Multi-Physics Coupled Acoustic-Mechanics Analysis and Synergetic Optimization for a Twin-Fluid Atomization Nozzle

Fine particulate matter produced during the rapid industrialization over the past decades can cause significant harm to human health.Twin-fluid atomization technology is an effective means of controlling fine particulate matter pollution.In this paper,the influences of the main parameters on the droplet size,effective atomization range and sound pressure level(SPL)of a twin-fluid nozzle(TFN)are investigated,and in order to improve the atomization performance,a multi-objective synergetic optimization algorithm is presented.A multi-physics coupled acousticmechanics model based on the discrete phase model(DPM),large eddy simulation(LES)model,and Ffowcs Williams-Hawkings(FW-H)model is established,and the numerical simulation results of the multi-physics coupled acoustic-mechanics method are verified via experimental comparison.Based on the analysis of the multi-physics coupled acoustic-mechanics numerical simulation results,the effects of the water flow on the characteristics of the atomization flow distribution were obtained.A multi-physics coupled acoustic-mechanics numerical simulation result was employed to establish an orthogonal test database,and a multi-objective synergetic optimization algorithm was adopted to optimize the key parameters of the TFN.The optimal parameters are as follows:A gas flow of 0.94 m^(3)/h,water flow of 0.0237 m^(3)/h,orifice diameter of the self-excited vibrating cavity(SVC)of 1.19 mm,SVC orifice depth of 0.53 mm,distance between SVC and the outlet of nozzle of 5.11 mm,and a nozzle outlet diameter of 3.15 mm.The droplet particle size in the atomization flow field was significantly reduced,the spray distance improved by 71.56%,and the SPL data at each corresponding measurement point decreased by an average of 38.96%.The conclusions of this study offer a references for future TFN research.

Verification of a self-developed CFD-based multi-physics coupled code MPC-LBE for LBE-cooled reactor

To perform an integral simulation of a pool-type reactor using CFD code,a multi-physics coupled code MPC-LBE for an LBE-cooled reactor was proposed by integrating a point kinetics model and a fuel pin heat transfer model into self-developed CFD code.For code verification,a code-to-code comparison was employed to validate the CFD code.Furthermore,a typical BT transient benchmark on the LBE-cooled XADS reactor was selected for verification in terms of the integral or system performance.Based on the verification results,it was demonstrated that the MPC-LBE coupled code can perform thermal-hydraulics or safety analyses for analysis for processes involved in LBE-cooled pool-type reactors.

Development and application of a multi-physics and multi-scale coupling program for lead-cooled fast reactor

In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and the NDK code is a neutron diffusion code.The coupling program framework adopts the"master-slave"mode,in which Fluent is the master program while NDK and KMC-sub are coupled internally and compiled into the dynamic link library(DLL)as slave codes.The domain decomposition method was adopted,in which the reactor core was simulated by NDK and KMC-sub,while the rest of the primary loop was simulated using Fluent.A simulation of the reactor shutdown process of M2LFR-1000 was carried out using the coupling program,and the code-to-code verification was performed with ATHLET,demonstrating a good agreement,with absolute deviation was smaller than 0.2%.The results show an obvious thermal stratification phenomenon during the shutdown process,which occurs 10 s after shutdown,and the change in thermal stratification phenomena is also captured by the coupling program.At the same time,the change in the neutron flux density distribution of the reactor was also obtained.

Multi-physics analysis of permanent magnet tubular linear motors under severe volumetric and thermal constraints

Permanent magnet tubular linear motors(TLMs) arranged in multiple rows and multiple columns used for a radiotherapy machine were studied. Due to severe volumetric and thermal constraints, the TLMs were at high risk of overheating. To predict the performance of the TLMs accurately, a multi-physics analysis approach was proposed. Specifically, it considered the coupling effects amongst the electromagnetic and the thermal models of the TLMs, as well as the fluid model of the surrounding air. To reduce computation cost, both the electromagnetic and the thermal models were based on lumped-parameter methods. Only a minimum set of numerical computation(computational fluid dynamics, CFD) was performed to model the complex fluid behavior. With the proposed approach, both steady state and transient state temperature distributions, thermal rating and permissible load can be predicted. The validity of this approach is verified through the experiment.

