Design and Optimization of Dual-Winding Fault-Tolerant Permanent Magnet Motor

To improve the performance of the traditional fault-tolerant permanent magnet(PM)motor,the design and optimal schemes of dual-winding fault-tolerant permanent magnet motor(DWFT-PMM)are proposed and investigated.In order to obtain small cogging torque ripple and inhibiting the short-circuit current,the air gap surface shape of the PM and the anti short-circuits reactance parameters are designed and optimized.According to the actual design requirements of an aircraft electrical actuation system,the parameters,finite element analysis and experimental verification of the DWFT-PMM after optimal design are presented.The research results show that the optimized DWFT-PMM owns the merits of strong magnetic isolation,physics isolation,inhibiting the short circuit current,small cogging torque ripple and high fault tolerance.

Design and Optimization of Omnidirectional Band Gap for One-Dimensional Periodic and Quasiperiodic Phononic Heterostructures

A new kind of one-dimensional multilayer phononie heterostructure is constructed to obtain a broad acoustic omnidirectional reflection （ODR） band. The heterostructure is formed by combining finite periodic phononic crystals （PnCs） and Fibonacci （or Thue-Morse） quasiperiodic PnCs. From the numerical results performed by the transfer matrix method, it is found that the ODR bands can be enlarged obviously by using the combination of periodic and quasi-periodic PnCs. Moreover, an application of particle swarm optimization in designing and optimizing acoustic ODR bands is reported. With regards to different thickness ratios and periodic numbers in the heterostructure, we give some optimization examples and finally achieve phononic heterostructure with a very broad ODR bandwidth. The result provides a new approach to achieve broad acoustic ODR bandwidth, and will be applied in design of omnidirectional acoustic mirrors.

Multidisciplinary Design and Optimization of Satellite Launch Vehicle Using Latin Hypercube Design of Experiments

The design of new Satellite Launch Vehicle （SLV） is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Low Earth Orbit （LEO） bound SLV comprising of solid and liquid stages with the use of Genetic Algorithm （GA） as global optimizer. Convergence of GA is improved by introducing initial population based on the Design of Experiments （DOE） Technique. Latin Hypercube Sampling （LHS）-DOE is used for its good space filling properties. LHS is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. In SLV design minimum Gross Lift offWeight （GLOW） concept is traditionally being sought. Since the development costs tend to vary as a function of GLOW, this minimum GLOW is considered as a minimum development cost concept. The design approach is meaningful to initial design sizing purpose for its computational efficiency gives a quick insight into the vehicle performance prior to detailed design.

Neural Network aided PMSM multi-objective design and optimization for more-electric aircraft applications

This study uses the Neural Network(NN)technique to optimize design of surfacemounted Permanent Magnet Synchronous Motors(PMSMs)for More-Electric Aircraft(MEA)applications.The key role of NN is to provide dedicated correction factors for the analytical PMSM mass and loss estimation within the entire design space.Based on that,a globally optimal design can be quickly obtained.Matching the analytical estimation with Finite-Element Analysis(FEA)is the main research target of training the NN.Conventional analytical formulae serve as the basis of this study,but they are prone to loss accuracy(especially for a large design space)due to their assumptions and simplifications.With the help of the trained NNs,the analytical motor model can give an estimation as accurate as the FEA but with super less time during the optimization process.The Average Correction Factor(ACF)approach is regarded as the comparison method to demonstrate the excellent performance of the proposed NN model.Furthermore,a NN aided three-stage-sevenstep optimization methodology is proposed.Finally,a Pole-10-Slot-12 PMSM case study is given to demonstrate the feasibility and gain of the NN aided multi-objective optimization approach.In this case,the NN aided analytical model can generate one motor design in 0.04 s while it takes more than 1 min for the used FEA model.

