The 3D simulation and optimized management model of groundwater systems based on eco-environmental water demand

Through the study of mutual process between groundwater systems and eco-environmental water demand, the eco-environmental water demand is brought into groundwater systems model as the important water consumption item and unification of groundwater抯 economic, environmental and ecological functions were taken into account. Based on eco-environmental water demand at Da抋n in Jilin province, a three-dimensional simulation and optimized management model of groundwater systems was established. All water balance components of groundwater systems in 1998 and 1999 were simulated with this model and the best optimal exploitation scheme of groundwater systems in 2000 was determined, so that groundwater resource was efficiently utilized and good economic, ecologic and social benefits were obtained.

Optimal Parameter and Uncertainty Estimation of a Land Surface Model: Sensitivity to Parameter Ranges and Model Complexities

Most previous land-surface model calibration studies have defined globalranges for their parameters to search for optimal parameter sets. Little work has been conducted tostudy the impacts of realistic versus global ranges as well as model complexities on the calibrationand uncertainty estimates. The primary purpose of this paper is to investigate these impacts byemploying Bayesian Stochastic Inversion (BSI) to the Chameleon Surface Model (CHASM). The CHASM wasdesigned to explore the general aspects of land-surface energy balance representation within acommon modeling framework that can be run from a simple energy balance formulation to a complexmosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem,importance sampling, and very fast simulated annealing. The model forcing data and surface flux datawere collected at seven sites representing a wide range of climate and vegetation conditions. Foreach site, four experiments were performed with simple and complex CHASM formulations as well asrealistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parametersets were used for each run. The results show that the use of global and realistic ranges givessimilar simulations for both modes for most sites, but the global ranges tend to produce someunreasonable optimal parameter values. Comparison of simple and complex modes shows that the simplemode has more parameters with unreasonable optimal values. Use of parameter ranges and modelcomplexities have significant impacts on frequency distribution of parameters, marginal posteriorprobability density functions, and estimates of uncertainty of simulated sensible and latent heatfluxes. Comparison between model complexity and parameter ranges shows that the former has moresignificant impacts on parameter and uncertainty estimations.

Discrete optimization models and methods for management systems of pavement maintenance and rehabilitation

With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four discrete optimization models are proposed for different parties involved in the management system： government,highway agent,con- tractor and the common users.These four optimal decision models are formulated as linear integer programming problems with binary decision variables.The objective function and constraints are based on the pavement performance and prediction model using the pavement condition index （PCI）.Numerical experiments are carried out with the data from a highway system in Sichuan Province which show the feasibility and effectiveness of the proposed models.

COMPREHENSIVE INTRODUCTION TO THE TECHNOLOGY OF GROUNDWATER MODELING AND OPTIMAL MANAGEMENT

Three numeric simulation and optimal management models on groundwater resources are introduced in this paper. These models stand for the present developing levels on the technology of groundwater modeling and optimal management in China, and show the practical application situations of the technology. Each of the technology of unique characteristics and purposes. According to the tests of the practical engineering, these models have played a very important role in solving the difficult problems of groundwater resources.

Influence range of emergency under special events based on CTM

To determine the dynamic influence range of emergencies under special events, the spacial and temporal characteristics of the traffic flow are studied by simulation based on the cell transmission model （CTM）. Based on the traffic management measures used under special events, a semi-dynamic assignment algorithm is proposed, which is combined with an algorithm for logit multi-path traffic assignment and the CTM. In a simple calculation network, the spacial and temporal characteristics of traffic flows which vary with different traffic management schemes are studied, and a method to obtain the influence range of emergency is proposed by computing the jam time of the intersections. By contrasting the average delay of each vehicle, the dissipation effect is studied under two different traffic management schemes. The example shows that the spatial and temporal variety of the traffic flow can be easily simulated and the influence range of emergency can be confirmed by the method based on the CTM. The proposed method provides a new idea for decision-making on traffic management under emergency under special events.

