Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

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.

Research on Regulation Method of Energy Storage System Based on Multi-Stage Robust Optimization

To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust optimization.This approach aims to regulate the energy storage system by using a multi-stage robust optimal control method,which helps overcome the limitations of traditional methods in terms of time scale.The goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the day.To achieve this,a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind power.The generalized Benders Decomposition method is then employed to solve the multi-stage objective optimization problem.By decomposing the problem into a series of sub-objectives,the system scale is effectively reduced,and the algorithm’s convergence ability is improved.Compared with other algorithms,the multi-stage robust optimization model has better economy and convergence ability and can be used to guide the power dispatching of uncertain energy and energy storage systems.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Rigidloop Adjustable可调袢钢板治疗踝关节骨折并下胫腓联合损伤

目的比较Rigidloop Adjustable(RLA)可调袢钢板与螺钉治疗踝关节骨折合并下胫腓联合损伤的临床效果。方法回顾性分析2019年9月至2022年5月武汉市第三医院收治的44例踝关节骨折合并下胫腓联合损伤的患者。踝关节骨折行切开复位内固定后,下胫腓联合采用RLA可调袢钢板固定22例,2枚皮质骨螺钉三皮质骨固定22例。应用AOFAS踝与后足功能评分、术侧与健侧踝关节活动度平均差值及术前、术后随访时正位X线片下胫腓间隙(tibiofibular bottom clear space,TBCS)、下胫腓重叠距离(tibiofibular bottom overlap,TBOL)比较两组临床效果。结果患者均获得随访,随访时间12~18个月,平均(16.41±1.66)个月。患者踝关节功能满意,无伤口感染、皮肤激惹等并发症。术后3、6、12个月时,RLA可调袢钢板组双侧踝关节活动度差值均显著小于螺钉组,差异有统计学意义(P<0.05);术后3、6、12个月时,两组的AOFAS评分比较,差异无统计学意义(P>0.05);TBCS、TBOL术前、术后即刻、术后3个月及末次随访时,差异无统计学意义(P>0.05)。结论RLA可调袢钢板和螺钉均可有效固定下胫腓联合,与螺钉固定相比,RLA可调袢钢板组可早期功能锻炼,获得更好的踝关节活动度。

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

Trace Elements of Multi-stage Minerals and Titanite U-Pb Dating for the Gneisses from Liansan Island,Sulu UHPM Belt

Gneisses with anatectic characteristics from the Liansan island in the Sulu UHPM(ultra-high pressure metamorphic)belt were studied for petrography,titanite U-Pb dating and mineral geochemistry.Three origins of garnets are distinguished:metamorphic garnet,peritectic garnet and anatectic garnet,which are formed in the stages of peak metamorphism,retrograde anatexis and melt crystallization,respectively.The euhedral titanite has a high content of REE and high Th/U ratios,which is interpreted as indicating that it was newly-formed from an anatectic melt.The LA-ICP-MS titanite U-Pb dating yields 214-217 Ma ages for the titanite(melt)crystallization.The distribution of trace elements varies in response to the different host minerals at different stages.At the peak metamorphic stage,Y and HREE are mainly hosted by garnet,Ba and Rb by phengite,Sr,Nb,Ta,Pb,Th,U and LREE by allanite and Y,U and HREE by zircon.During partial melting,Y,Pb,Th,U and REE are released into the melt,which causes a dramatic decline of these element contents in the retrograde minerals.Finally,titanite absorbs most of the Nb,U,LREE and HREE from the melt.Therefore,the different stages of metamorphism have different mineral assemblages,which host different trace elements.

Overview of multi-stage charging strategies for Li-ion batteries

To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.

Multi-Stage Improvement of Marine Predators Algorithm and Its Application

The metaheuristic algorithms are widely used in solving the parameters of the optimization problem.The marine predators algorithm(MPA)is a novel population-based intelligent algorithm.Although MPA has shown a talented foraging strategy,it still needs a balance of exploration and exploitation.Therefore,a multi-stage improvement of marine predators algorithm(MSMPA)is proposed in this paper.The algorithm retains the advantage of multistage search and introduces a linear flight strategy in the middle stage to enhance the interaction between predators.Predators further away from the historical optimum are required to move,increasing the exploration capability of the algorithm.In the middle and late stages,the searchmechanism of particle swarmoptimization(PSO)is inserted,which enhances the exploitation capability of the algorithm.This means that the stochasticity is decreased,that is the optimal region where predators jumping out is effectively stifled.At the same time,self-adjusting weight is used to regulate the convergence speed of the algorithm,which can balance the exploration and exploitation capability of the algorithm.The algorithm is applied to different types of CEC2017 benchmark test functions and threemultidimensional nonlinear structure design optimization problems,compared with other recent algorithms.The results show that the convergence speed and accuracy of MSMPA are significantly better than that of the comparison algorithms.

Reconfigurable source illusion device for airborne sound using an enclosed adjustable piezoelectric metasurface

Source illusion is an important issue in acoustic fields that has significant applications in various practical scenarios.Recent progress in acoustic metasurfaces has broken the limitation of manipulating large-scale waves at subwavelength scales and enables a better illusion capability,while there is still a problem that most previous studies are hampered by a lack of tuning capability.Here we propose a reconfigurable source illusion device capable of providing azimuthallydependent phase delay in real-time via changing the static voltage distribution.The resulting device is implemented by employing an adjustable piezoelectric metasurface with a subwavelength thickness that can achieve a full 2π-phase shift while maintaining efficient transmittance.The effectiveness of our mechanism is demonstrated via two distinctive source illusion phenomena of shifting and transforming a simple point source without changing the device geometry.We anticipate that our methodology,which does not require a large device size or a complicated phased array,will open up new avenues for the miniaturization and integration of source illusion devices and may promote their on-chip applications in a variety of fields,such as acoustic camouflage and manipulation precision.

