Molecular Dynamic Simulation on the Absorbing Process of Isolating and Coating of α-olefin Drag Reducing Polymer

The absorbing process in isolating and coating process of α-olefin drag reducing polymer was studied by molecular dynamic simulation method, on basis of coating theory of α-olefin drag reducing polymer particles with polyurethane as coating material. The distributions of sodium laurate, sodium dodeeyl sulfate, and sodium dodeeyl benzene sulfonate on the surface of α-olefin drag reducing polymer particles were almost the same, but the bending degrees of them were obviously different. The bending degree of SLA molecules was greater than those of the other two surfactant molecules. Simulation results of absorbing and accumulating structure showed that, though hydrophobie properties of surfactant molecules were almost the same, water density around long chain sulfonate sodium was bigger than that around alkyl sulfate sodium. This property goes against useful absorbing and accumulating on the surface of α-olefin drag reducing polymer particles; simulation results of interactions of different surfactant and multiple hydroxyl compounds on surface of particles showed that, interactions of different surfaetant and one kind of multiple hydroxyl compound were similar to those of one kind of surfaetant and different multiple hydroxyl compounds. These two contrast types of interactions also exhibited the differences of absorbing distribution and closing degrees to surface of particles. The sequence of closing degrees was derived from simulation; control step of addition polymerization interaction in coating process was absorbing mass transfer process, so the more closed to surface of particle the multiple hydroxyl compounds were, the easier interactions With isoeyanate were. Simulation results represented the compatibility relationship between surfactant and multiple hydroxyl compounds. The isolating and coating processes of α-olefin drag reducing polymer were further understood on molecule and atom level through above simulation research, and based on the simulation, a referenced theoretical basis was provided for practical optimal selection and experimental preparation of α-olefin drag reducing polymer particles suspension isolation agent.

Optimal Design and Dynamic Simulation of Mountain Bike with Rear Suspension

This paper investigates the dynamic design methodology of mountain bikes with rear suspension. Firstly, a multi-rigid body dynamic model of rider and mountain bike coupled system is constructed. The rider model includes 19 skeletons, 18 joints and 118 main muscles. Secondly, to validate the feasibility of the model, an experiment test is designed to reflect the real cycling status. Finally, aiming at enhancing the performance of the rider vibration comfort, the scale parameters of rear suspension are optimized with computer simulation and uniform design. The mathematical model in the vibration performance and the design variables is constructed with regression analysis. The result shows that when the length of side link is 90 mm, the length of connected rod is 336.115 1 mm and the included angle between absorber and side link is 60°, the mountain bike has better vibration comfort. This study and relevant conclusions are of practical importance to the design of the mountain bike＇s rear suspension system.

CAS-based Water Resources Optimal Allocation and Dynamic Simulation for Sewage Irrigation Area

Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilization of agricultural production and waste water resources.The results demonstrated that the difference of crop energy capture mainly depended on the development stage.Waste water with a certain concentration was able to promote crop growth,while excessive concentration inhibited crop growth.The correlation between water absorption rate and leaf area index was close(R=0.9498,p<0.01).The amount of bad seeds increased at a speed of 34.7·d^-1,when system irrigated randomly in the seedling stage,while it tended to remain stable at a speed of 0.3·d^-1 after plants entering the mature stage which impacted the total yields of crops.

Desulfurization characteristics of slaked lime and regulation optimization of circulating fluidized bed flue gas desulfurization process--A combined experimental and numerical simulation study

