Shale gas wells often face challenges in maintaining continuous and stable production due to their coexistence with high-and low-pressure wells within the same development block,which leads to issues involving mixed-p...Shale gas wells often face challenges in maintaining continuous and stable production due to their coexistence with high-and low-pressure wells within the same development block,which leads to issues involving mixed-pressure flows.Traditional pipeline optimization methods used in conventional gas well blocks fail to address the unique needs of shale gas wells,such as the precise planning of airflow paths,pressure distribution,and compression.This study proposes a pressure-controlled production optimization strategy specifically designed for shale gas wells operating under mixed-pressure flow conditions.The strategy aims to improve production stability and optimize system efficiency.The decline in production and pressure for individual wells over time is forecasted using a predictive model that accounts for key factors of system optimization,such as reservoir depletion,wellbore conditions,and equipment performance.Additionally,the model predicts the timing and impact of liquid loading,which can significantly affect production.The optimization process involves analyzing the existing gathering pipeline network to determine the most efficient flow directions and compression strategies based on these predictions,while the strategy involves adjusting compressor settings,optimizing flow rates,and planning pressure distribution across the network to maximize productivity while maintaining system stability.By implementing these strategies,this study significantly improves gas well productivity and enhances the adaptability and efficiency of the gathering and transportation system.The proposed approach provides systematic technical solutions and practical guidance for the efficient development and stable production of shale gas fields,ensuring more robust and sustainable pipeline operations.展开更多
[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infra...[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.展开更多
The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACT...The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.展开更多
In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants ...In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.展开更多
To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a ...To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.展开更多
With the in-depth advancement of rural revitalization and urban-rural integration strategies,the integration of agriculture,culture,and tourism has become an important path for promoting high-quality development in me...With the in-depth advancement of rural revitalization and urban-rural integration strategies,the integration of agriculture,culture,and tourism has become an important path for promoting high-quality development in metropolitan suburbs.Taking Cihui Subdistrict in Wuhan as an example,this research systematically sorts out its resource endowments,development models,and implementation effectiveness of the agriculture-culture-tourism integration through field research and case analysis.It further delves into the existing problems,such as insufficient planning and coordination,weak factor support,and insufficient industrial integration,along with their underlying causes.On such basis,targeted countermeasures are proposed from the aspects of scientific planning,industrial collaboration,talent introduction and cultivation,brand building,and policy optimization.The study aims to build an integrated development system of agriculture,culture,and tourism tailored to the characteristics of metropolitan suburbs,providing theoretical references and policy inspiration for similar regions.展开更多
Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainabili...Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.展开更多
The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system perf...The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.展开更多
In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy sys...In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.展开更多
Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characte...Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.展开更多
Driven by the global energy transition and the urgent“dual carbon”goals,regional integrated energy system(RIES)planning is undergoing a paradigm shift from carbon reduction to negative carbon emissions.This paper pr...Driven by the global energy transition and the urgent“dual carbon”goals,regional integrated energy system(RIES)planning is undergoing a paradigm shift from carbon reduction to negative carbon emissions.This paper provides a comprehensive review of the theoretical frameworks and technical pathways for RIES planning from a carbon-centric perspective.A key contribution is the proposed Carbon-Energy-Economy(CEE)triple-dimensional governance framework,which endogenizes carbon factors into planning decisions through emission constraints,trading mechanisms,and capture technologies.We first analyze the fundamental characteristics of RIES and their critical role in achieving carbon neutrality,detailing advancements in multi-energy coupling models,energy router concepts,and standardized energy hub modeling.The paper further explores multi-energy flow analysis methods,and systematically compares the applicability and limitations of various planning algorithms,with emphasis on addressing uncertainties from renewable integration.Finally,we highlight the integration of artificial intelligence with traditional optimization methods,offering new pathways for intelligent,adaptive,and low-carbon RIES planning.This review underscores the transition towards data-physical fusion models,cooperative uncertainty optimization,multi-market planning,and innovative zero/negative-carbon technological routes.展开更多