Novel Radiation-Adjustable Heating Terminal Based on Flat Heat Pipe Combined with Air Source Heat Pump

The electrification of building heating is an effective way to meet the global carbon target. As a clean and sustainable electrified heating technology, air-source heat pumps (ASHPs) are widely used in areas lacking central heating. However, as a major component of space heating, heating terminals might not fit well with ASHP in order to achieve both intermittency and comfort. Therefore, this study proposes a novel radiation-adjustable heating terminal combined with an ASHP to achieve electrification, intermittency, and better thermal comfort. Radiant terminals currently suffer from three major problems: limited maximum heating capacity, inability to freely adapt, and difficulty with combining them with ASHPs. These problems were solved by improving the structural design of the novel terminal (Improvement A–E). Results showed that the maximum heating capacity increased by 23.6% and radiation heat transfer ratio from 10.1% to 30.9% was provided for users with the novel terminal. Further, new flat heat pipe (FHP) design improved stability (compressor oil return), intermittency (refrigerant thermal inertia), and safety (refrigerant leakage risk) by reducing the length of exposed refrigerant pipes. Furthermore, a new phased operation strategy was proposed for the novel terminal, and the adjustability of the terminal was improved. The results can be used as reference information for decarbonizing buildings by electrifying heating terminals.

Experimental Analysis of the Flow Characteristics of an Adjustable Critical-Flow Venturi Nozzle

The response of an adjustable critical-flow Venturi nozzle is investigated through a set indoor experiments aimed to determine the related critical flow rate,critical pressure ratio,and discharge coefficient.The effect of a variation in the cone displacement and liquid content on the critical flow characteristics is examined in detail and it is shown that the former can be used to effectively adjust the critical flow rate.The critical pressure ratio of the considered nozzle is above 0.85,and the critical flow control deviation of the gas flow is within±3%.Liquid flow can reduce the gas critical mass flow rate accordingly,especially for the cases with larger liquid volume and lower inlet pressure.The set of results and conclusions provided are intended to support the optimization of steam injection techniques in the context of heavy oil recovery processes.

Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

Cross-Cultural Adjustment and Coping:U.S.Students in Taiwan Residents Higher Education

The aim of this study was to investigate the adjustment problems of students from the United States enrolled in universities in the East,specifically in Taiwan,their problems related to cultural adaptation,and the process of adjustment to student life in Taiwan.Under investigation were cultural adjustment and coping skills as these students transitioned from West to East.Qualitative data were collected from interviews with participants and faculty members as well as participant observations.Results indicated that U.S.students found their own ways to acclimate to their new academic setting as well as to social relations,cross-cultural issues,and the linguistic environment in Taiwan to achieve effective adaptation.They made changes in themselves to cope with all situations they encountered.This study provides suggestions for international students abroad in Taiwan,for the Taiwan Residents government,and for universities or colleges in terms of what they should offer to current and future international students.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

基于Multi-Stage DEA模型的中国细羊毛生产技术效率实证分析

以内蒙古等4省区为例，采用基于规模报酬可变假设的产出主导型Muhi-StageDEA模型，对2001～2010年中国细羊毛生产技术效率进行了测算和分析。研究结果表明，中国细羊毛生产技术效率不高，存在显著的技术效率损失；细羊毛生产在总体上出现了纯技术效率下降和规模效率提高并存的现象，2008年以来纯技术效率提高对细羊毛生产技术效率改善的促进作用逐渐增强，而细羊毛生产规模效率则呈现出了一定的下降趋势；各省区细羊毛生产技术效率存在较大差异，细羊毛生产的规模效率均要高于纯技术效率，规模效率仍是影响各省区细羊毛生产技术效率改善和提高的主要因素。最后提出改善和提高中国细羊毛生产技术效率的政策建议。

INTERVAL ADJUSTABLE ENTROPY ALGORITHM FOR A CLASS OF UNCONSTRAINED DISCRETE MINIMAX PROBLEMS

In this paper,a class of unconstrained discrete minimax problems is described,in which the objective functions are in C 1.The paper deals with this problem by means of taking the place of maximum entropy function with adjustable entropy function.By constructing an interval extension of adjustable entropy function an d some region deletion test rules,a new interval algorithm is presented.The rele vant properties are proven.The minimax value and the localization of the minimax points of the problem can be obtained by this method. This method can overcome the flow problem in the maximum entropy algorithm.Both theoretical and numerica l results show that the method is reliable and efficient.

Adjustable entropy function method for support vector machine

Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the proposed optimization problem and the Newton algorithm is used to figure out the optimal solution. The proposed method can find an optimal solution with a relatively small parameter p, which avoids the numerical overflow in the traditional entropy function methods. It is a new approach to solve support vector machine. The theoretical analysis and experimental results illustrate the feasibility and efficiency of the proposed algorithm.

Effectivity of intraoperative adjustable suture technique in horizontal strabismus

AIMTo compare the long-term effectivity of intraoperative adjustable suture technique with traditional non-adjustable strabismus surgery.