Circulating fluidized bed flue gas desulfurization(CFB-FGD) process has been widely applied in recent years. However, high cost caused by the use of high-quality slaked lime and difficult operation due to the complex flow field are two issues which have received great attention. Accordingly, a laboratory-scale fluidized bed reactor was constructed to investigate the effects of physical properties and external conditions on desulfurization performance of slaked lime, and the conclusions were tried out in an industrial-scale CFB-FGD tower. After that, a numerical model of the tower was established based on computational particle fluid dynamics(CPFD) and two-film theory. After comparison and validation with actual operation data, the effects of operating parameters on gas-solid distribution and desulfurization characteristics were investigated. The results of experiments and industrial trials showed that the use of slaked lime with a calcium hydroxide content of approximately 80% and particle size greater than 40 μm could significantly reduce the cost of desulfurizer. Simulation results showed that the flow field in the desulfurization tower was skewed under the influence of circulating ash. We obtained optimal operating conditions of 7.5 kg·s^(-1)for the atomized water flow, 70 kg·s^(-1)for circulating ash flow, and 0.56 kg·s^(-1)for slaked lime flow, with desulfurization efficiency reaching 98.19% and the exit flue gas meeting the ultraclean emission and safety requirements. All parameters selected in the simulation were based on engineering examples and had certain application reference significance.

Dynamic Simulation and Optimization Design of the Pendulum Ring Mechanism Based on ADAMS

For pendulum ring mechanism, the working principle is analyzed by using the ADAMS software. Confirming the simulation to accord with the actual motion law, the main bars＇ length is taken as the design variables in order to optimize the cutting speed. The optimization results show that the length of the pendulum rod increases by 3.22%, the cutting speed increases by 30. 8%. It shows that the length of pendulum rod determines the cutting speed at a given pendulum angle. Designers can adjust the length of pendulum rod so as to select the appropriate cutting speed. The virtual prototype technology could the performance of the product is not only improved, and the design efficiency is also done.

Dynamic simulation and optimization approach to construction diversion of hydraulic and hydroelectric projects

To solve the engineering and scientific problems in construction diversion and its simulation analysis, a complete scheme is presented. Firstly, the complex constraint relationship was analyzed among main buildings, diversion buildings and flow control. Secondly, the time-space relationship model of construction diversion system and the general block diagram-oriented simulation model of diversion process were set up. Then, the corresponding numerical simulation method and 3D dynamic visual simulation method were put forward. Further, the simulation and optimization platform of construction diversion control process was developed, integrated with simulation modeling, computation and visualization. Finally, these methods were applied to a practical project successfully, showing that the modeling process is convenient, the computation and the visual analysis can be coupled effectively, and the results conform to practical state. They provide new theoretical principles and technical measures for analyzing the control problems encountered in construction diversion of hydraulic and hydroelectric engineering under complex conditions.

Simulation and optimization approach for uncertainty-based short-term planning in open pit mines

Accuracy in predictions leads to better planning with a minimum of opportunity lost. In open pit mining,the complexity of operations, coupled with a highly uncertain and dynamic production environment,limit the accuracy of predictions and force a reactive planning approach to mitigate deviations from original plans. A simulation optimization framework/tool is presented in this paper to account for uncertainties in mining operations for robust short-term production planning and proactive decision making. This framework/tool uses a discrete event simulation model of mine operations, which interacts with a goalprogramming based mine operational optimization tool to develop an uncertainty based short-term schedule. Using scenario analysis, this framework allows the planner to make proactive decisions to achieve the mine's operational and long-term objectives. This paper details the development of simulation and optimization models and presents the implementation of the framework on an iron ore mine case study for verification through scenario analysis.

Distribution System Optimization Planning Based on Plant Growth Simulation Algorithm

An approach for the integrated optimization of the construction/expansion capacity of high-voltage/ medium-voltage (HV/MV) substations and the configuration of MV radial distribution network was presented using plant growth simulation algorithm (PGSA). In the optimization process, fixed costs correspondent to the investment in lines and substations and the variable costs associated to the operation of the system were considered under the constraints of branch capacity, substation capacity and bus voltage. The optimization variables considerably reduce the dimension of variables and speed up the process of optimizing. The effectiveness of the proposed approach was tested by a distribution system planning.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Cooperative Path Dynamic Planning Model of UCAV Team Based on Global Optimization Method

Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.

Study on Gait Planning of Dynamic Walking of Biped Robots Based on Optimization Theory

In this paper, two important problems in the gait planning of dynamic walking of biped robot, i.e., finding inverse kinematic solution and constructing joint trajectories, are studied in detail by adopting complex optimization theory. The optimization algorithm for finding the inverse kinematic solution is developed, the construction method of joint trajectories is given, and the gait planning method of dynamic walking of biped robots is proposed.

