In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket M...In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.展开更多
This paper proposes a hybrid architecture based on Multi-disciplinary Design Optimization(MDO) with the Variable Complexity Modeling(VCM) method, to solve the problem of general design optimization for a stratosphere ...This paper proposes a hybrid architecture based on Multi-disciplinary Design Optimization(MDO) with the Variable Complexity Modeling(VCM) method, to solve the problem of general design optimization for a stratosphere airship. Firstly, MDO based on the Concurrent SubSpace Optimization(CSSO) strategy is improved for handling the subsystem coupling problem in stratosphere airship design which contains aerodynamics, structure, and energy. Secondly, the VCM method based on the surrogate model is presented for reducing the computational complexity in high-fidelity modeling without loss of accuracy. Moreover, the global-to-local optimization strategy is added to the architecture to enhance the process. Finally, the result gives a prominent stratosphere airship general solution that validates the feasibility and efficiency of the optimization architecture. Besides, a sensitivity analysis is conducted to outline the critical impact upon stratosphere airship design.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
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 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
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
This paper focuses on the construction organization design of office building projects.It elucidates its concept,core elements,and characteristics,highlighting the shortcomings of traditional designs.The paper introdu...This paper focuses on the construction organization design of office building projects.It elucidates its concept,core elements,and characteristics,highlighting the shortcomings of traditional designs.The paper introduces the improvement effects of technologies such as prefabricated curtain walls,the collaborative optimization role of BIM technology,and various optimization methods,including the establishment of work breakdown structures and the creation of progress deviation warning systems.It also touches on aspects like green construction and risk management.Finally,it emphasizes the significance of optimizing construction organization design,addresses research deficiencies,and looks forward to future research directions.展开更多
Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structur...Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.展开更多
Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic ...Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic cell to design a family of inflatable origami tubular structures with the targeted configuration.First,the classification of rigid foldable degree-4 vertices is studied thoroughly.Since the proposed GMTC is comprised of forming units(FU)and linking units(LU),types of FUs and LUs are investigated based on the classification of degree-4 vertices,respectively.The rigid foldability of the GMTC is presented by studying the kinematics of the FUs and LUs.Volume of the GMTC is analyzed to investigate multistable configurations of the basic cell.The variations in volume of the GMTC offer great potential for developing the inflatable tubular structure.Design method and parametric optimization of the tubular structure with targeted configuration are proposed.The feasibility of the approach is validated by the approximation of four different cases,namely parabolic,semicircular,trapezoidal,and straight-arc hybrid tubular structures.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
The press-fit connector is a typical plug-and-play solderless connection,and it is widely used in signal transmission in fields such as communication and automotive devices.This paper focuses on inverse designing and ...The press-fit connector is a typical plug-and-play solderless connection,and it is widely used in signal transmission in fields such as communication and automotive devices.This paper focuses on inverse designing and optimization of geometric structure,as well as insertion-withdrawal forces of press-fit connector using artificial neural network(ANN)-assisted optimization method.The ANN model is established to approximate the relationship between geometric parameters and insertion-withdrawal forces,of which hyper-parameters of neural network are optimized to improve model performance.Two numerical methods are proposed for inverse designing structural parameters(Model-I)and multi-objective optimization of insertion-withdrawal forces(Model-II)of press-fit connector.In Model-I,a method for inverse designing structure parameters is established,of which an ANN model is coupled with single-objective optimization algorithm.The objective function is established,the inverse problem is solved,and effectiveness is verified.In Model-II,a multi-objective optimization method is proposed,of which an ANN model is coupled with genetic algorithm.The Pareto solution sets of insertion-withdrawal forces are obtained,and results are analyzed.The established ANN-coupled numerical optimization methods are beneficial for improving the design efficiency,and enhancing the connection reliability of the press-fit connector.展开更多
