Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

Probability Simulation Optimization Approach Using Orthogonal Genetic Algorithm

In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach synthesizes the computer simulation technology, orthogonal genetic algorithm and statistical test method faultlessly, which can solve complex optimization problem effectively. In this paper, the author gives the correlative conception of probability simulation optimization and describes the probability simulation optimization approach using orthogonal genetic algorithm in detail. Theoretically speaking, it has a strong rationality and maneuverability that can apply probability method in solving the complex optimization problems with uncertain phenomenon. In demonstration, the optimization performance of this method is better than other traditional methods. Simulation resuh suggests that the approach referred to this paper is feasible, correct and valid.

Simulation optimization for train movement on a single-track railway

Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traffic. Here a kind of single-track railway is considered. Our aim is to reduce the energy consumption of train movement and ensure the train being on time by controlling the velocity curve of train movement. The simulation results indicate that the proposed model is effective for optimizing train movement. In addition, some major characteristics of train movement can be well captured. This method provides a new way to optimize train movement in railway traffic.

On-Line Tuning Scheme for the Generalized Predictive Controller via Simulation Optimization

Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria.

Stochastic systems simulation optimization

With the advance of new computational technology,stochastic systems simulation and optimization has become increasingly a popular subject in both academic research and industrial applications.This paper presents some of recent developments about the problem of optimizing a performance function from a simulation model.We begin by classifying different types of problems and then provide an overview of the major approaches,followed by a more in-depth presentation of two specific areas:optimal computing budget allocation and the nested partitions method.

Numerical simulation and optimization of the cylinder head water jacket based on the two-phase flow boiling heat transfer

Boiling heat transfer and the controllability of the thermal load of the cylinder head were studied.The thermodynamic phase change characteristics of the cylinder head coolant were considered and the mass,momentumand energy transfers between two phases were calculated with the interface transfer submodels by using the computational fluid dynamics software CFX. Results showed that compared with the single-phase flow without considering the boiling heat transfer,the sub-cooled boiling heat transfer of the cylinder head was greatly increased. According to the results of the numerical simulation,an optimized structure of the water jacket was proposed. Finally,temperature and velocity of coolant,diameter of flow passage and mean bubble diameter that influences sub-cooled boiling were studied using the orthogonal experiment method.

Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Manufacturing Resource Planning Technology Based on Genetic Programming Simulationnn

Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.

Multiphase Flow Simulation of New Vapor Distributor in Dividing Wall Column and Control Mechanism

A new vapor distributor based on the Coanda effect is added to the Dividing Wall column(DWC),and the multiphase flow simulation is performed using ANSYS Fluent by this model.The results show that with the addition of the liquid phase,the new vapor distributor still follows the Coanda effect.Hereby,the vapor is ejected from the slits of the distributor to take away the surrounding vapor,and a negative pressure is formed under the distributor,so as to achieve the purpose of regulating Rv.Analogously to the working principle of vapor distributor,a certain amount of vapor is drawn out from a position of prefractionator,which is equivalent to the vapor ejected by the distributor.The same amount of vapor is fed into the main column,which corresponds to the gas phase at the inlet of the distributor.The Rv is adjusted by changing the speed of the input or output vapor.Simulation results show that adding this control mechanism on the basis of temperature or concentration control structure can better achieve the effect of vapor distribution.

APPLYING PARTICLE SWARM OPTIMIZATION TO JOB-SHOPSCHEDULING PROBLEM

A new heuristic algorithm is proposed for the problem of finding the minimummakespan in the job-shop scheduling problem. The new algorithm is based on the principles ofparticle swarm optimization (PSO). PSO employs a collaborative population-based search, which isinspired by the social behavior of bird flocking. It combines local search (by self experience) andglobal search (by neighboring experience), possessing high search efficiency. Simulated annealing(SA) employs certain probability to avoid becoming trapped in a local optimum and the search processcan be controlled by the cooling schedule. By reasonably combining these two different searchalgorithms, a general, fast and easily implemented hybrid optimization algorithm, named HPSO, isdeveloped. The effectiveness and efficiency of the proposed PSO-based algorithm are demonstrated byapplying it to some benchmark job-shop scheduling problems and comparing results with otheralgorithms in literature. Comparing results indicate that PSO-based algorithm is a viable andeffective approach for the job-shop scheduling problem.

