An Efficient Optimization Design Framework for Low-Resistance Shape of Bionic Amphibious Robot

To realize the low-resistance shape optimization design of amphibious robots,an efficient optimization design framework is proposed to improve the geometric deformation flexibility and optimization efficiency.In the proposed framework,the free-form deformation parametric model of the flat slender body is established and an analytical calculation method for the height constraints is derived.CFD method is introduced to carry out the high-precision resistance calculation and a constrained Kriging-based optimization method is built to improve the optimization efficiency by circularly infilling the new sample points which satisfying the constraints.Finally,the shape of an amphibious robot example is optimized to get the low-resistance shape and the results demonstrate that the presented optimization design framework has the advantages of simplicity,flexibility and high efficiency.

Multi-objective global optimization approach predicted quasi-layered ternary TiOS crystals with promising photocatalytic properties

Titanium dioxide(TiO_(2))has attracted considerable research attentions for its promising applications in solar cells and photocatalytic devices.However,the intrinsic challenge lies in the relatively low energy conversion efficiency of TiO_(2),primarily attributed to the substantial band gaps(exceeding 3.0 eV)associated with its rutile and anatase phases.Leveraging multi-objective global optimization,we have identified two quasi-layered ternary Ti-O-S crystals,composed of titanium,oxygen,and sulfur.The calculations of formation energy,phonon dispersions,and thermal stability confirm the chemical,dynamical and thermal stability of these newly discovered phases.Employing the state-of-art hybrid density functional approach and many-body perturbation theory(quasiparticle GW approach and Bethe-Salpeter equation),we calculate the optical properties of both the TiOS phases.Significantly,both phases show favorable photocatalytic characteristics,featuring band gaps suitable for visible optical absorption and appropriate band alignments with water for effective charge carrier separation.Therefore,ternary compound TiOS holds the potential for achieving high-efficiency photochemical conversion,showing our multi-objective global optimization provides a new approach for novel environmental and energy materials design with multicomponent compounds.

Structural optimization of a reusable seismic frame active link

Circular design encompasses the use of inventive construction methodologies that possess the capability to be readily dismantled,repurposed,or recycled upon reaching the conclusion of their functional lifespan.This work specifically examines the creation of a reusable design case-study idea for seismic frame design,which is commonly employed in steel-frame constructions in New Zealand.A reusable optimized design for the full seismic frame was proposed in the research.Optimizing the dimensions of welded structures,whether in terms of weight or cost,leads to a decrease in the weight of the steel utilized.The decrease in weight is directly associated with a decrease in environ-mental impact,as the environmental impact is directly proportional to the mass of the construction.The environmental consequences associated with welding technique are contingent upon the dimensions of the weld,hence exerting an indirect influence on the overall mass of the structure.Given the presence of mass dependence in all three areas,albeit in distinct manners,this work employed a multi-objective function optimization strategy to simultaneously address these areas while also partially evaluating them separately.On this way substantial reductions can be achieved both at structural mass and environmental effects.

Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

Optimization and Calculation of TbCl_3-ACl (A=Li, Na, K, Rb, Cs) Phase Diagrams

By using CALPHAD (Calculation of Phase Diagram) technique the optimization and calculation of the binary systems of TbCl_3-ACl (A= Li, Na, K, Rb, Cs) were carried out. For describing the Gibbs free energy of liquid phase in these systems the new modified quasichemical model in the pair-approximation for short-range ordering was used. From measured phase equilibria data and experimental integral properties the TbCl_3-ACl phase diagrams were optimized and calculated. A set of thermodynamic functions was optimized based on an interactive computer-assisted analysis. The calculated phase diagrams and thermodynamic data are self-consistent.

Optimization Method for Indoor Thermal Comfort Based on Interactive Numerical Calculation

In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an interactive numerical calculation platform which includes the functions of numerical simulation and optimization is established. The artificial neural network （ANN） and the greedy strategy are introduced into the hill-climbing pattern heuristic search process, and the optimizing search direction can be predicted by using small samples; when searching along the direction using the greedy strategy, the optimal values can be quickly approached. Therefore, excessive external calling of the numerical modeling process can be avoided, and the optimization time is decreased obviously. The experimental results indicate that the satisfied output parameters of air conditioning can be quickly given out based on the interactive numerical calculation platform and the improved search method, and the optimization for indoor thermal comfort can be completed.

