Composition optimization and performance prediction for ultra-stable water-based aerosol based on thermodynamic entropy theory

Water-based aerosol is widely used as an effective strategy in electro-optical countermeasure on the battlefield used to the preponderance of high efficiency,low cost and eco-friendly.Unfortunately,the stability of the water-based aerosol is always unsatisfactory due to the rapid evaporation and sedimentation of the aerosol droplets.Great efforts have been devoted to improve the stability of water-based aerosol by using additives with different composition and proportion.However,the lack of the criterion and principle for screening the effective additives results in excessive experimental time consumption and cost.And the stabilization time of the aerosol is still only 30 min,which could not meet the requirements of the perdurable interference.Herein,to improve the stability of water-based aerosol and optimize the complex formulation efficiently,a theoretical calculation method based on thermodynamic entropy theory is proposed.All the factors that influence the shielding effect,including polyol,stabilizer,propellant,water and cosolvent,are considered within calculation.An ultra-stable water-based aerosol with long duration over 120 min is obtained with the optimal fogging agent composition,providing enough time for fighting the electro-optic weapon.Theoretical design guideline for choosing the additives with high phase transition temperature and low phase transition enthalpy is also proposed,which greatly improves the total entropy change and reduce the absolute entropy change of the aerosol cooling process,and gives rise to an enhanced stability of the water-based aerosol.The theoretical calculation methodology contributes to an abstemious time and space for sieving the water-based aerosol with desirable performance and stability,and provides the powerful guarantee to the homeland security.

A PID Tuning Approach for Inertial Systems Performance Optimization

In the practice of control the industrial processes, proportional-integral-derivative controller remains pivotal due to its simple structure and system performance-oriented tuning process. In this paper are presented two approaches for synthesis the proportional-integral-derivative controller to the models of objects with inertia, that offer the procedure of system performance optimization based on maximum stability degree criterion. The proposed algorithms of system performance optimization were elaborated for model of objects with inertia second and third order and offer simple analytical expressions for tuning the PID controller. Validation and verification are conducted through computer simulations using MATLAB, demonstrating successful performance optimization and showcasing the effectiveness PID controllers’ tuning. The proposed approaches contribute insights to the field of control, offering a pathway for optimizing the performance of second and third-order inertial systems through robust controller synthesis.

Research on the Optimization of Green Building Performance Based on BIM Technology

With the acceleration of urbanization,the construction industry has developed rapidly worldwide but has also brought serious environmental problems.Traditional architectural design methods often only focus on the function and beauty of the building while ignoring its impact on the environment.In addition,the lack of effective design and construction management methods also led to high resource and energy consumption.To overcome this challenge,the concept of green building came into being.Green buildings emphasize reducing the negative impact of buildings on the environment and improving resource utilization efficiency throughout the entire life cycle.BIM technology provides strong support for achieving this goal.Based on this,starting from the role of BIM technology in green building performance optimization,this article analyzes the optimization of green building performance solutions based on BIM technology in detail to promote the sustainable development of buildings.

Hybrid data-driven framework for shale gas production performance analysis via game theory, machine learning, and optimization approaches

A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.

Performance optimization on finite-time quantum Carnot engines and refrigerators based on spin-1/2 systems driven by a squeezed reservoir

We investigate the finite-time performance of a quantum endoreversible Carnot engine cycle and its inverse operation-Carnot refrigeration cycle,employing a spin-1/2 system as the working substance.The thermal machine is alternatively driven by a hot boson bath of inverse temperatureβ_(h)and a cold boson bath at inverse temperatureβ_(c)(>βh).While for the engine model the hot bath is constructed to be squeezed,in the refrigeration cycle the cold bath is established to be squeezed,with squeezing parameter r.We obtain the analytical expressions for both efficiency and power in heat engines and for coefficient of performance and cooling rate in refrigerators.We find that,in the high-temperature limit,the efficiency at maximum power is bounded by the analytical valueη_(+)=√sech(2r)(1-η_(C)),and the coefficient of performance at the maximum figure of merit is limited byε_(+)=√sech(2r)(1+ε_(C))/sech(2r)(1+ε_(C))-εC)-1,whereη_(C)=1-β_(h)/β_(c)andε_(C)=β_(h)/(β_(c)-β_(h))are the respective Carnot values of the engines and refrigerators.These analytical results are identical to those obtained from the Carnot engines based on harmonic systems,indicating that the efficiency at maximum power and coefficient at maximum figure of merit are independent of the working substance.

ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

Layered power scheduling optimization of PV hydrogen production system considering performance attenuation of PEMEL

To analyze the additional cost caused by the performance attenuation of a proton exchange membrane electrolyzer(PEMEL)under the fluctuating input of renewable energy,this study proposes an optimization method for power scheduling in hydrogen production systems under the scenario of photovoltaic(PV)electrolysis of water.First,voltage and performance attenuation models of the PEMEL are proposed,and the degradation cost of the electrolyzer under a fluctuating input is considered.Then,the calculation of the investment and operating costs of the hydrogen production system for a typical day is based on the life cycle cost.Finally,a layered power scheduling optimization method is proposed to reasonably distribute the power of the electrolyzer and energy storage system in a hydrogen production system.In the up-layer optimization,the PV power absorbed by the hydrogen production system was optimized using MALTAB+Gurobi.In low-layer optimization,the power allocation between the PEMEL and battery energy storage system(BESS)is optimized using a non-dominated sorting genetic algorithm(NSGA-Ⅱ)combined with the firefly algorithm(FA).A better optimization result,characterized by lower degradation and total costs,was obtained using the method proposed in this study.The improved algorithm can search for a better population and obtain optimization results in fewer iterations.As a calculation example,data from a PV power station in northwest China were used for optimization,and the effectiveness and rationality of the proposed optimization method were verified.

Machine Learning Assisted Design of Natural Rubber Composites with Multi⁃Performance Optimization

Multi⁃performance optimization of tread rubber composites is a key issue of great concern in automotive industry.Traditional experimental design approach via“trial and error”or intuition is ineffective due to mutual inhibition among multiple properties.A“Uniform design⁃Machine learning”strategy for performance prediction and multi⁃performance optimization of tread rubber composites was proposed.The wear resistance,rolling resistance,tensile strength and wet skid resistance were simultaneously optimized.A series of feasible optimization designs were screened via statistical analysis and machine learning analysis,and were experimentally prepared.The verification experiments demonstrate that the optimization design via machine learning analysis meets the optimization requirements of all target performance,especially for Akron abrasion and 60℃tanδ(about 21%and 9%lower than the design targets,respectively)due to the inhibition of mechanical degradation and good dispersion of fillers.

Design methodology of a mini-missile considering flight performance and guidance precision

The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.

Effect of Spray Rails on Takeoff Performance of Amphibian Aircraft

Amphibian aircraft have seen a rise in popularity in the recreational and utility sectors due to their ability to take off and land on both land and water, thus serving a myriad of purposes, such as aerobatics, surveillance, and firefighting. Such seaplanes must be aerodynamically and hydrodynamically efficient, particularly during the takeoff phase. Naval architects have long employed innovative techniques to optimize the performance of marine vessels, including incorporating spray rails on hulls. This research paper is dedicated to a comprehensive investigation into the potential utilization of spray rails to enhance the takeoff performance of amphibian aircraft. Several spray rail configurations obtained from naval research were simulated on a bare Seamax M22 amphibian hull to observe an approximate 10% - 25% decrease in water resistance at high speeds alongside a 3% reduction in the takeoff time. This study serves as a motivation to improve the design of the reference airplane hull and a platform for detailed investigations in the future to improve modern amphibian design.

Multi‐objective particle swarm optimisation of complex product change plan considering service performance

Design change is an inevitable part of the product development process.This study proposes an improved binary multi‐objective PSO algorithm guided by problem char-acteristics(P‐BMOPSO)to solve the optimisation problem of complex product change plan considering service performance.Firstly,a complex product multi‐layer network with service performance is established for the first time to reveal the impact of change effect propagation on the product service performance.Secondly,the concept of service performance impact(SPI)is defined by decoupling the impact of strongly associated nodes on the service performance in the process of change affect propagation.Then,a triple‐objective selection model of change nodes is established,which includes the three indicators:SPI degree,change cost,and change time.Furthermore,an integer multi‐objective particle swarm optimisation algorithm guided by problem characteristics is developed to solve the model above.Experimental results on the design change problem of a certain type of Skyworth TV verify the effectiveness of the established optimisation model and the proposed P‐BMOPSO algorithm.

Parameter Optimization of Nose Landing Gear Considering Both Take-off and Landing Performance of Catapult Take-off Carrier-Based Aircraft

Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.

Light-Weight Design Method for Force-Performance-Structure of Complex Structural Part Based Co-operative Optimization

A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light?weight design of conceptual configuration for complex parts under multi?objective and multi?condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size charac?teristic parameters are obtained. A bed structure of gantry?type machining center is designed by using the proposed light?weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.

Performance Optimization of Fujian Digital Design and Manufacture Service Platform Based on AJAX

In this paper,the problem on the service platform,which existed on the traditional WEB application mode,are analyzed in detail.It shows that application of the AJAX technology can optimize the service platform.And the AJAX technology can supply the wonderful solution for the development of the high-performance WEB application by means of the WEB performance testing tool to test the network performance of the service platform.