Design and optimization of weakly-coupled few-mode fiber with low nonlinearity

By investigating the influence of the difference of refractive index between core and cladding （nco - ncl）, normalized frequency （V） and core radius （α） on both the intramodal and intermodal nonlinear coefficients （NCs） respectively, we design a novel weakly-coupled four-mode fiber with low nonlinearity. In general, under the premise of ensuring the low NCs between two non-degenerate modes, this design can reduce the intermodal NCs （〈 0.5 W-l·km^-1） between two degenerate modes and optimizes the parameters of differential group delays （DGDs） and chromatic dispersion. The optimized few mode fiber （FMF） is eligible for transmission and mode de-multiplexing in the receiver.

Conceptual design and heat transfer performance of a flat-tile water-cooled divertor target

The divertor target components for the Chinese fusion engineering test reactor(CFETR)and the future experimental advanced superconducting tokamak(EAST)need to remove a heat flux of up to20 MW m-2.In view of such a high heat flux removal requirement,this study proposes a conceptual design for a flat-tile divertor target based on explosive welding and brazing technology.Rectangular water-cooled channels with a special thermal transfer structure(TTS)are designed in the heat sink to improve the flat-tile divertor target’s heat transfer performance(HTP).The parametric design and optimization methods are applied to study the influence of the TTS variation parameters,including height(H),width(W*),thickness(T),and spacing(L),on the HTP.The research results show that the flat-tile divertor target’s HTP is sensitive to the TTS parameter changes,and the sensitivity is T>L>W*>H.The HTP first increases and then decreases with the increase of T,L,and W*and gradually increases with the increase of H.The optimal design parameters are as follows:H=5.5 mm,W*=25.8 mm,T=2.2 mm,and L=9.7 mm.The HTP of the optimized flat-tile divertor target at different flow speeds and tungsten tile thicknesses is studied using the numerical simulation method.A flat-tile divertor mock-up is developed according to the optimized parameters.In addition,high heat flux(HHF)tests are performed on an electron beam facility to further investigate the mock-up HTP.The numerical simulation calculation results show that the optimized flat-tile divertor target has great potential for handling the steady-state heat load of 20 MW m-2under the tungsten tile thickness<5 mm and the flow speed7 m s^(-1).The heat transfer efficiency of the flat-tile divertor target with rectangular cooling channels improves by13%and30%compared to that of the flat-tile divertor target with circular cooling channels and the ITER-like monoblock,respectively.The HHF tests indicate that the flat-tile divertor mock-up can successfully withstand 1000 cycles of20 MW m-2of heat load without visible deformation,damage,and HTP degradation.The surface temperature of the flat-tile divertor mock-up at the 1000th cycle is only930℃.The flat-tile divertor target’s HTP is greatly improved by the parametric design and optimization method,and is better than the ITER-like monoblock and the flat-tile mock-up for the WEST divertor.This conceptual design is currently being applied to the engineering design of the CFETR and EAST flat-tile divertors.

Exploring the Roles of Single Atom in Hydrogen Peroxide Photosynthesis

This comprehensive review provides a deep exploration of the unique roles of single atom catalysts(SACs)in photocatalytic hydrogen peroxide(H_(2)O_(2))production.SACs offer multiple benefits over traditional catalysts such as improved efficiency,selectivity,and flexibility due to their distinct electronic structure and unique properties.The review discusses the critical elements in the design of SACs,including the choice of metal atom,host material,and coordination environment,and how these elements impact the catalytic activity.The role of single atoms in photocatalytic H_(2)O_(2)production is also analysed,focusing on enhancing light absorption and charge generation,improving the migration and separation of charge carriers,and lowering the energy barrier of adsorption and activation of reactants.Despite these advantages,several challenges,including H_(2)O_(2)decomposition,stability of SACs,unclear mechanism,and low selectivity,need to be overcome.Looking towards the future,the review suggests promising research directions such as direct utilization of H_(2)O_(2),high-throughput synthesis and screening,the creation of dual active sites,and employing density functional theory for investigating the mechanisms of SACs in H_(2)O_(2)photosynthesis.This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H_(2)O_(2)production.