The jacket structure and transition piece comprise the supporting structure of a bottom-fixed offshore wind turbine(OWT)connected to the steel tower,which determines the overall structural dynamic performance of the e...The jacket structure and transition piece comprise the supporting structure of a bottom-fixed offshore wind turbine(OWT)connected to the steel tower,which determines the overall structural dynamic performance of the entire OWT.Ideally,optimal performance can be realized by effectively coordinating two components,notwithstanding their separate design processes.In pursuit of this objective,this paper proposes a concurrent design methodology for the jacket structure and transition piece by exploiting topology optimization(TO).The TO for a three-legged jacket foundation is formulated by minimizing static compliance.In contrast to conventional TO,two separated volume fractions are imposed upon the structural design domain of the jacket structure and transition piece to ensure continuity.A 5 MW(megawatt)OWT supported by a four-legged or three-legged jacket substructure is under investigation.The external loads are derived from various design load cases that are acquired using the commercial software platform DNV Bladed(Det Norske Veritas).Through a comparative analysis of the fundamental frequency and maximum nodal deformation,it was found that the optimized solution demonstrates a reduced weight and superior stiffness.The findings demonstrate the present concurrent design approach using TO can yield significant benefits by reducing the overall design cycle and enhancing the feasibility of the final design.展开更多
Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue feat...Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.展开更多
Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become...Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.展开更多
The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical ...The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.展开更多
To enhance the comprehensive performance of artillery internal ballistics—encompassing power,accuracy,and service life—this study proposed a multi-stage multidisciplinary design optimization(MS-MDO)method.First,the ...To enhance the comprehensive performance of artillery internal ballistics—encompassing power,accuracy,and service life—this study proposed a multi-stage multidisciplinary design optimization(MS-MDO)method.First,the comprehensive artillery internal ballistic dynamics(AIBD)model,based on propellant combustion,rotation band engraving,projectile axial motion,and rifling wear models,was established and validated.This model was systematically decomposed into subsystems from a system engineering perspective.The study then detailed the MS-MDO methodology,which included Stage I(MDO stage)employing an improved collaborative optimization method for consistent design variables,and Stage II(Performance Optimization)focusing on the independent optimization of local design variables and performance metrics.The methodology was applied to the AIBD problem.Results demonstrated that the MS-MDO method in Stage I effectively reduced iteration and evaluation counts,thereby accelerating system-level convergence.Meanwhile,Stage II optimization markedly enhanced overall performance.These comprehensive evaluation results affirmed the effectiveness of the MS-MDO method.展开更多
Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing ...Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.展开更多
Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,i...Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.展开更多
Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonun...Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonuniform corrosion using different materials.In this study,a reliability-based design optimization(RBDO)procedure is improved for the design of coastal bridge piers using six groups of commonly used materials,i.e.,normal performance concrete(NPC)with black steel(BS)rebar,high strength steel(HSS)rebar,epoxy coated(EC)rebar,and stainless steel(SS)rebar(named NPC-BS,NPC-HSS,NPC-EC,and NPC-SS,respectively),NPC with BS with silane soakage on the pier surface(named NPC-Silane),and high-performance concrete(HPC)with BS rebar(named HPC-BS).First,the RBDO procedure is improved for the design optimization of coastal bridge piers,and a bridge is selected to illustrate the procedure.Then,reliability analysis of the pier designed with each group of materials is carried out to obtain the time-dependent reliability in terms of the ultimate and serviceability performances.Next,the repair time of the pier is predicted based on the time-dependent reliability indices.Finally,the time-dependent LCCs for the pier are obtained for the selection of the optimal design.展开更多
Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas...Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.展开更多
基金supported by National Natural Science Foundation of China (No. 51305014)
文摘In this paper,an Uncertainty-based Multi-disciplinary Design Optimization (UMDO)method combining with fuzzy theory and Multi-Discipline Feasible (MDF) method is developed for the conceptual design of a Hybrid Rocket Motor (HRM) powered Launch Vehicle (LV).In the method proposed,membership functions are used to represent the uncertain factors,the fuzzy statistical experiment is introduced to analyze the propagation of uncertainties,and means,standard deviations and credibility measures are used to delineate uncertain responses.A geometric programming problem is solved to verify the feasibility of the Fuzzy-based Multi-Discipline Feasible(F-MDF) method.A multi-disciplinary analysis of a three-stage HRM powered LV involving the disciplines of propulsion,structure,aerodynamics and trajectory is implemented,and the mathematical models corresponding to the F-MDF method and the MDF method are established.A two-phase optimization method is proposed for multi-disciplinary design optimization of the LV,including the orbital capacity optimization phase based on the Ziolkowski formula,and the scheme trajectory verification phase based on the 3-degree-of-freedom point trajectory simulation.The correlation coefficients and the quadratic Response Surface Method (RSM) based on Latin Hypercube Sampling (LHS) are adopted for sensitive analysis of uncertain factors,and the Multi-Island Genetic Algorithm (MIGA) is adopted as the optimization algorithm.The results show that the F-MDF method is applicable in LV conceptual design,and the design with the F-MDF method is more reliable and robust than that with the MDF method.
