RSM was compared with that using the WSM.Finally,an experiment was carried out on the manufactured motor and the optimized model is presented here.
基金supported by the Education and Teaching Research Project of Universities in Fujian Province(FBJY20230167).
文摘The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.
文摘In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.
基金supported by the Major Project of the National Basic Research Program of China (No2006CB202200)the Program for New Century Excellent Talents in Uni-versity (NoNCET07-0800)the Special Fund for Basic Research and Operating Expenses of the China University of Mining & Technology, Beijing and the Academician workstation in enterprise of Jiangsu Province (No.BM2009563)
文摘Pump chambers, normally used as dominant structures in mining engineering to insure the safety and production of un-derground coal mines, become generally deformed under conditions of deep mining. Given the geology and engineering condition of Qishan Coal Mine in Xuzhou, the failure characteristics of pump chambers at the –1000 m level show that the main cause can be attributed to the spatial effect induced by intersectional chambers, where one pump is constructed per well. We developed an opti-mized design of the pump room, in which the pump wells in the traditional design are integrated into one compounding well. We suggest that the new design can limit the spatial effect of intersectional chambers during construction given our relevant numerical simulation. The new design is able to simplify the structure of the pump chamber and reduce the amount of excavation required. Based on a bolt-mesh-anchor with a rigid gap coupling supporting technology, the stability of pump chamber can be improved greatly.
文摘The vacuum vessel of the HT-7U superconducting tokamak will be a fully-welded structure with a double-wall. The space between the double-wall will be filled with borated water for neutron shielding. Non-circular cross-section is designed for plasma elongating. Horizontal and vertical ports are designed for diagnosing, vacuum pumping, plasma heating and plasma current driving, etc. The vacuum vessel consists of 16 segments. It will be baked out at 250℃ to obtain a clean wall. When the machine is in operation, both the hot wall (the wall temperature is around 100℃) and the cold wall (wall temperature is in normal equilibrium) are considered. The stress caused by thermal deformation and the electromagnetic (EM) loads caused by 1.5 MA plasma disruption in 3.5 T magnetic field have to be taken into account in the design of the HT-7U vacuum vessel Finite element method was employed for structure analysis of the vacuum vessel.
基金supported by the Postdoctoral Fellowship Program of CPSF(Grant No.GZC20242194)the National Natural Science Foundation of China(Grant Nos.52175251 and 52205268)+1 种基金the Industry Key Technology Research Fund Project of Northwestern Polytechnical University(Grant No.HYGJXM202318)the National Basic Scientific Research Program(Grant No.JCKY2021206B005).
文摘Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.
基金supported by the National Natural Science Foundation of China(22038012,U24A20543)the Science and Technology Pro-gram of Fujian Province,China(2025Y4001).
文摘The use of microalgae to recover nitrogen and phosphorus from wastewater has garnered significant attention,positioning it as one of the most promising and sustainable strategies in modern wastewater treatment.While various photobioreactors(PBRs)configurations have been widely applied for microalgae cultivation,limited research has focused on optimizing PBR design specificallyto enhance nitrogen and phosphorus removal efficiency.The high operational costs of wastewater treatment,combined with the inherent variability of microalgal growth,have prompted the search for advanced solutions that improve nitrogen and phosphorus removal while minimizing resource consumption and enabling predictive process control.Recently,the integration of PBR systems with artificialintelligence and machine learning(AI/ML)modeling has emerged as a transformative approach to enhancing nutrient removal,particularly for nitrogen and phosphorus.This study firstsummarizes existing PBR designs tailored for diverse applications,then outlines strategies for system enhancement through the optimization of mixing methods,construction materials,light intensity,and light source configuration.Furthermore,computational fluiddynamics(CFD)and AI/ML modeling are presented as tools to guide the structural design and operational optimization of microalgae-based nitrogen and phosphorus removal processes.Finally,future research directions and key challenges are discussed.
基金National Natural Science Foundation of China under Grant No.52278490。
文摘Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3009400)the National Natural Science Foundation of China(Grant Nos.52238009 and 52208344).
文摘Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These challenges highlight the need for more precise and efficient design methodologies to ensure structural stability and economic feasibility.This research proposes an innovative automatic optimization inverse design method(AOIDM)that integrates an enhanced genetic algorithm(EGA)with a multiobjective optimization model.By combining advanced computational techniques with engineering principles,this approach improves search efficiency by 30%and enhances deformation control accuracy by 25%.Additionally,the approach exhibits potential for reducing carbon emissions to align with sustainable engineering goals.The effectiveness of this approach was validated through comprehensive data analysis and practical case studies,demonstrating its ability to optimize retaining structure designs under complex asymmetric loading conditions.This research establishes a new standard for precision and efficiency in automated excavation design,with accompanying improvements in safety and cost-effectiveness.Furthermore,it lays the foundation for future geotechnical engineering advancements,offering a robust solution to one of the most challenging aspects of modern excavation projects.