To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon...To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon capture and storage(CCS),hydrogen fuel cell(HFC),and combined heat and power(CHP).The P2G process is refined into a two-stage structure,and HFC is introduced to enhance hydrogen utilization.Together with CCS and CHP,these devices form a multi-energy conversion system coupling electricity,heat,cooling,and gas.A laddertype carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.To evaluate the resilience of the proposed low-carbon scheduling strategy involving multiple energy units under the variability of renewable energy,a two-level robust optimization framework is developed.This model captures the most adverse scenarios of wind and solar generation.The dispatch strategy is validated against these extreme conditions to demonstrate its flexibility and effectiveness.The problem is solved using the GUROBI optimization tool.Results from simulations indicate that themodel increases renewable energy integration by 39.1%,and achieves reductions of 15.96%in carbon emissions and 16.29%in operational expenditures.The results demonstrate that the strategy ensures both economic efficiency and environmental performance under uncertain conditions.Compared with existing studies that separately model two-stage P2G or CCS devices,this paper integrates HFC,CHP,and CCS into a unified dispatchable system,enabling refined hydrogen utilization and flexible carbon circulation.Furthermore,the introduction of a laddertype carbon pricing mechanism,combined with multi-energy storage participation in implicit demand response,creates a dynamic and cost-sensitive dispatch framework.These modeling strategies go beyond conventional linear IES formulations and provide more realistic system representations.The proposed approach not only deepens the coupling among electric,thermal,and gas systems,but also offers a feasible pathway for high-penetration renewable integration in low-carbon energy systems.展开更多
Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,...Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.展开更多
Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convol...Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.展开更多
Capacitive deionization(CDI),as an emerging desalination technique,has been intensively explored because of its energy-saving,cost-effectiveness and sustainability.Despite the promise,CDI systems still encounter vario...Capacitive deionization(CDI),as an emerging desalination technique,has been intensively explored because of its energy-saving,cost-effectiveness and sustainability.Despite the promise,CDI systems still encounter various challenges involving active sites,mass transfer and stability that severely limit their further application.So far,there is still much-limited review across material,electrodes and devices to cope with the above challenges.Notably,carbon nanotubes(CNTs),have garnered significant attention owing to their exceptional conductivity,high specific surface area(S_(BET)),unique skeleton role and superior mechanical strength.More importantly,CNTs serve multifunctional roles in CDI systems,including active materials,conductive agents,binders,and even current collectors,while also making for the thick electrode framework construction.Specifically,this review first discusses current challenges in CDI system design.Subsequently,it systemic highlights how CNTs address these issues through material innovation,electrode optimization and device integration.Eventually,a conceptual model for CNT composite self-supporting CDI systems is further proposed,aiming to exploit advanced CDI desalination systems.Overall,this review underscores the pivotal role of CNTs in overcoming technical bottlenecks and driving the practical application of CDI for sustainable water treatment.展开更多
With the rapid development of electronic information engineering,high-speed digital circuits have been increasingly widely applied in various fields.In high-speed digital circuits,signal integrity is prone to interfer...With the rapid development of electronic information engineering,high-speed digital circuits have been increasingly widely applied in various fields.In high-speed digital circuits,signal integrity is prone to interference from various external factors,leading to issues such as signal distortion or degradation of system performance.Based on this,this paper conducts research on the optimization strategies for signal integrity of high-speed digital circuits in electronic information engineering.It deeply analyzes the importance of high-speed digital circuits,elaborates on the challenges they face and the specific manifestations of signal integrity issues,and proposes a series of optimization strategies in electronic information engineering.The aim is to improve the signal integrity of highspeed digital circuits and provide theoretical support and practical guidance for the development of related fields.展开更多
In recent years,managing rural living environments has become a vital component of the rural revitalization strategy.Jiangsu Province,rich in economic and cultural resources,has accumulated valuable experience in expl...In recent years,managing rural living environments has become a vital component of the rural revitalization strategy.Jiangsu Province,rich in economic and cultural resources,has accumulated valuable experience in exploring rural environmental governance by integrating culture and tourism.This research analyzes the practical logic of rural environmental governance in Jiangsu from both theoretical and practical perspectives.It emphasizes the importance of integrating culture and tourism to enhance environmental governance while addressing the associated challenges.The results show that the integration of culture and tourism not only enhances rural ecological environments and living facilities but also boosts regional economic development and the preservation of cultural resources.Nevertheless,there are still challenges in aspects such as the collaboration of stakeholders,the establishment of long-term mechanisms,and the application of digital technologies.Based on real cases in Jiangsu,this study suggests optimization strategies and policy recommendations to improve rural environmental governance within the framework of cultural and tourism integration.展开更多
For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model f...For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.展开更多
The design of Human Occupied Vehicle （HOV） is a typical multidisciplinary problem, but heavily dependent on the experience of naval architects at present engineering design. In order to relieve the experience depend...The design of Human Occupied Vehicle （HOV） is a typical multidisciplinary problem, but heavily dependent on the experience of naval architects at present engineering design. In order to relieve the experience dependence and improve the design, a new Multidisciplinary Design Optimization （MDO） method ＂Bi-Level Integrated System Collaborative Optimization （BLISCO）＂ is applied to the conceptual design of an HOV, which consists of hull module, resistance module, energy module, structure module, weight module, and the stability module. This design problem is defined by 21 design variables and 23 constraints, and its objective is to maximize the ratio of payload to weight. The results show that the general performance of the HOV can be greatly improved by BLISCO.展开更多
