Multiphysics Constraints Research Articles

Prediction of thermal runaway for a lithium-ion battery through multiphysics-informed DeepONet with virtual data

A surrogate model that predicts thermal runaway (TR) of lithium-ion batteries (LIBs) fast and accurately is essential, yet complex phenomena of TR present significant challenges to achieving adequate performance in both aspects, particularly as traditional finite element models (FEMs) incur significant time and cost. This study proposes a multiphysics-informed deep operator network (MPI-DeepONet) with encoders to address these issues. This proposed neural network aims to predict TR under various thermal abuse conditions, offering a fast and accurate TR prediction surrogate model. In this study, MPI-DeepONet with encoders is trained with virtual data from a multiphysics FEM to overcome the scarcity of actual TR data. The architecture of DeepONet solves interpolation and extrapolation problems, allowing predictions across multiple thermal abuse conditions once trained. The neural network is further enhanced by the supervision of energy balance and chemical reaction equations, ensuring accurate and robust predictions despite limited data by effectively capturing the complex phenomena of TR. Quantitative analysis, compared against actual experiments and ablation studies, confirms the effectiveness of the proposed neural network. Notably, MPI-DeepONet achieves a mean RMSE of 13.2 °C for temperature predictions in the test set, significantly outperforming the 25.4 °C RMSE of purely data-driven DeepONet. This improvement highlights the importance of integrating multiphysics constraints into the neural network. The generality of the proposed neural network is further evidenced by accurate TR prediction in both LFP and NMC cells. The features deployed on the proposed neural network enable real-time quantification of internal temperature distribution and dimensionless concentration of the key components in LIBs, which are challenging to measure directly, achieving speeds at least 10,000 times faster than FEM. The proposed neural network provides comprehensive information for advanced battery management systems to ensure safety and reliability in LIBs, accelerating the digital twin of electric transportation systems through artificial intelligence transformation.

Li-ion battery charging strategy based on multi-state joint estimation model

This paper proposes a fast-charging strategy for lithium-ion batteries based on an intelligent optimization algorithm with multi-physics constraints. First, a thermoelectric coupling model and a battery degradation model have been established. Then an improved particle swarm optimization (PSO) is used to calculate the optimal charging strategy under different weighting factors. Finally, the Pareto boundary is drawn according to the optimization objective, and two charging strategies with different optimization objectives are developed. By comparing in different benchmark functions, the So-improved PSO proposed in this paper improves the convergence of the algorithm compared to the traditional PSO algorithm without increasing the computation time. The simulation results show that the multistage constant-current (MCC) charging strategy proposed in this paper can adjust the magnitude and order of charging current according to the change of weights, and reducing the loss of capacity and energy by only 0.017 % and 35.1 % while improving the charging speed by 24.9 % compared with the constant current-constant voltage (CCCV) charging strategy of 2C. Compared with the traditional CCCV charging strategy, the charging method proposed in this paper can have a broad application prospect.

Multi-Physics Constraints at Different Densities to Probe Nuclear Symmetry Energy in Hyperonic Neutron Stars

The appearance of strangeness in the form of hyperons within the inner core of neutron stars is expected to affect its detectable properties, such as its global structure or gravitational wave emission. This work explores the parameter space of hyperonic stars within the framework of the Relativistic Mean Field model allowed by the present uncertainties in the state-of-the-art nuclear and hypernuclear experimental data. We impose multi-physics constraints at different density regimes to restrict the parameter space: Chiral effective field theory, heavy-ion collision data, and multi-messenger astrophysical observations of neutron stars. We investigate possible correlations between empirical nuclear and hypernuclear parameters, particularly the symmetry energy and its slope, with observable properties of neutron stars. We do not find a correlation for the hyperon parameters and the astrophysical data. However, the inclusion of hyperons generates a tension between the astrophysical and heavy-ion data constraining considerably the available parameter space.

Design and Optimization Analysis of Coreless Stator Axial-Flux Permanent Magnet In-Wheel Motor for Unmanned Ground Vehicle

In this article, a coreless stator axial-flux permanent magnet (CSAFPM) indirect drive (ID) in-wheel motor is proposed and researched taking into consideration the multiphysics constraints, including electromagnetic performance and mechanical strength for unmanned ground vehicles (UGVs). At first, two 12-slot-14-pole CSAFPM motors with different rotor structures are designed to meet the vehicle rim space and driving system demand. In addition, the rotor parameters are optimized to obtain higher torque density based on the response surface method (RSM) and finite element model (FEM). Meanwhile, the electromagnetic performance of optimized motors with different rotors is compared, including back electromotive force (EMF), output torque capability, and efficiency characteristics. The results indicate that the Halbach-array PM rotor has higher torque and efficiency than the spoke-type PM rotor. On that basis, the thermal stress and deformation of the stator support are analyzed and optimized, considering material property and temperature distribution. In addition, the stress of PM rotor, annular gear, and gear reducer are analyzed and optimized to achieve higher torque density. Finally, a 35-kW prototype is manufactured and tested to verify the performance of the design.