Dose Comparison between Eclipse Dose Calculation and Fast Dose Calculator in Single- and Multi-Field Optimization Intensity-Modulated Proton Therapy Plans with Various Multi-Beams for Brain Cancer

The purpose of this study was to grasp current potential problems of dose error in intensity-modulated proton therapy (IMPT) plans. We were interested in dose differences of the Varian Eclipse treatment planning system (TPS) and the fast dose calculation method (FDC) for single-field optimization (SFO) and multi-field optimization (MFO) IMPT plans. In addition, because some authors have reported dosimetric benefit of a proton arc therapy with ultimate multi-fields in recent years, we wanted to evaluate how the number of fields and beam angles affect the differences for IMPT plans. Therefore, for one brain cancer patient with a large heterogeneity, SFO and MFO IMPT plans with various multi-angle beams were planned by the TPS. Dose distributions for each IMPT plan were calculated by both the TPS’s conventional pencil beam algorithm and the FDC. The dosimetric parameters were compared between the two algorithms. The TPS overestimated 400 - 500 cGy (RBE) for minimum dose to the CTV relative to the dose calculated by the FDC. These differences indicate clinically relevant effect on clinical results. In addition, we observed that the maximum difference in dose calculated between the TPS and the FDC was about 900 cGy (RBE) for the right optic nerve, and this quantity also has a possibility to have a clinical effect. The major difference was not seen in calculations for SFO IMPT planning and those for MFO IMPT planning. Differences between the TPS and the FDC in SFO and MFO IMPT plans depend strongly on beam arrangement and the presence of a heterogeneous body. We advocate use of a Monte Carlo method in proton treatment planning to deliver the most precise proton dose in IMPT.

THERMODYNAMIC OPTIMIZATION AND CALCULATION OF THE Fe-Pr SYSTEM

Based on the phase diagram of the Fe-Pr system available,the thermodynamic optimization and calcula- tion of the system have been carried out by the least square method.The lattice stabilities of Fe and Pr are described by the expression recommended by SGTE organization.The liquid phase is described by the subregular solution model.The intermetallic compounds,Fe_(17)Pr_2 and Fe_2Pr,are treated as stoichiometric compounds.The optimized parameters describing phases in the system are presented.The comparision be- tween the calculated and experimentally determined phase diagram shows that the agreement is generally very good except for the liquid+δ-Fe equilibrium.It is suggested to measure this part of phase diagram again.

Calculation Model of Equivalent Strength for Induced Crack Based on Double-K Fracture Theory and Its Optimizing Setting in RCC Arch Dam

By means of fracture testing on roller-compacted concrete （RCC） three-point bending beams with two different specimen sizes, the P-CMOD complete curve for RCC was gained. Furthermore, by applying double-K fracture theory, KiniⅠC,KunⅠC, as well as the critical effective crack length and the critical crack tip opening displacement, were evaluated. Based on the double-K fracture parameters above, the calculation model of equivalent strength for induced crack was established, thus the calculation method on its initiation, stable propagation and unstable fracture was ascertained. Moreover, the finite element simulation analysis of stress field in ShaPai arch dam and the on-site observational splaying points of induced crack at different altitudes validated the reliability of the model. Finally, crack inducer′s optimal setting in RCC arch dam was studied. It improves the design level of induced crack in RCC arch dam and satisfies the necessity of engineering practice.

Pulsed gas–liquid discharge plasma catalytic degradation of bisphenol A over graphene/Cd S:process parameters optimization and O_(3)activation mechanism analysis

In the present work,pulsed gas–liquid hybrid discharge plasma coupled with graphene/Cd S catalyst was evaluated to eliminate bisphenol A(BPA)in wastewater.The optimization of a series of process parameters was performed in terms of BPA degradation performance.The experimental results demonstrated that nearly 90%of BPA(20 mg l^(-1))in the synthetic wastewater(p H=7.5,σ=10μS m^(-1))was degraded by the plasma catalytic system over 0.2 g l^(-1)graphene/Cd S at 19k V with a 4 l min^(-1)air flow rate and 10 mm electrode gap within 60 min.The BPA removal rate increased with increasing the discharge voltage and decreasing the initial BPA concentration or solution conductivity.Nevertheless,either too high or too low an air flow rate,electrode gap,catalyst dosage or initial solution p H would lead to a decrease in BPA degradation.Moreover,optical emission spectroscopy was used to gain information on short-lived reactive species formed from the pulsed gas–liquid hybrid discharge plasma system.The results indicated the existence of several highly oxidative free radicals such as·O and·OH.Finally,the activation pathway of O_(3)on the catalyst surface was analyzed by density functional theory.