Optimization of stratification scheme for a fishery-independent survey with multiple objectives

Fishery-independent surveys are often used for collecting high quality biological and ecological data to support fisheries management. A careful optimization of fishery-independent survey design is necessary to improve the precision of survey estimates with cost-effective sampling efforts. We developed a simulation approach to evaluate and optimize the stratification scheme for a fishery-independent survey with multiple goals including estimation of abundance indices of individual species and species diversity indices. We compared the performances of the sampling designs with different stratification schemes for different goals over different months. Gains in precision of survey estimates from the stratification schemes were acquired compared to simple random sampling design for most indices. The stratification scheme with five strata performed the best. This study showed that the loss of precision of survey estimates due to the reduction of sampling efforts could be compensated by improved stratification schemes, which would reduce the cost and negative impacts of survey trawling on those species with low abundance in the fishery-independent survey. This study also suggests that optimization of a survey design differed with different survey objectives. A post-survey analysis can improve the stratification scheme of fishery-independent survey designs.

Stability analysis of backflling in subsiding area and optimization of the stoping sequence

In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the subsiding area. In this paper, taking Zhangfushan iron mine as an example, the ore body and the general layout are focused on the safety of backflling of mined-out area. Then, we use the ANSYS software to construct a three-dimensional(3D) model for the mining area in the Zhangfushan iron mine. According to the simulation results of the initial mining stages, the ore body is stoped step by step as suggested in the design. The stability of the backflling is back analyzed based on the monitored displacements, considering the stress distribution to optimize the stoping sequence. The simulations show that a reasonable stoping sequence can minimize the concentration of high compressive stress and ensure the safety of stoping of the ore body.

Uniformity evaluation and optimization of fluid flow characteristics in a seven-strand tundish

The effect of flow control devices（FCDs） on the uniformity of flow characteristics in a seven-strand symmetrical trapezoidal tundish was studied using both an experimental 1：2.5 hydraulic model and a numerical simulation of a 1：1 geometric model.The variation coefficient（CV） was defined to evaluate the flow uniformity of the seven-strand tundish.An optimized FCD configuration was proposed on the basis of the evaluation of experimental results.It is concluded that a turbulence inhibitor（TI） and U-type dam are essential to improve the uniformity of fluid flow in the seven-strand tundish.In addition,the configuration of inclination T-type dams with a height of 200 mm between the second and third strands and with a height of 300 mm between the third and fourth strands can minimize the proportion of dead zone.After optimizing the configuration of FCDs,the variation coefficient reduces below 20%of the mean value,and the average proportion of dead zone is just 14.6%;in addition,the temperature fluctuation between the strands could be controlled within 0.6 K.In summary,the uniformity of flow and temperature in the seven-strand tundish is greatly improved.

Solving algorithm for TA optimization model based on ACO-SA

An ant colony optimization （ACO）-simulated annealing （SA）-based algorithm is developed for the target assignment problem （TAP） in the air defense （AD） command and control （C2） system of surface to air missile （SAM） tactical unit. The accomplishment process of target assignment （TA） task is analyzed. A firing advantage degree （FAD） concept of fire unit （FU） intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.

Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

Finite element（FE） is a powerful tool and has been applied by investigators to real-time hybrid simulations（RTHSs）. This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time（TET） decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method（CDM）, the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ（λ = 4） method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

Optimization of Shanghai marine environment monitoring sites by integrating spatial correlation and stratified heterogeneity