Transient multi-physics behavior of an insert high temperature superconducting no-insulation coil in hybrid superconducting magnets with inductive coupling

A transient multi-physics model incorporated with an electromagneto-thermomechanical coupling is developed to capture the multi-field behavior of a single-pancake(SP)insert no-insulation(NI)coil in a hybrid magnet during the charging and discharging processes.The coupled problem is resolved by means of the finite element method(FEM)for the magneto-thermo-elastic behaviors and the Runge-Kutta method for the transient responses of the electrical circuits of the hybrid superconducting magnet system.The results reveal that the transient multi-physics responses of the insert NI coil primarily depend on the charging/discharging procedure of the hybrid magnet.Moreover,a reverse azimuthal current and a compressive hoop stress are induced in the insert NI coil during the charging process,while a forward azimuthal current and a tensile hoop stress are observed during the discharging process.The induced voltages in the insert NI coil can drive the currents flowing across the radial turns where the contact resistance exists.Therefore,it brings forth significant Joule heat,causing a temperature rise and a uniform distribution of this heat in the coil turns.Accordingly,a thermally/mechanically unstable or quenching event may be encountered when a high operating current is flowing in the insert NI coil.It is numerically predicted that a quick charging will induce a compressive hoop stress which may bring a risk of buckling instability in the coil,while a discharging will not.The simulations provide an insight of hybrid superconducting magnets under transient start-up or shutdown phases which are inevitably encountered in practical applications.

A robust multi-objective and multi-physics optimization of multi-physics behavior of microstructure

A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization （IMOCO） and its extension improved multi-objective robust collaborative （IMORCO）. In this work, the proposed IMORCO approach combined the IMOCO method, the worst possible point （WPP） constraint cuts and the Genetic algorithm NSGA-II type as an optimizer in order to solve the robust optimization problem of multi-physics of microstructures with uncertainties. The optimization problem is hierarchically decomposed into two levels： a microstructure level, and a disciplines levels, For validation purposes, two examples were selected： a numerical example, and an engineering example of capacitive micro machined ultrasonic transducers （CMUT） type. The obtained results are compared with those obtained from robust non-distributed and distributed optimization approach, non-distributed multi-objective robust optimization （NDMORO） and multi-objective collaborative robust optimization （McRO）, respectively. Results obtained from the application of the IMOCO approach to an optimization problem of a CMUT cell have reduced the CPU time by 44% ensuring a Pareto front close to the reference non-distributed multi-objective optimization （NDMO） approach （mahalanobis distance, D2M =0.9503 and overall spread, So=0.2309）. In addition, the consideration of robustness in IMORCO approach applied to a CMUT cell of optimization problem under interval uncertainty has reduced the CPU time by 23% keeping a robust Pareto front overlaps with that obtained by the robust NDMORO approach （D2M =10.3869 and So=0.0537）.

Minimal Realization of Linear Graph Models for Multi-physics Systems

An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.

Mechatronic Modeling and Domain Transformation of Multi-physics Systems

The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.

Multi-physics multi-scale simulation of unique equiaxed-to-columnar-to-equiaxed transition during the whole solidification process of Al-Li alloy laser welding

In this study,a novel multi-physics multi-scale model with the dilute multicomponent phase-field method in three-dimensional(3D)space was developed to investigate the complex microstructure evolu-tion in the molten pool during laser welding of Al-Li alloy.To accurately compute mass data within both two and three-dimensional computational domains,three efficient computing methods,including central processing unit parallel computing,adaptive mesh refinement,and moving-frame algorithm,were uti-lized.Emphasis was placed on the distinctive equiaxed-to-columnar-to-equiaxed transition phenomenon that occurs during the entire solidification process of Al-Li alloy laser welding.Simulation results indi-cated that the growth distance of columnar grains that epitaxially grew from the base metal(BM)de-creased as the nucleation rate increased.As the nucleation rate increased,the morphology of the newly formed grains near the fusion boundary(FB)changed from columnar to equiaxed,and newly formed equiaxed grains changed from having high-order dendrites to no obvious dendrite structure.When the nucleation rate was sufficiently high,non-dendritic equiaxed grains could directly form near the FB,and there was nearly no epitaxial growth from the BM.Additionally,simulation results illustrated the com-petition among multiple grains with varying orientations that grow in 3D space near the FB.Finally,how equiaxed grain bands develop was elucidated.The equiaxed band not only hindered the growth of early columnar grains but also some of its grains could grow epitaxially to form new columnar grains.These predicted results were in good agreement with experimental measurements and observations.