A systematic analysis is performed to assess the current situation of transportation and tourism integration in 20 districts and counties located along National Highway 310(Gansu-Qinghai section),and optimization stra...A systematic analysis is performed to assess the current situation of transportation and tourism integration in 20 districts and counties located along National Highway 310(Gansu-Qinghai section),and optimization strategies are explored based on the findings of this analysis.The findings indicate a pressing necessity for further improvement in the practice of transportation and tourism integration in both Gansu and Qinghai provinces.Based on this foundation,a development framework for transportation and tourism integration has been established.This framework simulates a“fast-forward-slow-travel”system in which tourists commence their journey from the origin,traverse through core,secondary,and subsidiary tourist destinations,and ultimately reach the core,secondary,and subsidiary attractions.Furthermore,this study presents optimization recommendations for the integrated development of regional transportation and tourism along the designated route.These suggestions encompass the establishment and optimization of facilities and service points,the planning and design of tourism routes,the promotion of regional synergistic development,the construction of intelligent tourism,and the implementation of green tourism pathways.展开更多
基金supported by the National Natural Science Foundation of China under Grant 52325402,52274057 and 52074340the National Key R&D Program of China under Grant 2023YFB4104200+1 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSN111 Project under Grant B08028.
文摘Shale gas wells often face challenges in maintaining continuous and stable production due to their coexistence with high-and low-pressure wells within the same development block,which leads to issues involving mixed-pressure flows.Traditional pipeline optimization methods used in conventional gas well blocks fail to address the unique needs of shale gas wells,such as the precise planning of airflow paths,pressure distribution,and compression.This study proposes a pressure-controlled production optimization strategy specifically designed for shale gas wells operating under mixed-pressure flow conditions.The strategy aims to improve production stability and optimize system efficiency.The decline in production and pressure for individual wells over time is forecasted using a predictive model that accounts for key factors of system optimization,such as reservoir depletion,wellbore conditions,and equipment performance.Additionally,the model predicts the timing and impact of liquid loading,which can significantly affect production.The optimization process involves analyzing the existing gathering pipeline network to determine the most efficient flow directions and compression strategies based on these predictions,while the strategy involves adjusting compressor settings,optimizing flow rates,and planning pressure distribution across the network to maximize productivity while maintaining system stability.By implementing these strategies,this study significantly improves gas well productivity and enhances the adaptability and efficiency of the gathering and transportation system.The proposed approach provides systematic technical solutions and practical guidance for the efficient development and stable production of shale gas fields,ensuring more robust and sustainable pipeline operations.
文摘[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
文摘The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.
基金supported by the National Nature Science Foundation of China(Nos.62063019)Natural Science Foundation of Gansu Province(22JR5RA241,2023CXZX-465).
文摘In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.
基金the Foshan Science and Technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.
基金Sponsored by Innovation and Entrepreneurship Training Program for College Students of Wuhan Polytechnic University(202510496165)Youth Project of the Education Department of Hubei Province(24Q195).
文摘With the in-depth advancement of rural revitalization and urban-rural integration strategies,the integration of agriculture,culture,and tourism has become an important path for promoting high-quality development in metropolitan suburbs.Taking Cihui Subdistrict in Wuhan as an example,this research systematically sorts out its resource endowments,development models,and implementation effectiveness of the agriculture-culture-tourism integration through field research and case analysis.It further delves into the existing problems,such as insufficient planning and coordination,weak factor support,and insufficient industrial integration,along with their underlying causes.On such basis,targeted countermeasures are proposed from the aspects of scientific planning,industrial collaboration,talent introduction and cultivation,brand building,and policy optimization.The study aims to build an integrated development system of agriculture,culture,and tourism tailored to the characteristics of metropolitan suburbs,providing theoretical references and policy inspiration for similar regions.
基金supported by National Key Research and Development Program(2024YFE0115600).
文摘Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.
文摘The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.
基金supported by the Central Government Guides Local Science and Technology Development Fund Project(2023ZY0020)Key R&D and Achievement Transformation Project in InnerMongolia Autonomous Region(2022YFHH0019)+3 种基金the Fundamental Research Funds for Inner Mongolia University of Science&Technology(2022053)Natural Science Foundation of Inner Mongolia(2022LHQN05002)National Natural Science Foundation of China(52067018)Metallurgical Engineering First-Class Discipline Construction Project in Inner Mongolia University of Science and Technology,Control Science and Engineering Quality Improvement and Cultivation Discipline Project in Inner Mongolia University of Science and Technology。
文摘In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.