Ice-Class Propeller Strength and Integrity Evaluation Using Unified Polar ClassURI3 Rules

A systematic method was developed for ice-class propeller modeling,performance estimation,strength and integrity evaluation and optimization.To estimate the impact of sea ice on the propeller structure,URI3 rules,established by the International Association of Classification Societies in 2007,were applied for ice loading calculations.An R-class propeller(a type of ice-class propeller)was utilized for subsequent investigations.The propeller modeling was simplified based on a conventional method,which expedited the model building process.The propeller performance was simulated using the computational fluid dynamics(CFD)method.The simulation results were validated by comparison with experimental data.Furthermore,the hydrodynamic pressure was transferred into a finite element analysis(FEA)module for strength assessment of ice-class propellers.According to URI3 rules,the ice loading was estimated based on different polar classes and working cases.Then,the FEA method was utilized to evaluate the propeller strength.The validation showed that the simulation results accorded with recent research results.Finally,an improved optimization method was developed to save the propeller constituent materials.The optimized propeller example had a minimum safety factor of 1.55,satisfying the safety factor requirement of≥1.5,and reduced the design volume to 88.2%of the original.

Aerodynamic design,analysis,and validation techniques for the Tianwen-1 entry module

The clear differences between the atmosphere of Mars and the Earth coupled with the lack of a domestic research basis were significant challenges for the aerodynamic prediction and verification of Tianwen-1.In addition,the Mars entry,descent,and landing(EDL)mission led to specific requirements for the accuracy of the aerodynamic deceleration performance,stability,aerothermal heating,and various complex aerodynamic coupling problems of the entry module.This study analyzes the key and difficult aerodynamic and aerothermodynamic problems related to the Mars EDL process.Then,the study process and results of the design and optimization of the entry module configuration are presented along with the calculations and experiments used to obtain the aerodynamic and aerothermodynamic characteristics in the Martian atmosphere.In addition,the simulation and verification of the low-frequency free oscillation characteristics under a large separation flow are described,and some special aerodynamic coupling problems such as the aeroelastic buffeting response of the trim tab are discussed.Finally,the atmospheric parameters and aerodynamic characteristics obtained from the flight data of the Tianwen-1 entry module are compared with the design data.The data obtained from the aerodynamic design,analysis,and verification of the Tianwen-1 entry module all meet the engineering requirements.In particular,the flight data results for the atmospheric parameters,trim angles of attack,and trim axial forces are within the envelopes of the prediction deviation zones.

Dynamic modulation performance of ferroelectric liquid crystal polarization rotators and Mueller matrix polarimeter optimization

A ferroelectric liquid crystal polarization rotator(FLCPR)has been widely used in polarization measurement due to its fast and stable modulation characteristics.The accurate characterization of the modulation performance of FLCPR directly affects the measurement accuracy of the instrument based on liquid crystal modulation.In this study,FLCPR is accurately characterized using a self-developed high-speed Stokes polarimeter.Strong linear and weak circular birefringence are observed during modulation processes,and all the optical parameters of FLCPR are dependent on driving voltage.A dual FLCPR-based Mueller matrix polarimeter is designed on the basis of the Stokes polarimeter.The designed polarimeter combines the advantages of the high modulation frequency of FLCPR and the ultrahigh temporal resolution of the fast polarization measurement system in the Stokes polarimeter.The optimal configuration of the designed polarizer is predicted in accordance with singular value decomposition.A simulated thickness measurement of a 24 nm standard SiO2 thin film is performed using the optimal configuration.Results show that the relative error in thickness measurement caused by using the unsatisfactory modulation characteristics of FLCPR reaches up to−4.34%.This finding demonstrates the importance of the accurate characterization of FLCPR in developing a Mueller matrix polarizer.