基金founded by the National Natural Science Foundation of China(42030109)the Startup Foundation for Doctors of Liaoning Province(2021-BS-275)+4 种基金the Scientific Study Project for Institutes of Higher LearningMinistry of EducationLiaoning Province(LJKMZ20220673)the Project supported by the State Key Laboratory of Geodesy and Earths'DynamicsInnovation Academy for Precision Measurement Science and Technology(SKLGED2023-3-2)。
文摘The application of Low Earth Orbit(LEO)satellite navigation can enhance geometric structure,increase observations and contribute to navigation and positioning.To improve the performance of the navigation constellation in China,this study proposes an optimized method of LEO-enhanced navigation constellation for BDS based on Bayesian optimization algorithm.In this paper,four different optimal LEO constellation configurations are designed,and their enhancements to BDS3 navigation performance are analyzed,including Geometric Dilution of Precision(GDOP),the numbers of visible satellites,and the rapid convergence of precision point positioning(PPP).Additionally,the enhancement advantages in China compared to other regions are further discussed.The results demonstrate that regional enhanced constellations with 70,72,80,and 81 satellites at an altitude of 1000 km can significantly improve the navigation performance of the navigation constellation.Globally,the addition of optimized LEO constellations has reduced the hybrid constellation GDOP by 19.0%,18.3%,19.9%,and 20.3%.Similar results can be obtained using the genetic algorithm(GA),but the computational efficiency of Bayesian optimization algorithm is 53.9%higher than that of the genetic algorithm.The number of visible satellites of enhanced constellations in China has increased by more than four on average,which is better than that in other regions.In the PPP experiment,the convergence time of the stations in China and other regions is shortened by 83.0%and 76.2%,respectively,and the navigation performance of hybrid constellations in China is better.
基金supported by the National Natural Science Foundation of China(72025103,72394360,72394362,and 72361137001)the Project of Science and Technology Commission of Shanghai Municipality,China(23JC1402200).
文摘Placement optimization is a crucial phase in chip design,involving the strategic arrangement of cells within a limited region to enhance space utilization and reduce wirelength.Chip design enterprises need to optimize the placement according to design rules to meet customer demands.While mixed-cell-height circuits are widely used in modern chip design,few studies have simultaneously considered the non-overlapping cells,rails alignment,and minimum implantation area constraints in the placement optimization problems.Hence,this study involves preprocessing the non-linear parts and developing a mixed-integer linear programming model to reduce the cost of legalizing chip placements for businesses.Furthermore,this study designs and implements an exact algorithm based on Benders decomposition,utilizing dual theory to obtain an optimal cut and iteratively solve for the coordinates of cells.Numerical experiments across various scales validate the performance of the algorithm.Through a detailed analysis of the shape of the chip region division,the proportion of different types of cells,the total number of cells and bins,and their impact on the placement,we derive some potentially useful design insights that can benefit chip design enterprises.
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.
基金Supported the National Natural Science Foundation of China （No. 51179040） Natural Science Foundation of Heilongjiang Province （No. E200904）
文摘The plow of the submarine plowing trencher is one of the main functional mechanisms, and its optimization is very important. The design parameters play a very significant role in determining the requirements of the towing force of a vessel. A multi-objective genetic algorithm based on analytical models of the plow surface has been examined and applied in efforts to obtain optimal design of the plow. For a specific soil condition, the draft force and moldboard surface area which are the key parameters in the working process of the plow are optimized by finding the corresponding optimal values of the plow blade penetration angle and two surface angles of the main cutting blade of the plow. Parameters such as the moldboard side angle of deviation, moldboard lift angle, angular variation of the tangent line, and the spanning length are also analyzed with respect to the force of the moldboard surface along soil flow direction. Results show that the optimized plow has an improved plow performance. The draft forces of the main cutting blade and the moldboard are 10.6% and 7%, respectively, less than the original design. The standard deviation of Gaussian curvature of moldboard is lowered by 64.5%, which implies that the smoothness of the optimized moldboard surface is much greater than the original.
基金supported by the Fundamental Research Funds for the Central Universities(No.30922010719).
文摘Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.