文摘Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.
基金supported by the Natural Science Foundation of China(Grants U2166211)Zhejiang Provincial Natural Science Foundation of China(Grants LY24E070006 and LMS25E070002).
文摘Driven by the global energy transition and the urgent“dual carbon”goals,regional integrated energy system(RIES)planning is undergoing a paradigm shift from carbon reduction to negative carbon emissions.This paper provides a comprehensive review of the theoretical frameworks and technical pathways for RIES planning from a carbon-centric perspective.A key contribution is the proposed Carbon-Energy-Economy(CEE)triple-dimensional governance framework,which endogenizes carbon factors into planning decisions through emission constraints,trading mechanisms,and capture technologies.We first analyze the fundamental characteristics of RIES and their critical role in achieving carbon neutrality,detailing advancements in multi-energy coupling models,energy router concepts,and standardized energy hub modeling.The paper further explores multi-energy flow analysis methods,and systematically compares the applicability and limitations of various planning algorithms,with emphasis on addressing uncertainties from renewable integration.Finally,we highlight the integration of artificial intelligence with traditional optimization methods,offering new pathways for intelligent,adaptive,and low-carbon RIES planning.This review underscores the transition towards data-physical fusion models,cooperative uncertainty optimization,multi-market planning,and innovative zero/negative-carbon technological routes.
基金supported by the Key Project of Shanghai(Project Number A1-0224-25-002-02-040,Municipal Key Course—Heat Transfer)funded by the National Natural Science Foundation of China(Grant No.52077137).
文摘To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon capture and storage(CCS),hydrogen fuel cell(HFC),and combined heat and power(CHP).The P2G process is refined into a two-stage structure,and HFC is introduced to enhance hydrogen utilization.Together with CCS and CHP,these devices form a multi-energy conversion system coupling electricity,heat,cooling,and gas.A laddertype carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.To evaluate the resilience of the proposed low-carbon scheduling strategy involving multiple energy units under the variability of renewable energy,a two-level robust optimization framework is developed.This model captures the most adverse scenarios of wind and solar generation.The dispatch strategy is validated against these extreme conditions to demonstrate its flexibility and effectiveness.The problem is solved using the GUROBI optimization tool.Results from simulations indicate that themodel increases renewable energy integration by 39.1%,and achieves reductions of 15.96%in carbon emissions and 16.29%in operational expenditures.The results demonstrate that the strategy ensures both economic efficiency and environmental performance under uncertain conditions.Compared with existing studies that separately model two-stage P2G or CCS devices,this paper integrates HFC,CHP,and CCS into a unified dispatchable system,enabling refined hydrogen utilization and flexible carbon circulation.Furthermore,the introduction of a laddertype carbon pricing mechanism,combined with multi-energy storage participation in implicit demand response,creates a dynamic and cost-sensitive dispatch framework.These modeling strategies go beyond conventional linear IES formulations and provide more realistic system representations.The proposed approach not only deepens the coupling among electric,thermal,and gas systems,but also offers a feasible pathway for high-penetration renewable integration in low-carbon energy systems.
基金partially supported by the National Natural Science Foundation of China(Nos.32471474 and 82102574)the Precision Medicine Project of People’s Hospital of Xinjiang Uygur Autonomous Region(No.20220305)+4 种基金Chengdu Advanced Metal Materials Industry Technology Research Institute Co.,Ltd.Support Project(No.24H0802)Sichuan Science and Technology Program(Nos.2025YFHZ0086,2023YFS0053,2024YFHZ0125,and 2025ZNSFSC0381)Project of Tianfu Jincheng Laboratory(No.2025ZH009)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515220102)Xinjiang Autonomous Region Science and Technology Support Project Plan(Directive)Project(No.2024E02049)。
文摘Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.
基金supported by Science and Technology Innovation Programfor Postgraduate Students in IDP Subsidized by Fundamental Research Funds for the Central Universities(Project No.ZY20240335)support of the Research Project of the Key Technology of Malicious Code Detection Based on Data Mining in APT Attack(Project No.2022IT173)the Research Project of the Big Data Sensitive Information Supervision Technology Based on Convolutional Neural Network(Project No.2022011033).
文摘Previous studies have shown that deep learning is very effective in detecting known attacks.However,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low accuracy.Therefore,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 dataset.The hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 dataset.The evaluation accuracy of the new dataset GINKS2023 created in this paper is 0.9386.Compared to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.
