Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

Modeling of an Automatic Optimization System of Cyanide Concentration in Carbon in Leach for Optimal Ore Processing in a Mining Company

The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.

Deep Structure Optimization for Incremental Hierarchical Fuzzy Systems Using Improved Differential Evolution Algorithm

The optimization of the rule base of a fuzzy logic system (FLS) based on evolutionary algorithm has achievednotable results. However, due to the diversity of the deep structure in the hierarchical fuzzy system (HFS) and thecorrelation of each sub fuzzy system, the uncertainty of the HFS’s deep structure increases. For the HFS, a largenumber of studies mainly use fixed structures, which cannot be selected automatically. To solve this problem, thispaper proposes a novel approach for constructing the incremental HFS. During system design, the deep structureand the rule base of the HFS are encoded separately. Subsequently, the deep structure is adaptively mutated basedon the fitness value, so as to realize the diversity of deep structures while ensuring reasonable competition amongthe structures. Finally, the differential evolution (DE) is used to optimize the deep structure of HFS and theparameters of antecedent and consequent simultaneously. The simulation results confirm the effectiveness of themodel. Specifically, the root mean square errors in the Laser dataset and Friedman dataset are 0.0395 and 0.0725,respectively with rule counts of rules is 8 and 12, respectively.When compared to alternative methods, the resultsindicate that the proposed method offers improvements in accuracy and rule counts.

Numerical and Experimental Analysis of A Ducted Propeller Designed by A Fully Automated Optimization Process Under Open Water Condition

A fully automated optimization process is provided for the design of ducted propellers under open water conditions, including 3D geometry modeling, meshing, optimization algorithm and CFD analysis techniques. The developed process allows the direct integration of a RANSE solver in the design stage. A practical ducted propeller design case study is carried out for validation. Numerical simulations and open water tests are fulfilled and proved that the optimum ducted propeller improves hydrodynamic performance as predicted.

OPTIMAL TORQUE CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE WITH AUTOMATIC MECHANICAL TRANSMISSION

In parallel hybrid electrical vehicle （PHEV） equipped with automatic mechanical transmission （AMT）, the driving smoothness and the clutch abrasion are the primary considerations for powertrain control during gearshift and clutch operation. To improve these performance indexes of PHEV, a coordinated control system is proposed through the analyzing of HEV powertrain dynamic characteristics. Using the method of minimum principle, the input torque of transmission is optimized to improve the driving smoothness of vehicle. Using the methods of fuzzy logic and fuzzy-PID, the engaging speed of clutch and the throttle opening of engine are manipulated to ensure the smoothness of clutch engagement and reduce the abrasion of clutch friction plates. The motor provides the difference between the required input torque of transmission and the torque transmitted through clutch plates. Results of simulation and experiments show that the proposed control strategy performs better than the contrastive control system, the smoothness of driving and the abrasion of clutch can be improved simultaneously.

基于一维和三维CFD方法的四级径流式鼓风机扩压器和回流器设计与优化

Soft In Way Inc. performed the aerodynamic design of a 4 stages high pressure radial blower with vaneless diffusers and deswirlers for DMW Corporation in 2021. The nominal pressure ratio of the machine is near 2.Such a pressure ratio often characterizes what would typically be called a compressor, especially if the compression work is performed in one stage. For the subject machine of the present study, the compression work is split into 4 stages.This paper describes the design procedure for this blower, initially focusing in depth on the tradeoffs between work split,rotor diameter, and rotor vane back-sweep angle. The paper then presents a further design and optimization work of different variants of diffuser and deswirler based on aerodynamic performance for this 4 stages radial blower. The number of deswirler blades in the return channel was reduced from 19 to 10 in consideration of manufacturing requirements. To minimize losses in performance due to reduced blade number, several candidates of varied geometry shape deswirler blades were obtained from an automatic design and optimization workflow combining with 3D CFD calculation. All candidates of deswirler were implemented to the entire 4 stages radial blower to analyze machine performance by 3D CFD calculation and the best 10-blade deswirler geometry was determined. 3D CFD analysis shows that 10 blades of deswirler is unable to provide the same pressure rise and efficiency as the original design with 19 blades when all other parts of the design, such as rotor and diffuser are maintained the same. To further improve the blower performance, the similar automatic workflow was applied to study vaned diffuser influence to the blower performance based on the new blower configuration. The number and geometry of best diffuser blades was obtained from the automatic workflow and entire blower performance with vaned diffuser was analyzed and validated by 3D CFD calculation. After finalizing the aerodynamic flow path geometries and configuration of new blower design,performance for new blower and old one are predicted by 1D method with loss model correction and 3D CFD calculation. 1D and 3D CFD calculation results are compared and good agreement is achieved. Though, small discrepancy between them is noticed and reasons are analyzed. Furthermore, 3D CFD calculations with stall determination method based on several stall-indication metrics were performed to determine surge points of the 2 new blower configurations with vaned and vaneless diffuser. A future publication is intended to show the validation of the design with tested performance data.

Multi-population particle swarm optimization algorithm for automatic design of steel frames

Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost effective.Therefore,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design codes.Modifications are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative strategy.The proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design codes.The related parameter influences on optimization results are discussed.For the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65% and can obtain frame with the weight for at least 2.4%lighter.A similar trend can also be observed in cases subjected to Chinese design codes.In addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO results.The purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design codes.It aims to provide a reference for automatic structural optimization design problems even with dimensional complexity.The proposed method can be easily generalized to the optimization problem of other structural systems.

Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China

Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.

Real-time AGC dispatch units considering wind power and ramping capacity of thermal units

The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service.To fulfill the automatic generation control(AGC)and compensate the influence of wind power fluctuations simultaneously,ramping capacity should be considered in the dispatch model of thermals.Meanwhile,conventional methods in this area do not take the impact of transmission loss into the dispatch model,or rely on offline network model and parameters,failing to reflect the real relationships between the wind farms and thermal generators.This paper proposes an online approach for AGC dispatch units considering the above issues.Firstly,the power loss sensitivity is online identified using recursive least square method based on the real-time data of phasor measurement units.It sets up power balance constraint and results in a more accurate dispatch model.Then,an improved multi-objective optimization model of dispatch is proposed and a connection is established between the thermal units with fast ramping capacity and the wind farms with rapid fluctuations.Genetic algorithm is used to solve the dispatch model.The proposed method is compared with conventional methods in simulation case in the IEEE 30-bus system.Finally,simulation results verify the validity and the feasibility of identification method and optimization model.