基金supported in part by the National Key R&D Program of China(No.2016YFB1200100)
文摘This paper proposes a hybrid architecture based on Multi-disciplinary Design Optimization(MDO) with the Variable Complexity Modeling(VCM) method, to solve the problem of general design optimization for a stratosphere airship. Firstly, MDO based on the Concurrent SubSpace Optimization(CSSO) strategy is improved for handling the subsystem coupling problem in stratosphere airship design which contains aerodynamics, structure, and energy. Secondly, the VCM method based on the surrogate model is presented for reducing the computational complexity in high-fidelity modeling without loss of accuracy. Moreover, the global-to-local optimization strategy is added to the architecture to enhance the process. Finally, the result gives a prominent stratosphere airship general solution that validates the feasibility and efficiency of the optimization architecture. Besides, a sensitivity analysis is conducted to outline the critical impact upon stratosphere airship design.
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 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.
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This paper focuses on the construction organization design of office building projects.It elucidates its concept,core elements,and characteristics,highlighting the shortcomings of traditional designs.The paper introduces the improvement effects of technologies such as prefabricated curtain walls,the collaborative optimization role of BIM technology,and various optimization methods,including the establishment of work breakdown structures and the creation of progress deviation warning systems.It also touches on aspects like green construction and risk management.Finally,it emphasizes the significance of optimizing construction organization design,addresses research deficiencies,and looks forward to future research directions.
基金supported by the National Natural Science Foundation of China (Grant Nos.12102021,12372105,12172026,and 12225201)the Fundamental Research Funds for the Central Universities and the Academic Excellence Foundation of BUAA for PhD Students.
文摘Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.
基金supported by the National Natural Science Foundation of China(No.52222501,52075016,52192632)the Fundamental Research Funds for the Central Universities(Grant No.YWF-23-L-904).
文摘Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic cell to design a family of inflatable origami tubular structures with the targeted configuration.First,the classification of rigid foldable degree-4 vertices is studied thoroughly.Since the proposed GMTC is comprised of forming units(FU)and linking units(LU),types of FUs and LUs are investigated based on the classification of degree-4 vertices,respectively.The rigid foldability of the GMTC is presented by studying the kinematics of the FUs and LUs.Volume of the GMTC is analyzed to investigate multistable configurations of the basic cell.The variations in volume of the GMTC offer great potential for developing the inflatable tubular structure.Design method and parametric optimization of the tubular structure with targeted configuration are proposed.The feasibility of the approach is validated by the approximation of four different cases,namely parabolic,semicircular,trapezoidal,and straight-arc hybrid tubular structures.
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 the National Natural Science Foundation of China(No.52005378)the opening project fund of Materials Service Safety Assessment Facilities(No.MSAF-2021-107).
文摘The press-fit connector is a typical plug-and-play solderless connection,and it is widely used in signal transmission in fields such as communication and automotive devices.This paper focuses on inverse designing and optimization of geometric structure,as well as insertion-withdrawal forces of press-fit connector using artificial neural network(ANN)-assisted optimization method.The ANN model is established to approximate the relationship between geometric parameters and insertion-withdrawal forces,of which hyper-parameters of neural network are optimized to improve model performance.Two numerical methods are proposed for inverse designing structural parameters(Model-I)and multi-objective optimization of insertion-withdrawal forces(Model-II)of press-fit connector.In Model-I,a method for inverse designing structure parameters is established,of which an ANN model is coupled with single-objective optimization algorithm.The objective function is established,the inverse problem is solved,and effectiveness is verified.In Model-II,a multi-objective optimization method is proposed,of which an ANN model is coupled with genetic algorithm.The Pareto solution sets of insertion-withdrawal forces are obtained,and results are analyzed.The established ANN-coupled numerical optimization methods are beneficial for improving the design efficiency,and enhancing the connection reliability of the press-fit connector.
基金supports were received from the National Key Research and Development Program of China(2024YFE0208600)New Energy Joint Laboratory of China Southern Power Grid Corporation(GDXNY2024KF03)+2 种基金the National Natural Science Foundation of China(Grant No.U24B2090)National Key R&D Program(No.2022YFB4201300)Science and Technology Project of Huaneng Group(HNKJ24-H78).