基金financial support of the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grants No.163105819)Nanjing Forestry University High-level Talent Introduction Research Foundation(Grants No.163105774)。
文摘Capacitive deionization(CDI),as an emerging desalination technique,has been intensively explored because of its energy-saving,cost-effectiveness and sustainability.Despite the promise,CDI systems still encounter various challenges involving active sites,mass transfer and stability that severely limit their further application.So far,there is still much-limited review across material,electrodes and devices to cope with the above challenges.Notably,carbon nanotubes(CNTs),have garnered significant attention owing to their exceptional conductivity,high specific surface area(S_(BET)),unique skeleton role and superior mechanical strength.More importantly,CNTs serve multifunctional roles in CDI systems,including active materials,conductive agents,binders,and even current collectors,while also making for the thick electrode framework construction.Specifically,this review first discusses current challenges in CDI system design.Subsequently,it systemic highlights how CNTs address these issues through material innovation,electrode optimization and device integration.Eventually,a conceptual model for CNT composite self-supporting CDI systems is further proposed,aiming to exploit advanced CDI desalination systems.Overall,this review underscores the pivotal role of CNTs in overcoming technical bottlenecks and driving the practical application of CDI for sustainable water treatment.
文摘With the rapid development of electronic information engineering,high-speed digital circuits have been increasingly widely applied in various fields.In high-speed digital circuits,signal integrity is prone to interference from various external factors,leading to issues such as signal distortion or degradation of system performance.Based on this,this paper conducts research on the optimization strategies for signal integrity of high-speed digital circuits in electronic information engineering.It deeply analyzes the importance of high-speed digital circuits,elaborates on the challenges they face and the specific manifestations of signal integrity issues,and proposes a series of optimization strategies in electronic information engineering.The aim is to improve the signal integrity of highspeed digital circuits and provide theoretical support and practical guidance for the development of related fields.
基金2022 Key Research Project of Philosophy and Social Sciences at Nanjing Tech University Pujiang Institute,“The Subject-Object Relationship and Its Coordination Mechanism in the Construction of Beautiful Countryside in Jiangsu”(Project No.:Njpj2022-2-01)。
文摘In recent years,managing rural living environments has become a vital component of the rural revitalization strategy.Jiangsu Province,rich in economic and cultural resources,has accumulated valuable experience in exploring rural environmental governance by integrating culture and tourism.This research analyzes the practical logic of rural environmental governance in Jiangsu from both theoretical and practical perspectives.It emphasizes the importance of integrating culture and tourism to enhance environmental governance while addressing the associated challenges.The results show that the integration of culture and tourism not only enhances rural ecological environments and living facilities but also boosts regional economic development and the preservation of cultural resources.Nevertheless,there are still challenges in aspects such as the collaboration of stakeholders,the establishment of long-term mechanisms,and the application of digital technologies.Based on real cases in Jiangsu,this study suggests optimization strategies and policy recommendations to improve rural environmental governance within the framework of cultural and tourism integration.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473374,62403487 and U2441243).
文摘For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.
基金financially supported by the National Natural Science Foundation of China(Grant No.51109132)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20110073120015)
文摘The design of Human Occupied Vehicle （HOV） is a typical multidisciplinary problem, but heavily dependent on the experience of naval architects at present engineering design. In order to relieve the experience dependence and improve the design, a new Multidisciplinary Design Optimization （MDO） method ＂Bi-Level Integrated System Collaborative Optimization （BLISCO）＂ is applied to the conceptual design of an HOV, which consists of hull module, resistance module, energy module, structure module, weight module, and the stability module. This design problem is defined by 21 design variables and 23 constraints, and its objective is to maximize the ratio of payload to weight. The results show that the general performance of the HOV can be greatly improved by BLISCO.
文摘A systematic analysis is performed to assess the current situation of transportation and tourism integration in 20 districts and counties located along National Highway 310(Gansu-Qinghai section),and optimization strategies are explored based on the findings of this analysis.The findings indicate a pressing necessity for further improvement in the practice of transportation and tourism integration in both Gansu and Qinghai provinces.Based on this foundation,a development framework for transportation and tourism integration has been established.This framework simulates a“fast-forward-slow-travel”system in which tourists commence their journey from the origin,traverse through core,secondary,and subsidiary tourist destinations,and ultimately reach the core,secondary,and subsidiary attractions.Furthermore,this study presents optimization recommendations for the integrated development of regional transportation and tourism along the designated route.These suggestions encompass the establishment and optimization of facilities and service points,the planning and design of tourism routes,the promotion of regional synergistic development,the construction of intelligent tourism,and the implementation of green tourism pathways.