Imposing multi-physics constraints at different densities on the neutron Star Equation of State

Neutron star matter spans a wide range of densities, from that of nuclei at the surface to exceeding several times normal nuclear matter density in the core. While terrestrial experiments, such as nuclear or heavy-ion collision experiments, provide clues about the behaviour of dense nuclear matter, one must resort to theoretical models of neutron star matter to extrapolate to higher density and finite neutron/proton asymmetry relevant for neutron stars. In this work, we explore the parameter space within the framework of the Relativistic Mean Field model allowed by present uncertainties compatible with state-of-the-art experimental data. We apply a cut-off filter scheme to constrain the parameter space using multi-physics constraints at different density regimes: chiral effective field theory, nuclear and heavy-ion collision data as well as multi-messenger astrophysical observations of neutron stars. Using the results of the study, we investigate possible correlations between nuclear and astrophysical observables.

Theoretical Study of Potential Manufacturing Insulation Defects in Medium–Voltage Traction Motors

Medium-voltage motors dedicated to the applications of traction operate in an environment with strong multi-physics constraints. Electrical insulation of these engines is a complex multi-layered impregnated system which requires a given number of steps during the manufacturing process. In the present study, we theoretically investigated the potential manufacturing insulation defects of traction motors in low frequency domain. The aim is to assess the theoretical ability of dielectric spectroscopy method for the detection of these defects and the extension of the method to others insulation systems. The theoretical study is based on numerical modelling and simulation achieved by using Comsol Multiphysics software. In our numerical modelling the properties of the main dielectric elementary materials are frequency–dependent. The identification of each potential defect is carried out by comparing its equivalent capacitance and dissipation loss spectra with the characteristics of insulation without defect. As the results, all artificial defects are identifiable with a specific relative deviation. The detection of all the defects analysed will need a measuring device with resolution of 0.4%. Keywords—AC electric motors, Capacitance, dielectric, dissipation factor, composite insulation, numerical modelling.

Model-Based Simulation Approach for Pre-Front End Engineering Design Studies for Subsea Field Architecture Development

Summary Presented is a model-based methodology identifying subsea field architectures that satisfy prespecified multiphysics constraints. The proposed methodology prioritizes the identified subsea system using a multiobjective optimization approach considering two objective functions, which are minimizing pressure drop reflecting the maximization of production flow rates and minimizing capital expenditures. The architecture solutions produce manifolds positioning and optimal pipeline routing/sizing. A convex combination approach creates the multiobjective optimization criterion enabling weighting among constraints such as hydraulic, topological, structural, and flow assurance, as well as technical issues and financial limitations. The optimization problem is computationally solved using a hybrid method with a global multistart algorithm that combines a scatter search process with a gradient-based local nonlinear problem solver. A case study is provided to test the proposed methodology including the effect of varying the weights among the constraints. This deep-dive analysis demonstrates the potential offered by the proposed methodology, illustrated by the ability to perform several investigations such as wells-grouping analysis and insulation effect on the overall optimization procedure, as well as to provide a tracking tool for flow-assurance factors, namely erosion and corrosion rates along the subsea layout. Hence, we present a demonstration of the capabilities of the proposed model-based subsea field layout optimization procedure.

Optimized Design and Multiphysics Analysis of a Ka-Band Stacked Antenna for CubeSat Applications

CubeSats and the space environment poses uniques, challenging and multiphysics constraints on the antenna design. In this work, we present the design of a patch stacked antenna working across the up- and downlink Ka-bands. The selection of the materials and geometry of the radiator was carried out by accounting for the trade-off between electromagnetic, thermal and mechanical requirements. The design of the antenna is performed with a particle swarm optimization algorithm developed to control the bandwidth and matching of the antenna over the Ka-band. Furthermore, a multiphysics thermal analysis is performed to verify the operational stability of the optimized array, mounted on a 1U satellite, in a case-study mission. The temperature patterns in the array are evaluated during the orbital period and the influence of operative temperature on the antenna responses and gain was considered. The thermal loads can affect the antenna matching, but, thanks to the optimized design, the proposed stacked antenna could operate from -100C to 100C, with analmost constant gain. Finally, folllowing a damage tolerant approach, the level of mechanical deformation which could be inducedon the communication system was studied. The analysis of stresses reveals that the stacked geometry could effectively be used in a space mission