A genetic algorithm based stochastic programming model for air quality management

This paper presents a model that can aid planners in defining the total allowable pollutant discharge in the planning region, accounting for the dynamic and stochastic character of meteorological conditions. This is accomplished by integrating Monte Carlo simulation and using genetic algorithm to solve the model. The model is demonstrated by using a realistic air urban scale SO 2 control problem in the Yuxi City of China. To evaluate effectiveness of the model, results of the approach are shown to compare with those of the linear deterministic procedures. This paper also provides a valuable insight into how air quality targets should be made when the air pollutant will not threat the residents' health. Finally, a discussion of the areas for further research are briefly delineated.

A simulation-based two-stage interval-stochastic programming model for water resources management in Kaidu-Konqi watershed,China

This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presents a distributed model predictive control DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints GRCs, load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints. © 2014 Chinese Association of Automation.

Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency.

Research on logistics domain-oriented cloud resource management model and architecture

To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.

Research on Welding Quality Traceability Model of Offshore Platform Block Construction Process

Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.

A Modified Pareto Dominance Based Real-Coded Genetic Algorithm for Groundwater Management Model

This study proposes a groundwater management model in which the solution is performed through a combined simulation-optimization model. In the proposed model, a modular three-dimensional finite difference groundwater flow model, MODFLOW is used as simulation model. This model is then integrated with an optimization model, in which a modified Pareto dominance based Real-Coded Genetic Algorithm (mPRCGA) is adopted. The performance of the proposed mPRCGA based management model is tested on a hypothetical numerical example. The results indicate that the proposed mPRCGA based management model is an effective way to obtain good optimum management strategy and may be used to solve other type of groundwater simulation-optimization problems.

Comparative research on three-echelon and two-echelon medicine inventory model with positive lead-time

According to the principle of minimizing total cost, the three-echelon optimized medical inventory model with stochastic lead-time and two-echelon optimized medicine inventory model with fixed lead-time are established. The relationship between lead-time and inventory cost is studied by Matlab software. It shows that the variety of lead-time has an important effect on medicine inventory systems. Numerical simulation and sensitivity analysis of two models are presented by Lingo software. Based on analysis, it is concluded that the two-echelon model with lead-time results in inventory cost savings, and keeps the quality of care as reflected in service levels when compared with the three-echelon network structure.

Layout effects and optimization of runoff storage and filtration facilities based on SWMM simulation in a demonstration area

The layout effects and optimization of runoff storage and filtration facilities are crucial to the efficiency and management of the cost of runoff control, but related research is still lacking. In this study, scenarios with different layouts were simulated using the storm water management model(SWMM), to investigate the layout effects on control efficiency with different precipitations. In a rainfall event with 50 mm of precipitation in two hours, 1820 scenarios with different layouts of four facilities constructed in 16 sub-catchments were simulated, the reduction rates of internal flow presented a standard deviation of 10.9%, and the difference between the maximum and minimum reduction rates reached59.7%. Based on weighting analysis, an integrated ranking index was obtained and used to determine the optimal layout scenarios considering different rainfall events. In the optimal scenario(storage and filtration facilities constructed in sub-catchments 14, 12, 7, and 2), the reduction rates of the total outflow reached 31.4%, 26.4%, and 14.7%, respectively, with 30, 50, and 80 mm of precipitation. The reduction rate of the internal outflow reached 95% with 50 mm of precipitation and approximately 56% with 80 mm of precipitation.

Test selection and optimization for PHM based on failure evolution mechanism model

The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.

Energy Management Control StraEnergy Management Control Strategy for Renewable Energy System Based on Spotted Hyena Optimizertegy for Renewable Energy System Based on Spotted Hyena Optimizer