Understanding and improving Yangtze River Basin summer precipitation prediction using an optimal multi-Physics ensemble

This study employs the regional Climate-Weather Research and Forecasting model(CWRF)to first investigate the primary physical mechanisms causing biases in simulating summer precipitation over the Yangtze River Basin(YRB),and then enhance its predictive ability through an optimal multi-physics ensemble approach.The CWRF 30-km simulations in China are compared among 28 combinations of varying physics parameterizations during 1980−2015.Long-term average summer biases in YRB precipitation are remotely correlated with those of large-scale circulations.These teleconnections of biases are highly consistent with the observed correlation patterns between interannual variations of precipitation and circulations,despite minor shifts in their primary action centers.Increased YRB precipitation aligns with a southward shifted East Asian westerly jet,an intensified low-level southerly flow south of YRB,and a south-eastward shifted South Asian high,alongside higher moisture availability over YRB.Conversely,decreased YRB precipitation corresponds to an opposite circulation pattern.The CWRF control configuration using the ensemble cumulus parameterization(ECP),compared to other cumulus schemes,best captures the observed YRB precipitation characteristics and associated circulation patterns.Coupling ECP with the Morrison or Morrison-aerosol microphysics and the CCCMA or CAML radiation schemes enhances the overall CWRF skills.Compared to the control CWRF,the ensemble average of these skill-enhanced physics configurations more accurately reproduces YRB summer precipitation’s spatial distributions,interannual anomalies,and associated circulation patterns.The Bayesian Joint Probability calibration to these configurations improves the ensemble’s spatial distributions but compromises its interannual anomalies and teleconnection patterns.Our findings highlight substantial potential for refining the representation of climate system physics to improve YRB precipitation prediction.This is notably achieved by realistically coupling cumulus,microphysics,and radiation processes to accurately capture circulation teleconnections.Further enhancements can be achieved by optimizing the multi-physics ensemble among skill-enhanced configurations.

Heavy Rainfall Ensemble Prediction:Initial Condition Perturbation vs Multi-Physics Perturbation

Mesoscale ensemble is an encouraging technology for improving the accuracy of heavy rainfall predictions. Occurrences of heavy rainfall are closely related to convective instability and topography. In mid-latitudes, perturbed initial fields for medium-range weather forecasts are often configured to focus on the baroclinic instability rather than the convective instability. Thus, alternative approaches to generate initial perturba- tions need to be developed to accommodate the uncertainty of the convective instability. In this paper, an initial condition perturbation approach to mesoscale heavy rainfall ensemble prediction, named as Different Physics Mode Method （DPMM）, is presented in detail. Based on the PSU/NCAR mesoscale model MM5, an ensemble prediction experiment on a typical heavy rainfall event in South China is carried out by using the DPMM, and the structure of the initial condition perturbation is analyzed. Further, the DPMM ensem- ble prediction is compared with a multi-physics ensemble prediction, and the results show that the initial perturbation fields from the DPMM have a reasonable mesoscale circulation structure and could reflect the prediction uncertainty in the sensitive regions of convective instability. An evaluation of the DPMM ini- tial condition perturbation indicates that the DPMM method produces better ensemble members than the multi-physics perturbation method, and can significantly improve the precipitation forecast than the control non-ensemble run.