Optimization of the Algorithm for Increasing Injection Rate in Water Injection Wells for Pressure Optimization in P Oilfield

In today’s society, with the continuous growth of energy demand, Bohai Oilfield, as an important offshore oil resource base in China, is facing increasingly severe challenges while contributing to national energy security. In order to improve the quality of water injection in the oilfield and gradually achieve efficient and stable production, Bohai Oilfield has launched a water injection well pressure optimization project, focusing on improving the efficiency and quality of water injection in the water injection wells, in order to achieve the optimal water injection plan. In practical work, P Oilfield continues to promote the development of water injection well pressure optimization projects, emphasizing practical exploration and continuous optimization of work plans. However, during the project implementation process, there were some problems, one of which was that the statistics of cumulative injection volume were not scientific enough, resulting in a more comprehensive and accurate presentation of the actual results of pressure optimization work. In the context of continuous improvement work, after careful analysis and research, P Oilfield has decided to optimize the cumulative injection rate algorithm to guide the oilfield’s water injection work in a more refined way, ensuring sufficient and good water injection, and enhancing the oilfield’s production efficiency and comprehensive competitiveness.

Sequential Inverse Optimal Control of Discrete-Time Systems

This paper presents a novel sequential inverse optimal control(SIOC)method for discrete-time systems,which calculates the unknown weight vectors of the cost function in real time using the input and output of an optimally controlled discrete-time system.The proposed method overcomes the limitations of previous approaches by eliminating the need for the invertible Jacobian assumption.It calculates the possible-solution spaces and their intersections sequentially until the dimension of the intersection space decreases to one.The remaining one-dimensional vector of the possible-solution space’s intersection represents the SIOC solution.The paper presents clear conditions for convergence and addresses the issue of noisy data by clarifying the conditions for the singular values of the matrices that relate to the possible-solution space.The effectiveness of the proposed method is demonstrated through simulation results.

Optimal Design of High-Speed Partial Flow Pumps using Orthogonal Tests and Numerical Simulations

To investigate the influence of structural parameters on the performances and internal flow characteristics of partial flow pumps at a low specific speed of 10000 rpm,special attention was paid to the first and second stage impeller guide vanes.Moreover,the impeller blade outlet width,impeller inlet diameter,blade inclination angle,and number of blades were considered for orthogonal tests.Accordingly,nine groups of design solutions were formed,and then used as a basis for the execution of numerical simulations(CFD)aimed at obtaining the efficiency values and heads for each design solution group.The influence of impeller geometric parameters on the efficiency and head was explored,and the“weight”of each factor was obtained via a range analysis.Optimal structural parameters were finally chosen on the basis of the numerical simulation results,and the performances of the optimized model were verified accordingly(yet by means of CFD).Evidence is provided that the increase in the efficiency and head of the optimized model was 12.11%and 23.5 m,respectively,compared with those of the original model.

Rapid Parameter-Optimizing Strategy for Plug-and-Play Devices in DC Distribution Systems under the Background of Digital Transformation

By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.

OPTIMAL SCHEME FOR SEQUENTIAL COMPUTATIONS OF F_m(z) INTEGRALS IN AB INITIO CALCULATIONS----COMBINATORY USE OF UPWARD AND DOWNWARD RECURSIONS

The quantitative rules of the transfer and variation of errors,when the Gaussian integral functions F.(z) are evaluated sequentially by recurring,have been expounded.The traditional viewpoint to negate the applicability and reliability of upward recursive formula in principle is amended.An optimal scheme of upward-and downward-joint recursions has been developed for the sequential F(z) computations.No additional accuracy is needed with the fundamental term of recursion because the absolute error of Fn(z) always decreases with the recursive approach.The scheme can be employed in modifying any of existent subprograms for Fn<z> computations.In the case of p-d-f-and g-type Gaussians,combining this method with Schaad's formulas can reduce,at least,the additive operations by a factor 40%;the multiplicative and exponential operations by a factor 60%.