ARTIFICIAL INTELLIGENCE DESIGN OF NUCLEAR SYSTEMS EMPOWERED BY ADVANCED MANUFACTURING*

Implicit in any engineering design is an underlying optimization problem, although the exact objective function to be optimized is rarely stated explicitly. Nuclear systems optimization is as old as the discipline of nuclear engineering. Advanced manufacturing in the nuclear industry has opened the door for the re-examination of optimization in a way in which it was not possible before, namely, determining the optimal geometry for a given objective function. A trivial example is the sphere as the shape that minimizes the volume (or mass) of bare fissile material in a critical configuration. However, the problem becomes less trivial under even the simplest of multiphysics considerations. In this work, we develop the solution methodology for finding the minimum volume geometric configurations under the multiphysics constraints of 1,500 pcm excess reactivity and maximum fuel temperature of 618°C under forced-flow cooling conditions. Constraining the solution geometry only to right cylinders, surprisingly yields two disjoint solution regions. Flat, wide (disk-like) cylinders and tall, narrow (rod-like) cylinders both satisfy the constraints and yield very similar minimal volumes. However, the ultimate pursuit of this work is truly arbitrary geometry.

Comprehensive Sensitivity Analysis and Multiphysics Optimization of the Rotor for a High Speed Permanent Magnet Machine

To improve the reliability of high speed permanent magnet machines (HSPMMs) under multiphysics constraints, including the electromagnetic properties, losses, rotor stress, rotor dynamics, and temperature, the rotor of an HSPMM is optimized to achieve low loss and temperature in this paper. To assess the impact of each rotor design parameter on multiphysics performance, a comprehensive sensitivity analysis of the rotor parameters on multiphysics performance is first implemented. On this basis, a multiphysics optimization process for HSPMM rotor is proposed to obtain the optimal design parameters. A comparison of the multiphysics performances of the initial and optimized design schemes shows that the optimized scheme can achieve much lower rotor loss and temperature. The optimization scheme is verified by comprehensive experimental tests on a 400 kW, 10 000 rpm HSPMM prototype.

Parameter Design for a High-Speed Permanent Magnet Machine Under Multiphysics Constraints

Regarding high-speed permanent magnet machines (HSPMMs), there is a lack of complete and detailed design processes for main parameters under multiphysics constraints, which makes it difficult to obtain high-reliability designs for designers of HSPMMs. This paper presents a detailed and complete design process for the main parameters of an HSPMM under multiphysics constraints. Firstly, the initial sizes are obtained through electromagnetic and mechanical design theory. Then, the influence of design parameters on rotor stress is analyzed in detail, including PM material, rotor temperature, sleeve thickness, PM thickness and rotor diameter. Furthermore, the rotor dynamics have also been studied in detail, including the effects of bearing stiffness, impeller mass, rotor diameter, core length, and gyroscopic effect on critical speed. Afterwards, the comprehensive research on the electromagnetic filed and the loss characteristics is performed. The cooling system is designed and the thermal field is also studied in Ansys-Cfx. Besides, the coupled temperature-stress analysis is established considering the interaction between temperature and mechanical characteristics. Finally, a full-size HSPMM prototype has been fabricated and tested to validate the detailed multiphysics design process.

Multiphysics analysis of high‐speed permanent magnet generators for waste heat application

In the direct drive waste heat power system, the turbine is directly connected to high-speed permanent magnet generators (HSPMGs), and the transmission efficiency, service life and system volume can be obviously improved by removing the gearbox and screw rod. However, in the design of high-speed electrical machines, a comprehensive multiphysics analysis must be conducted in order to meet various requirements of electromagnetic, mechanical and thermal specifications simultaneously. The design of one HSPMG by the multiphysics approach for the electromagnetic and loss characteristics, rotor stress, rotor dynamics and fluid-thermal parameters, which satisfies all specified multiphysics constraints, is presented. The theoretical results are confirmed by the experimental results on a prototype in terms of electromagnetic, mechanical and thermal characteristics, such as induced voltage, load current, rotor continuous operation and temperature distribution.