The water quality grades of phosphate（PO4-P） and dissolved inorganic nitrogen（DIN） are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validation is used to determine the statistical inference method. To minimize absolute average errors and error mean squares,stratified Kriging（SK） interpolation is applied to DIN and ordinary Kriging（OK） interpolation is applied to PO4-P.Ten percent of the sites is adjusted by considering their impact on the change in deviations in DIN and PO4-P interpolation and the resultant effect on areas with different water quality grades. Thus, seven redundant historical sites are removed. Seven historical sites are distributed in areas with water quality poorer than Grade IV at the north and south branches of the Changjiang（Yangtze River） Estuary and at the coastal region north of the Hangzhou Bay. Numerous sites are installed in these regions. The contents of various elements in the waters are not remarkably changed, and the waters are mixed well. Seven sites that have been optimized and removed are set to water with quality Grades III and IV. Optimization and adjustment of unrestricted areas show that the optimized and adjusted sites are mainly distributed in regions where the water quality grade undergoes transition.Therefore, key sites for adjustment and optimization are located at the boundaries of areas with different water quality grades and seawater.

Simulation and Optimized Design of Grid Concentration Transducer for Two-Phase Flow

A new concentration transducer for the measurement of gas/solid two-phase flow in the profile of pipeline was studied. The design of grid electrode was employed, and hence the distribute of electric field in the space was homogeneous effectively. The variance of measurement value for the influence of flow regime variations has greatly reduced, and the precision of measurement was improved. Meanwhile, optimization of axial property in the grid electrode increases the ability of tracing and measuring of the concentration signal in real-time.

Optimized Simulation Design of Double Glass Curtain Wall Shading System in Hot Summer and Cold Winter Zone

The glass curtain wall is widely favored by the owners for its good appearance modeling effect. In using process,however,excessive energy consumption,low level indoor comfort and other problems of glass curtain wall are often exposed. Aiming at office buildings in hot Summer and cold Winter zone,taking the optimization of thermal comfort of double glass curtain wall in the summer and the reduction of building energy consumption throughout the year as the breakthrough point,using the method of energy simulation analysis,through changing the size of internal shading component in the simulated room,this paper analyzes and summarizes the variation law of its energy consumption value,to explore the relatively reasonable design plan of shading systems of the building with glass curtain wall.

FMS Scheduling Simulation Based on an Evolution Algorithm

A FMS (flexible manufacturing system)scheduling algorithm based on an evolution algorithm (EA) is developed by intensively analyzing and researching the scheduling method in this paper.Many factors related to FMS scheduling are considered sufficiently.New explanations for a common kind of the encoding model are given.The rationality of encoding model is ensured by designing a set of new encoding methods,while the simulation experiment is performed.The results show that a FMS scheduling optimum problem with multi-constraint conditions can be effectively solved by a FMS scheduling simulation model based on EA.Compating this method with others,this algorithm has the advantage of good stability and quick convergence.

Preliminary Hydrogeologic Modeling and Optimal Monitoring Network Design for a Contaminated Abandoned Mine Site Area: Application of Developed Monitoring Network Design Software

In abandoned mine sites, i.e., mine sites where mining operations have ended, wide spread contaminations are often evident, but the potential sources and pathways of contamination especially through the subsurface, are difficult to identify due to inadequate and sparse geochemical measurements available. Therefore, it is essential to design and implement a planned monitoring net-work to obtain essential information required for establishing the potential contamination source locations, i.e., waste dumps, tailing dams, pits and possible pathways through the subsurface, and to design a remediation strategy for rehabilitation. This study presents an illustrative application of modeling the flow and transport processes and monitoring network design in a study area hydrogeologically resembling an abandoned mine site in Queensland, Australia. In this preliminary study, the contaminant transport process modeled does not incorporate the reactive geochemistry of the contaminants. The transport process is modeled considering a generic conservative contaminant for the illustrative purpose of showing the potential application of an optimal monitoring design methodology. This study aims to design optimal monitoring network to: 1) minimize the contaminant solute mass estimation error;2) locate the plume boundary;3) select the monitoring locations with (potentially) high concentrations. A linked simulation optimization based methodology is utilized for optimal monitoring network design. The methodology is applied utilizing a recently developed software package CARE-GWMND, developed at James Cook University for optimal monitoring network design. Given the complexity of the groundwater systems and the sparsity of pollutant concentration observation data from the field, this software is capable of simulating the groundwater flow and solute transport with spatial interpolation of data from a sparse set of available data, and it utilizes the optimization algorithm to determine optimum locations for implementing monitoring wells.