Optimization of a Centrifugal Pump Used as a Turbine Impeller By Means of an Orthogonal Test Approach

A prototype centrifugal pump with a specific speed of 110 is used to investigate and optimize the performances of a turbine for power generation.Particular attention is given to the design of the internal impeller.The internal flow field is simulated in the framework of a commercial computational fluid dynamics software(ANSYS).Four geometrical parameters of the impeller are considered,i.e.,the inlet diameter,the inlet width,the blade number,and the blade angle.The optimization is carried out on the basis of a three-level approach relying on an orthogonal test method.The results of the numerical simulations show good agreement with the experimental tests under different flow conditions.In accordance with the L9(34)design table,the head and efficiency under the rated flow rate of the nine designed schemes are calculated and processed with the method of range analysis to obtain an optimized model.

Re-entry trajectory optimization using a multiple- interval Radau pseudospectral method

Aiming at increasing the calculation efficiency of the pseudospectral methods, a multiple- interval Radau pseudospectral method （RPM） is presented to generate a reusable launch vehicle （RLV） ＇s optimal re-entry trajectory. After dividing the optimal control problem into many intervals, the state and control variables are approximated using many fixed- and low-degree Lagrange polyno- mials in each interval. Convergence of the numerical discretization is then achieved by increasing the number of intervals. With the application of the proposed method, the normal nonlinear program- ming （NLP） problem transcribed from the optimal control problem can avoid being dense because of the low-degree approximation polynomials in each interval. Thus, the NLP solver can easily compute a solution. Finally, simulation results show that the optimized re-entry trajectories satisfy the path constraints and the boundary constraints successfully. Compared with the single interval RPM, the multiple-interval RPM is significantly faster and has higher calculation efficiency. The results indicate that the multiple-interval RPM can be applied for real-time trajectory generation due to its high effi- ciency and high precision.

Optimization of Additively Decomposed Function with Constraints

We propose a modified evolutionary computation method to solve the optimization problem of additively decomposed function with constraints. It is based on factorized distribution instead of penalty function and any transformation to a linear model or others. The feasibility and convergence of the new algorithm are given. The numerical results show that the new algorithm gives a satisfactory performance.

A Dynamic Memory Allocation Optimization Mechanism Based on Spark

Spark is a distributed data processing framework based on memory.Memory allocation is a focus question of Spark research.A good memory allocation scheme can effectively improve the efficiency of task execution and memory resource utilization of the Spark.Aiming at the memory allocation problem in the Spark2.x version,this paper optimizes the memory allocation strategy by analyzing the Spark memory model,the existing cache replacement algorithms and the memory allocation methods,which is on the basis of minimizing the storage area and allocating the execution area according to the demand.It mainly including two parts:cache replacement optimization and memory allocation optimization.Firstly,in the storage area,the cache replacement algorithm is optimized according to the characteristics of RDD Partition,which is combined with PCA dimension.In this section,the four features of RDD Partition are selected.When the RDD cache is replaced,only two most important features are selected by PCA dimension reduction method each time,thereby ensuring the generalization of the cache replacement strategy.Secondly,the memory allocation strategy of the execution area is optimized according to the memory requirement of Task and the memory space of storage area.In this paper,a series of experiments in Spark on Yarn mode are carried out to verify the effectiveness of the optimization algorithm and improve the cluster performance.

STUDY OF TOPOLOGY OPTIMIZATION FOR THERMO-STRUCTURAL COUPLING FIELD

A number of critical problems of topology optimization concerning the thermostructural coupling field axe studied at length. The governing equations and topology optimization model for the thermal-structural coupling field axe derived, with an adjoint method for sensitivity analysis of the thermo-structural coupling field proposed. The optimization algorithm for coupling field topology optimization is investigated and a flowchart of coupling field topology optimization presented. The theory and algorithms axe implemented and verified by two numerical examples.