Surrogate role of machine learning in motor-drive optimization for more-electric aircraft applications

Motor drives form an essential part of the electric compressors,pumps,braking and actuation systems in the More-Electric Aircraft(MEA).In this paper,the application of Machine Learning(ML)in motor-drive design and optimization process is investigated.The general idea of using ML is to train surrogate models for the optimization.This training process is based on sample data collected from detailed simulation or experiment of motor drives.However,the Surrogate Role(SR)of ML may vary for different applications.This paper first introduces the principles of ML and then proposes two SRs(direct mapping approach and correction approach)of the ML in a motor-drive optimization process.Two different cases are given for the method comparison and validation of ML SRs.The first case is using the sample data from experiments to train the ML surrogate models.For the second case,the joint-simulation data is utilized for a multi-objective motor-drive optimization problem.It is found that both surrogate roles of ML can provide a good mapping model for the cases and in the second case,three feasible design schemes of ML are proposed and validated for the two SRs.Regarding the time consumption in optimizaiton,the proposed ML models can give one motor-drive design point up to 0.044 s while it takes more than 1.5 mins for the used simulation-based models.

A goal-oriented Design Method of CO_(2) Power Cycle(CPC)System

The CO_(2)power cycle(CPC)system is an efficient and environmentally friendly method for waste heat recovery(WHR).However,the traditional design and optimization process of a CPC system is very complex and timeconsuming.This paper proposes a novel goal-oriented design method based on machine-learning methods for quickly designing an optimized CPC system with given performance indicators.And taking the design of the CO_(2)transcritical power cycle(CTPC)system for internal combustion engines(ICEs)as an example.Firstly,the net output power and the total cost of the system prediction models are trained by simulated data.Then the multiobjective optimization of the system is carried out by using the genetic algorithm coupled with the prediction models,and the optimization results are used to train a classification model.Finally,the given target indicators are input into the classification model for goal-oriented designing and getting the optimal configuration.The results of the goal-oriented design validation show that the goal-oriented design method can design the CTPC system well.And,once the classification model is trained,the CTPC system’s future goal-oriented design process only needs to be calculated once,significantly reducing design time.In conclusion,the goal-oriented design method based on machine-learning proposed is a novel and promising method.This is a technology that combines computer science and energy science and can provide users with a quick and reliable CPC system design method.

Recent advances in the application of computational fluid dynamics in the development of rotary blood pumps

In recent years,ventricular assist devices(VADs,also known as blood pumps)have gradually entered clinical practice and provide effective treatment for heart failure patients.However,adverse events related to mechanical blood damage in patients receiving the VAD treatment,were often reported and have become a major concern during the development of VADs,limiting their clinical and economic benefits.Compared with bench and in-vivo testing,computational fluid dynamics(CFD)is flexible and inexpensive,offering the possibility to predict hemodynamics and mechanical blood damage in a purely numerical manner.Thus,CFD has become an important tool for the design,optimization and evaluation of blood pumps.The stringent requirements of blood pumps require high fidelity simulations.Thus,this article reviews the current state of the art in high-fidelity methodologies for simulating blood flow and blood damage for the development and evaluation of rotary blood pumps;design and optimization methods of rotatory blood pumps using CFD,as well as future challenges.

Biomechanical finite element analysis of typical tibiotalar arthrodesis

Tibiotalar arthrodesis(TTA)is a common surgical method for post-traumatic arthrosis and primary osteoarthrosis of ankle.Internal screw fixation exhibits such advantages of higher fusion rate and fewer complications that it has become the mainstream surgical procedure in clinics.However,there are still disputes over the choice of screw type,number and nailing method.In this study,a 3D model of tibiotalar joint was established based on CT data.Two representative types of screws were modeled according to their real objects.Preprocessing was done in Hypermesh 2017,and the finite element simulations of different surgical schemes and postoperative ankle joint movements were performed via Abaqus 2016.The stress distribution in tibiotalar joints and screws,interarticular displacement,and screw deformation were extracted for comparative analyses.The results show that:(1)the three-screw fixation scheme with smaller displacements and higher contact pressure is superior to the two-screw one;(2)the relative displacements of the tibia and talus of full-thread screw under all loads were reduced by approximately 50%compared with those of lag screw,showing better stability;(3)the 60
scheme is more favorable for joint fusion and more stable under vertical load,while the 75
has the best bending resistance;(4)the stress and strain distributions in screws indicate that the screw break is most likely to happen near its contact region with the bone inlet,the maximum stress reaches 212.2 MPa.This study is of great significance for the selection and optimization of the surgical plan.