Multidisciplinary Design Strategies for Turbomolecular Pumps With Ultrahigh Vacuum Performance

Turbomolecular pumps with ultrahigh vacuum performances are a desired technology among modern vacuum systems, which requires the pump to synchronously possess the wide pumping speed and high vacuum. This paper describes a systematic design methodology for a magnetically levitated turbomolecular pump with consideration of multiphysics constraints, such as the mechanical strength, rotor dynamics, electromagnetic losses, and thermal characteristic. These variables will directly decide the acquisition of high vacuum performances. The design process for such high-performance pumps requires multidisciplinary and highly iterative due to the complex interaction of the many design variables involved. The structure of the bladed rotor is determined in terms of the material selection and mechanical verification. In this paper, an effective modeling method is presented to achieve accurate bending modes of the bladed rotor. An assessment on the loss level and the thermal limit is performed to ensure the temperature rise of the pump within the acceptable range. The measured results show that the pump can achieve the high vacuum performance with the pumping speed of 4370 l/s and the lowest working pressure of 10–8 magnitude. The proposed design process described in this paper provides the general guidelines for the multidisciplinary design of high-performance turbomolecular pumps.

Design and Optimization of Halbach-Array PM Rotor for High-Speed Axial-Flux Permanent Magnet Machine With Ironless Stator

In this article, a high-speed Halbach-array permanent magnet (PM) rotor for ironless stator axial-flux permanent magnet (AFPM) machine is proposed and researched with consideration of the multiphysics constraints, including the electromagnetic characteristics, mechanical strength, and rotor dynamics. Considering the severity of attractive force between twin rotors, the complex repulsive force among PM segments of Halbach-array and centrifugal force, the new hybrid sleeve, and PM fixation method are proposed to improve the rotor mechanical strength. Then, the rotor stress is analyzed by numerical analysis and three-dimensional (3-D) finite-element analysis (FEA). Furtherly, the sleeve thickness and interference fit are optimized by 3-D FEA. The rotor dynamics and bearing arrangement are analyzed to validate the effectiveness of the high-speed Halbach-array PM rotor. A 50-kW, 9000 r/min ironless stator AFPM machine prototype with Halbach-array PM rotor is manufactured and tested. The measured results show that the output power is up to 53.8 kW at 9000 r/min. The feasibility of high-speed Halbach-array PM rotor and accuracy of analysis method are validated by both simulated and measured results.

Effects of Design Parameters on the Multiphysics Performance of High-Speed Permanent Magnet Machines

In the design of high-speed permanent magnet machines (HSPMMs), comprehensive effects of design parameters on the various properties of electromagnetic loss, rotor stress, rotor critical speed, and temperature distribution must be analyzed to obtain the optimal design. The aim of this paper is to examine the effects of design parameters, such as the pole number, stator slots number, number of conductors per slot, permanent magnet (PM) thickness, PM pole arc coefficient, air gap length, rotor diameter, core length, and sleeve thickness, on multiphysics performance based on a high-power HSPMM. A reasonable design is determined according to the above-mentioned analysis that satisfies all specified multiphysics constraints. The theoretical results are confirmed by the experimental results on a prototype in terms of electromagnetic, mechanical, and thermal characteristics such as back electromotive force, no-load loss, full-load current, overspeed experiment, and temperature distribution.

Multiphysics Modeling and Optimization of a Compact Actuation System

This paper describes a methodology for the optimization of complex actuation systems, using analog simulations and an evolutionary algorithm. Our proposal consists of the development of an automated design framework that helps the designer to quickly complete a presizing step while ensuring that multidomain requirements are met within short development times typical of automotive industry. Multiphysics constraints can be handled, allowing the sizing of a complete automotive mechatronic system. The effectiveness of the methodology is demonstrated in the case of an exhaust gas recirculation valve. Electrical, mechanical, thermal, and magnetic requirements are met while a minimal volume is reached.

Multiphysics Design and Optimization of High-Speed Permanent-Magnet Electrical Machines for Air Blower Applications

In this paper, a high-speed permanent-magnet (PM) electrical machine is designed for centrifugal air blower application with consideration of the multiphysics constraints, including the mechanical strength, rotor dynamics, mechanical losses, and thermal field. In order to minimize the probabilities of mechanical failure and to realize the compact structure, the length and the outer diameter of rotor from mechanical point of view are designed and optimized. The optimization of sleeve thickness is performed by an accurate finite-element modeling which the interference is equivalent to the contact pressure. The optimization of rotor strength is based on the length–diameter ratio curve by using the finite-element method, which is followed behind the optimization of sleeve thickness. An assessment of machine cooling design from thermal point of view is performed by using the computational fluid dynamics modeling. Finally, in order to verify the accuracy of theoretical analysis, the prototype is fabricated with consideration of all critical values of the design parameters, and measured on the test bench.