Application of Aerodynamic Optimization Design and Dynamic Numerical Simulation in UAV Design

In the past two decades,the world’s unmanned aerial vehicle(UAV)industry has developed rapidly.Various kinds of UAVs have been used in military and civilian fields.Based on the characteristics of UAVs and the development of aerodynamics,this article analyzes the development of aerodynamic optimization design and dynamic numerical simulation technology,then lists engineering applications.Both aerodynamic optimization design and dynamic numerical simulation have greatly shortened the UAV design period and reduced the research and design cost.These two methods gradually replace traditional methods such as wind tunnel test.

Dynamic Analysis and Optimization of Pneumatic Wedge-Shaped Launcher for UAV

The constitution,structure,working principle and launching process of the wedge-shaped pneumatic launcher of an unmanned aerial vehicle(UAV)are described.By simplifying its physical model,two dynamic models of the UAV launch system are established based on Lagrange equation and MSC.ADAMS,respectively.The curves of the acceleration and the velocity of UAV changing with time are obtained.The simulation results are compared with the experimental results to verify the correctness of the model.Then,the influence of the parameters on the launch is explored.Finally,the system is optimized.The maximum overload and the acceleration fluctuation are reduced.

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.

CFD-Based Optimization of Hot Primary-Air Pipe Networks in Power Plant Milling Systems

A hot primary-air pipe system is the bridge connecting an air-preheater with a coal mill in power generation stations.The effective geometrical configuration of the pipe network greatly affects the air flow distribution and consequently influences the safe and economic operation of milling systems in power stations.In order to improve the properties of the air flow,in the present work the SIMPLEC method is used to simulate numerically the flow field for the original layout of the system.As a result,the internal mechanisms influencing the uneven pressure drop in each branch are explored and three optimization schemes are proposed accordingly.The numerical results indicate that,for the original layout,the local pressure drop of the tee section accounts for approximately 74%of the total drop of the system,with other pressure drops depending on the specific branch considered.It is shown that after optimization,a roughly balanced flow resistance and flow rate can be obtained.Compared with the original layout,the pressure drop relating to different branches is significantly reduced.

Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.

Weighted Time-Based Global Hierarchical Path Planning in Dynamic Environment

A weighted time-based global hierarchical path planning method is proposed to obtain the global optimal path from the starting point to the destination with time optimal control. First, the grid-or graph-based modeling is performed and the environment is divided into a set of grids or nodes. Then two time-based features of time interval and time cost are presented. The time intervals for each grid are built, during each interval the condition of the grid remains stable, and a time cost of passing through the grid is defined and assigned to each interval. Furthermore, the weight is introduced for taking both time and distance into consideration, and thus a sequence of multiscale paths with total time cost can be achieved. Experimental results show that the proposed method can handle the complex dynamic environment, obtain the global time optimal path and has the potential to be applied to the autonomous robot navigation and traffic environment.

Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot

Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.

The Development of Autonomous Dynamic Trajectory Optimization Control of Launch Vehicles

This paper first introduces the technical requirements for autonomous flight, with a brief review of the International Academy of Astronautics(IAA) study group, "autonomous dynamic trajectory optimization control of launch vehicle". Two research scenarios, ascent rescue and powered descent, are compared from the viewpoint of optimal control. On this basis, the technologies on the autonomous trajectory planning and control under the thrust-drop failures in the ascending phase, and the autonomous guidance method during the powered landing for the recovery of the rockets are discussed respectively. For the ascending problem, the characteristics of different solutions, including the iterative guidance method(IGM)-based residual carrying capacity evaluation, the state-triggered indices(STI), the joint planning with the payload’s performance, and the multiple graded optimization(MGO), are analyzed for comparison. For the landing problem, the challenges such as the feasible region reduction caused by high thrust weight ratio(HTWR) and the disturbance adaptability brought by the limited feasible region, are studied in detail, as well as the onboard planning demonstration flight in China are introduced. Finally, the foundations supporting the above methods are summarized, which play an important role in promoting the flight autonomy.