Hydrocarbons,carbon monoxide and other pollutants from the transportation sector harm human health in many ways.Fuel cell(FC)has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy.The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand.Therefore,adding energy storage systems is necessary.However,to manage and distribute the power-sharing among the hybrid proton exchange membrane(PEM)fuel cell(FC),battery storage(BS),and supercapacitor(SC),an energy management strategy(EMS)is essential.In this research work,an optimal EMS based on a spotted hyena optimizer(SHO)for hybrid PEM fuel cell/BS/SC is proposed.The main goal of an EMS is to improve the performance of hybrid FC/BS/SC and to reduce the amount of hydrogen consumption.To prove the superiority of the SHO method,the obtained results are compared with the chimp optimizer(CO),the artificial ecosystem-based optimizer(AEO),the seagull optimization algorithm(SOA),the sooty tern optimization algorithm(STOA),and the coyote optimization algorithm(COA).Two main metrics are used as a benchmark for the comparison:the minimum consumed hydrogen and the efficiency of the system.The main findings confirm that the minimum amount of hydrogen consumption and maximum efficiency are achieved by the proposed SHO based EMS.

Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system's ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.

Optimal Matching Analysis of Net Buoyancy and Pitching Angle for Underwater Gliders

Control parameter optimization is an efficient way to improve the endurance of underwater gliders(UGs),which influences their gliding efficiency and energy consumption.This paper analyzes the optimal matching between the net buoyancy and the pitching angle and proposes a segmented control strategy of Petrel-L.The optimization of this strategy is established based on the gliding range model of UG,which is solved based on the approximate model,and the variations of the optimal control parameters with the hotel load are obtained.The optimization results indicate that the segmented control strategy can significantly increase the gliding range when the optimal matching between the net buoyancy and the pitching angle is reached,and the increase rate is influenced by the hotel load.The gliding range of the underwater glider can be increased by 10.47%at a hotel load of 0.5 W.The optimal matching analysis adopted in this study can be applied to other UGs to realize endurance improvement.

Optimal nitrogen fertilization of boreal conifer forest

Background： Forest fertilization offers a means to increase the production of renewable resources.Nitrogen is the most common fertilizer in boreal upland forests.There is plenty of research on the effect of nitrogen fertilization on volume growth, but less research on the optimal timing of fertilization and optimal management of fertilized stands.Methods： This study used simulation and optimization to analyze the profitability of fertilization, optimal management of fertilized stands and the effects of fertilization on cash flows and timber yields.The management of 100 stands representing the most common growing sites of Scots pine and Norway spruce was optimized.Results： Fertilization improved profitability in most of the analyzed stands.Profitability improved most in spruce stands growing on mesic site.Improving stem quality increased the economic benefit of fertilization.The timber yields of medium-aged conifer stands can be increased by almost 1 m^3·ha^（-1）·a^（-1）（15%） in sub-xeric pine and mesic spruce sites and about 0.5 m^3·ha^（-1）·a^（-1）（5%） in mesic pine and herb-rich spruce sites when the recommended nitrogen dose（150kg·ha^（-1）） is applied once in 30 years.Conclusions： Nitrogen fertilization of boreal conifer forest should be used mainly in spruce-dominated stands growing on medium sites.The gains are the highest in stands where the mean tree diameter is 16–20 cm and stand basal area is 14–20 m^2·ha^（-1）.

A Reliable and Accurate Calculation of Excitation Capacitance Value for an Induction Generator Based on Interval Computation Technique

A squirrel cage induction generator （SCIG） offers many advantages for wind energy conversion systems but suffers from poor voltage regulation under varying operating conditions. The value of excitation capacitance （C exct ） is very crucial for the selfexcitation and voltage build-up as well as voltage regulation in SCIG. Precise calculation of the value of C exct is, therefore, of considerable practical importance. Most of the existing calculation methods make use of the steady-state model of the SCIG in conjunction with some numerical iterative method to determine the minimum value of C exct . But this results in over estimation, leading to poor transient dynamics. This paper presents a novel method, which can precisely calculate the value of C exct by taking into account the behavior of the magnetizing inductance during saturation. Interval analysis has been used to solve the equations. In the proposed method, a range of magnetizing inductance values in the saturation region are included in the calculation of C exct , required for the self-excitation of a 3-φ induction generator. Mathematical analysis to derive the basic equation and application of interval method is presented. The method also yields the magnetizing inductance value in the saturation region which corresponds to an optimum C exct（min） value. The proposed method is experimentally tested for a 1.1 kW induction generator and has shown improved results.