文摘The jacket structure and transition piece comprise the supporting structure of a bottom-fixed offshore wind turbine(OWT)connected to the steel tower,which determines the overall structural dynamic performance of the entire OWT.Ideally,optimal performance can be realized by effectively coordinating two components,notwithstanding their separate design processes.In pursuit of this objective,this paper proposes a concurrent design methodology for the jacket structure and transition piece by exploiting topology optimization(TO).The TO for a three-legged jacket foundation is formulated by minimizing static compliance.In contrast to conventional TO,two separated volume fractions are imposed upon the structural design domain of the jacket structure and transition piece to ensure continuity.A 5 MW(megawatt)OWT supported by a four-legged or three-legged jacket substructure is under investigation.The external loads are derived from various design load cases that are acquired using the commercial software platform DNV Bladed(Det Norske Veritas).Through a comparative analysis of the fundamental frequency and maximum nodal deformation,it was found that the optimized solution demonstrates a reduced weight and superior stiffness.The findings demonstrate the present concurrent design approach using TO can yield significant benefits by reducing the overall design cycle and enhancing the feasibility of the final design.
文摘Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.
文摘Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.
基金funded by the Hanoi University of Mining and Geology(Grant No.T23-44)The research is also funded by the German Research Foundation(DFG e Project number 518862444)in collaboration with the Vietnam National Foundation for Science and Technology Development(NAFOSTED)under grant number DFG.105e2022.03The third author was funded by the Postdoctoral Scholarship Program of the Vingroup Innovation Foundation(VINIF)(VINIF.2023.STS.15).
文摘The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.
基金supported by the“National Natural Science Foundation of China”(Grant Nos.52105106,52305155)the“Jiangsu Province Natural Science Foundation”(Grant Nos.BK20210342,BK20230904)the“Young Elite Scientists Sponsorship Programby CAST”(Grant No.2023JCJQQT061).
文摘To enhance the comprehensive performance of artillery internal ballistics—encompassing power,accuracy,and service life—this study proposed a multi-stage multidisciplinary design optimization(MS-MDO)method.First,the comprehensive artillery internal ballistic dynamics(AIBD)model,based on propellant combustion,rotation band engraving,projectile axial motion,and rifling wear models,was established and validated.This model was systematically decomposed into subsystems from a system engineering perspective.The study then detailed the MS-MDO methodology,which included Stage I(MDO stage)employing an improved collaborative optimization method for consistent design variables,and Stage II(Performance Optimization)focusing on the independent optimization of local design variables and performance metrics.The methodology was applied to the AIBD problem.Results demonstrated that the MS-MDO method in Stage I effectively reduced iteration and evaluation counts,thereby accelerating system-level convergence.Meanwhile,Stage II optimization markedly enhanced overall performance.These comprehensive evaluation results affirmed the effectiveness of the MS-MDO method.
基金supported by the National Natural the Science Foundation of China(51971042,51901028)the Chongqing Academician Special Fund(cstc2020yszxjcyj X0001)+1 种基金the China Scholarship Council(CSC)Norwegian University of Science and Technology(NTNU)for their financial and technical support。
文摘Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.
基金supported by 2024 Central Guidance Local Science and Technology Development Fund Project"Study on the mechanism and evaluation method of thermal pollution in water bodies,as well as research on thermal carrying capacity".(Grant 246Z4506G)Key Research and Development Project in Hebei Province:"Key Technologies and Equipment Research and Demonstration of Multiple Energy Complementary(Electricity,Heat,Cold System)for Solar Energy,Geothermal Energy,Phase Change Energy"(Grant 236Z4310G)the Hebei Academy of Sciences Key Research and Development Program"Research on Heat Transfer Mechanisms and Efficient Applications of Intermediate and Deep Geothermal Energy"(22702)。
文摘Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.
基金National Natural Science Foundation of China under Grant Nos.51921006 and 51725801Fundamental Research Funds for the Central Universities under Grant No.FRFCU5710093320Heilongjiang Touyan Innovation Team Program。
文摘Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonuniform corrosion using different materials.In this study,a reliability-based design optimization(RBDO)procedure is improved for the design of coastal bridge piers using six groups of commonly used materials,i.e.,normal performance concrete(NPC)with black steel(BS)rebar,high strength steel(HSS)rebar,epoxy coated(EC)rebar,and stainless steel(SS)rebar(named NPC-BS,NPC-HSS,NPC-EC,and NPC-SS,respectively),NPC with BS with silane soakage on the pier surface(named NPC-Silane),and high-performance concrete(HPC)with BS rebar(named HPC-BS).First,the RBDO procedure is improved for the design optimization of coastal bridge piers,and a bridge is selected to illustrate the procedure.Then,reliability analysis of the pier designed with each group of materials is carried out to obtain the time-dependent reliability in terms of the ultimate and serviceability performances.Next,the repair time of the pier is predicted based on the time-dependent reliability indices.Finally,the time-dependent LCCs for the pier are obtained for the selection of the optimal design.
基金the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province.It was also supported in part by Young Elite Scientists Sponsorship Program by CAST.
文摘Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.