Mechanical Analysis and Performance Optimization for the Lunar Rover’s Vane-Telescopic Walking Wheel

It is well-known that optimizing the wheel system of lunar rovers is essential.However,this is a difficult task due to the complex terrain of the moon and limited resources onboard lunar rovers.In this study,an experimental prototype was set up to analyze the existing mechanical design of a lunar rover and improve its performance.First,a new vane-telescopic walking wheel was proposed for the lunar rover with a positive and negative quadrangle suspension,considering the complex terrain of the moon.Next,the performance was optimized under the limitations of preserving the slope passage and minimizing power consumption.This was achieved via analysis of the wheel force during movement.Finally,the effectiveness of the proposed method was demonstrated by several simulation experiments.The newly designed wheel can protrude on demand and reduce energy consumption;it can be used as a reference for lunar rover development engineering in China.

H-infinity performance optimization for networked control systems with limited communication channels

This paper studies the problems of H-infinity performance optimization and controller design for continuoustime NCSs with both sensor-to-controller and controller-to-actuator communication constraints(limited communication channels).By taking the derivative character of network-induced delay into full consideration and defining new Lyapunov functions,linear matrix inequalities(LMIs)-based H-infinity performance optimization and controller design are presented for NCSs with limited communication channels.If there do not exist any constraints on the communication channels,the proposed design methods are also applicable.The merit of the proposed methods lies in their less conservativeness,which is achieved by avoiding the utilization of bounding inequalities for cross products of vectors.The simulation results illustrate the merit and effectiveness of the proposed H-infinity controller design for NCSs with limited communication channels.

Different effects of economic and structural performance indexes on model construction of structural topology optimization

The objective and constraint functions related to structural optimization designs are classified into economic and performance indexes in this paper.The influences of their different roles in model construction of structural topology optimization are also discussed.Furthermore,two structural topology optimization models,optimizing a performance index under the limitation of an economic index,represented by the minimum compliance with a volume constraint(MCVC)model,and optimizing an economic index under the limitation of a performance index,represented by the minimum weight with a displacement constraint(MWDC)model,are presented.Based on a comparison of numerical example results,the conclusions can be summarized as follows:(1)under the same external loading and displacement performance conditions,the results of the MWDC model are almost equal to those of the MCVC model;(2)the MWDC model overcomes the difficulties and shortcomings of the MCVC model;this makes the MWDC model more feasible in model construction;(3)constructing a model of minimizing an economic index under the limitations of performance indexes is better at meeting the needs of practical engineering problems and completely satisfies safety and economic requirements in mechanical engineering,which have remained unchanged since the early days of mechanical engineering.

Study on the Performance Optimization of Knitted Fabric Anti-Roll by Tissue Structure

Will use the same number of positive and negative coil longitudinal organization of fabric is ta edge sex used in the work of the organization to warp fabric edge sex, between restrained knitting principle, design a kind of weft basketwork weaving method, especially in weft knitting machine woven from has the edge of weft knitted fabric performance weaving method. In order to overcome the existing technology aims to make weft basketwork structure of a single organization, edge sex is bad, or can’t produce rich weft knitted fabric appearance of shortage, provide a resistance to edge weft knitted fabric weaving method.

Parallelization and I/O Performance Optimization of a Global Nonhydrostatic Dynamical Core Using MPI

The Global-Regional Integrated forecast System(GRIST)is the next-generation weather and climate integrated model dynamic framework developed by Chinese Academy of Meteorological Sciences.In this paper,we present several changes made to the global nonhydrostatic dynamical(GND)core,which is part of the ongoing prototype of GRIST.The changes leveraging MPI and PnetCDF techniques were targeted at the parallelization and performance optimization to the original serial GND core.Meanwhile,some sophisticated data structures and interfaces were designed to adjust flexibly the size of boundary and halo domains according to the variable accuracy in parallel context.In addition,the I/O performance of PnetCDF decreases as the number of MPI processes increases in our experimental environment.Especially when the number exceeds 6000,it caused system-wide outages(SWO).Thus,a grouping solution was proposed to overcome that issue.Several experiments were carried out on the supercomputing platform based on Intel x86 CPUs in the National Supercomputing Center in Wuxi.The results demonstrated that the parallel GND core based on grouping solution achieves good strong scalability and improves the performance significantly,as well as avoiding the SWOs.

Development and Application of Decision Support Model for the Performance Optimization of Office Buildings Based on Grasshopper

With the expansion of the office building area,the energy consumption of office buildings is growing.High⁃performance building design contributes to energy saving and the development of green buildings.However,there is a lack of high⁃performance building tools and the workflow is often time⁃consuming.The building performance simulation,multiple objective optimizations,and the decision support model are the new approaches of high⁃performance building design.This paper proposes a newly developed decision support model,a high⁃performance building decision model named HPBuildingDSM,which integrates the building performance simulation,building performance multiple objective optimizations,building performance sampling,and parameter sensitivity analysis to design high⁃performance office buildings.In this research,the HPBuildingDSM was operated to search for the desirable office building design results with low⁃energy and high⁃quality daylighting performances.The simulated results had better daylighting performance and lower energy consumption,whose UDI100-2000 was 37.94%and annual energy consumption performance was 76.28 kWh/(m2·a),indicating a better building performance than the optimized results in the previous case study.