Electrochemical machining gap prediction with multi-physics coupling model based on two-phase turbulence flow

Considering the influence of hydrogen gas generated during electrochemical machining on the conductivity of electrolyte, a two-phase turbulent flow model is presented to describe the gas bubbles distribution.The k-e turbulent model is used to describe the electrolyte flow field.The Euler–Euler model based on viscous drag and pressure force is used to calculate the twodimensional distribution of gas volume fraction.A multi-physics coupling model of electric field,two-phase flow field and temperature field is established and solved by weak coupling iteration method.The numerical simulation results of gas volume fraction, temperature and conductivity in equilibrium state are discussed.The distributions of machining gap at different time are analyzed.The predicted results of the machining gap are consistent with the experimental results, and the maximum deviation between them is less than 50 lm.

Multi-physics coupling field finite element analysis on giant magnetostrictive materials smart component

This study presents a new method to solve the difficult problem of precise machining a non-cylinder pinhole of a piston using embedded giant magnetostrictive material (GMM) in the component. We propose the finite element model of GMM smart component in electric, magnetic, and mechanical fields by step computation to optimize the design of GMM smart com-ponent. The proposed model is implemented by using COMSOL multi-physics V3.2a. The effects of the smart component on the deformation and the system resonance frequencies are studied. The results calculated by the model are in excellent agreement (relative errors are below 10%) with the experimental values.

Multi-Physics CFD Simulations in Engineering

Nowadays Computational Fluid Dynamics （CFD） software is adopted as a design and analysis tool in a great number of engineering fields. We can say that single-physics CFD has been suffciently matured in the practical point of view. The main target of existing CFD software is single-phase flows such as water and air. However, many multi-physics problems exist in engineering. Most of them consist of flow and other physics, and the interactions between different physics are very important. Obviously, multi-physics phenomena are critical in devel- oping machines and processes. A multi-physics phenomenon seems to be very complex, and it is so difficult to be predicted by adding other physics to flow phenomenon. Therefore, multi-physics CFD techniques are still under research and development. This would be caused from the facts that processing speed of current computers is not fast enough for conducting a multi-physics simulation, and furthermore physical models except for flow physics have not been suitably established. Therefore, in near future, we have to develop various physical models and ef- ficient CFD techniques, in order to success multi-physics simulations in engineering. In the present paper, I will describe the present states of multi-physics CFD simulations, and then show some numerical results such as ice accretion and electro-chemical machining process of a three-dimensional compressor blade which were obtained in my laboratory. Multi-physics CFD simulations would be a key technology in near future.

Multi-physics analysis of the RFQ for Injector Scheme Ⅱ of C-ADS driver linac

A 162.5 MHz, 2.1 MeV radio frequency quadruples （RFQ） structure is being designed for the Injector Scheme Ⅱ of the China Accelerator Driven Sub-critical System （C-ADS） linac. The RFQ will operate in continuous wave （CW） mode as required. For the CW normal conducting machine, the heat management will be one of the most important issues, since the temperature fluctuation may cause cavity deformation and lead to the resonant frequency shift. Therefore a detailed multi-physics analysis is necessary to ensure that the cavity can stably work at the required power level. The multi-physics analysis process includes RF electromagnetic analysis, thermal analysis, mechanical analysis, and this process will be iterated for several cycles until a satisfactory solution can be found. As one of the widely accepted measures, the cooling water system is used for frequency fine tunning, so the tunning capability of the cooling water system is also studied under different conditions. The results indicate that with the cooling water system, both the temperature rise and the frequency shift can be controlled at an acceptable level.

An Objective Approach to Generating Multi-Physics Ensemble Precipitation Forecasts Based on the WRF Model

Selecting proper parameterization scheme combinations for a particular application is of great interest to the Weather Research and Forecasting(WRF)model users.This study aims to develop an objective method for identifying a set of scheme combinations to form a multi-physics ensemble suitable for short-range precipitation forecasting in the Greater Beijing area.The ensemble is created by using statistical techniques and some heuristics.An initial sample of 90 scheme combinations was first generated by using Latin hypercube sampling(LHS).Then,after several rounds of screening,a final ensemble of 40 combinations were chosen.The ensemble forecasts generated for both the training and verification cases using these combinations were evaluated based on several verification metrics,including threat score(TS),Brier score(BS),relative operating characteristics(ROC),and ranked probability score(RPS).The results show that TS of the final ensemble improved by 9%-33%over that of the initial ensemble.The reliability was improved for rain≤10 mm day^-1,but decreased slightly for rain>10 mm day^-1 due to insufficient samples.The resolution remained about the same.The final ensemble forecasts were better than that generated from randomly sampled scheme combinations.These results suggest that the proposed approach is an effective way to select a multi-physics ensemble for generating accurate and reliable forecasts.

Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation

The use of solid oxide fuel cells(SOFCs)is a promising approach towards achieving sustainable electricity pro-duction from fuel.The utilisation of the hydrocarbons and biomass in SOFCs is particularly attractive owing to their wide distribution,high energy density,and low price.The long-term operation of SOFCs using such fuels remains difficult owing to a lack of an effective diagnosis and optimisation system,which requires not only a precise analysis but also a fast response.In this study,we developed a hybrid model for an on-line analysis of SOFCs at the cell level.The model combines a multi-physics simulation(MPS)and deep learning,overcoming the complexity of MPS for a model-based control system,and reducing the cost of building a database(compared with the experiments)for the training of a deep neural network.The maximum temperature gradient and heat generation are two target parameters for an efficient operation of SOFCs.The results show that a precise predic-tion can be achieved from a trained AI algorithm,in which the relative error between the MPS and AI models is less than 1%.Moreover,an online optimisation is realised using a genetic algorithm,achieving the maximum power density within the limitations of the temperature gradient and operating conditions.This method can also be applied to the prediction and optimisation of other non-liner,dynamic systems.

Integration of multi-physics and machine learning-based surrogate modelling approaches for multi-objective optimization of deformed GDL of PEM fuel cells

The development of artificial intelligence(AI)greatly boosts scientific and engineering innovation.As one of the promising candidates for transiting the carbon intensive economy to zero emission future,proton exchange membrane(PEM)fuel cells has aroused extensive attentions.The gas diffusion layer(GDL)strongly affects the water and heat management during PEM fuel cells operation,therefore multi-variable optimization,including thickness,porosity,conductivity,channel/rib widths and compression ratio,is essential for the improved cell performance.However,traditional experiment-based optimization is time consuming and economically unaffordable.To break down the obstacles to rapidly optimize GDLs,physics-based simulation and machine-learning-based surrogate modelling are integrated to build a sophisticated M 5 model,in which multi-physics and multi-phase flow simulation,machine-learning-based surrogate modelling,multi-variable and multi-objects optimization are included.Two machine learning methodologies,namely response surface methodol-ogy(RSM)and artificial neural network(ANN)are compared.The M 5 model is proved to be effective and efficient for GDL optimization.After optimization,the current density and standard deviation of oxygen dis-tribution at 0.4 V are improved by 20.8%and 74.6%,respectively.Pareto front is obtained to trade off the cell performance and homogeneity of oxygen distribution,e.g.,20.5%higher current density is achieved when sacrificing the standard deviation of oxygen distribution by 26.0%.

Multi-physics analysis of a 325 MHz bi-periodic on-axis coupled accelerating structure

Purpose A 325-MHz bi-periodic on-axis coupled accelerating structure prototype which consists of two bi-periodic accelerating modules is under fabrication in the Institute of High Energy Physics,Beijing,dedicated to a 10-MeV/100 kW industrial linear electron accelerator.According to the beam dynamics study,the average power dissipated in the prototype cavity is about 19.1 kW.Effective cooling scheme is one of the most important issues in the high-power operation.Methods This paper mainly deals with the RF,thermal and structural coupled analyses of the accelerating structure prototype with the help of the ANSYS code.The cooling scheme is optimized to minimize the temperature rise,displacement and von Mises stresses.Results The temperature and stress distributions in the steady state are presented.The maximum von Mises stress is much lower than the yield strength limit of the corresponding material.The frequency shift caused by the thermal expansion is calculated as well,which is within the scope of the tuning range.Conclusion The coupled analyses based on the ANSYS software package are presented to design and optimize the cooling scheme of the accelerating structure.The von Mises stresses are much lower than the yield strength limit of the material.The calculation results indicate that our cooling scheme can deal with the dissipated RF power efficiently.

An internal ballistic model of electromagnetic railgun based on PFN coupled with multi-physical field and experimental validation

To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.