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The thermal management of electrical insulations poses a challenge in electrical devices as electrical insulators are also thermal insulators. Diamond is the best solid electrical insulator and thermal conductor. This can lead to a paradigm change for electrical machine winding and lamination insulation design and thermal management. The paper introduces these techniques and discusses its effect for the design of electrical machines and its potential consequences for electromagnetic analysis, for example, in multi-physics modelling. The diamond winding insulation is patent-pending, but the diamond enriched lamination insulation is published for the benefit of the scientific community.

The windings of electrical machines are insulated to avoid contact between the coil and other conductive components, for example, the stator core. The principle of using mica tape and resin impregnation has not changed for a century and is well established to produce main insulation on a complex conductor shape and size. These insulations have poor heat-conducting properties. Similarly, the insulation of laminated steel sheets comprising the stator and rotor restrict heat flow. Diamond-based insulation provides a new path. Increased thermal conductivity means reduced temperature rise and the reduced thermal time constants in multi-physics simulations and system analysis.

The largest benefit of a diamond-based core insulation is in electrical machines in which the losses are conducted axially to the coolant. These are machines with radial ducts and effective cooling in the end regions. The main benefit will be in reducing the number of radial ducts that positively affect the size, production costs and the copper losses of the machine. The increased thermal conductivity of the diamond insulation system will reduce the thermal constants noticeably. These will affect system behavior and the corresponding simulation methods.

Diamond insulation can lead to a paradigm change for electrical machine winding and lamination insulation design and thermal management. It might also lead to new modeling requirements in system analysis.

The uniformity of electrodeposition is the key to successful application of pattern plating because the quality of electrodeposited copper layer has a huge impact on the performance of printed circuit boards (PCBs). The multi-physics coupling technology was used to accurately analyze and forecast the characteristics of electrochemical system. Further, an optimized plating bath was used to achieve a uniform electrodeposition.

A multi-physics coupling numerical simulation based on the finite element method was used to optimize electrodeposition conditions in pattern plating process. The influences of geometric and electrochemical factors on uniformity of current distribution and electrodeposited layer thickness were discussed by multi-physics coupling.

The model results showed that the distance between cathode and anode and the insulating shield had a great impact on uniformity of electrodeposition. By numerical simulation, it had been proved that using an auxiliary cathode was an effective and simple way to improve uniformity of electrodeposition due to redistributing of the current. This helped to achieve more uniform surface of the copper patterns by preventing the edge effect and the roughness of the copper layer was reduced to 1 per cent in the secondary current distribution model.

The research is still in progress with the development of high-performance computers.

A multi-physics coupling platform is an excellent tool for quickly and cheaply studying the process behaviors under a variety of operating conditions.

The numerical simulation method has laid the foundation for the design and improvement of the plating bath.

By multi-physics coupling technology, we built a bridge between theoretical and experimental study for control of uniformity of pattern plating in PCB manufacturing. This method can help optimize the design of plating bath and uniformity of pattern plating in PCB manufacturing.

The design of electromagnetic systems for a variety of applications such as induction heating, electrical machines, actuators and transformers requires the solution of a multi-physics problem often involving thermal, structural and mechanical coupling to the electromagnetic system. This results in a complex analysis system embedded within an optimization process. The appearance of high-performance computing systems over the past few years has made coupled simulations feasible for the design engineer. When coupled with surrogate modelling techniques, it is possible to significantly reduce the wall clock time for generating a complete design while including the impact of the multi-physics performance on the device.

An architecture is proposed for linking multiple singe physics analysis tools through the material models and a controller which schedules the execution of the various software tools. The combination of tools is implemented on a series of computational nodes operating in parallel and creating a “super node” cluster within a collection of interconnected processors.

The proposed architecture and job scheduling system can allow a parallel exploration of the design space for a device.

The originality of the work derives from the organization of the parallel computing system into a series of “super nodes” and the creation of a materials database suitable for multi-physics interactions.

In high-speed trains, the energy is supplied from a high voltage catenary to the vehicle via a pantograph catenary system (PCS). Carbon pantograph strips must maintain continuous contact with the wire to ensure safety and reliability. The contact is often confined to a particular spot, resulting in excessive wear due to mechanical and thermal damage, exacerbated by the presence of an electric arc and associated electrochemical corrosion. The effectiveness and reliability of the PCS impacts on the performance and safety of HSTs, especially under high-speed conditions. To alleviate some of these adverse effects, this paper aims to propose a configuration where a circular PCS replaces the currently used pantograph strips.

Two dynamic multi-physics models of a traditional PCS with a carbon strip and a novel PCS with a circular pantograph strip catenary system are established, and the electrical and mechanical characteristics of these two systems are compared. Moreover, a PCS experimental platform is designed to verify the validity and accuracy of the multi-physics model.

A novel circular pantograph system is proposed in this paper to alleviate some of the shortcomings of the traditional PCS. Comparing with a traditional PCS, the circular PCS exhibits superior performance in both electromagnetic and thermal aspects.

The paper offers a new technical solution to the PCS and develops a dedicated multi-physics model for analysis and performance prediction with the aim to improve the performance of the PCS. The new system offers numerous benefits, such as less friction heat, better heat dispersion and improved catenary-tracking performance.

The purpose of this paper is to present a reduced order computational strategy for a multi-physics simulation involving a fluid flow, electromagnetism and heat transfer in a hot-wall chemical vapour deposition reactor. The main goal is to produce a multi-parametric solution for fast exploration of the design space to perform numerical prototyping and process optimisation.

Different reduced order techniques are applied. In particular, proper generalized decomposition is used to solve the parameterised heat transfer equation in a five-dimensional space.

The solution of the state problem is provided in a compact separated-variable format allowing a fast evaluation of the process-specific quantities of interest that are involved in the optimisation algorithm. This is completely decoupled from the solution of the underlying state problem. Therefore, once the whole parameterised solution is known, the evaluation of the objective function is done on-the-fly.

Reduced order modelling is applied to solve a multi-parametric multi-physics problem and generate a fast estimator needed for preliminary process optimisation. Different order reduction techniques are combined to treat the flow, heat transfer and electromagnetism problems in the framework of separated-variable representations.

To present numerical approaches to the solution of physically coupled non‐linear problems, which frequently happen to be characterized by their multi‐domain character.

By adopting coupled solution strategies a considerable attention is devoted, in order to obtain a computationally efficient numerical algorithm, to the selection of appropriate space and time discretization, as well as to a proper discrete approximation method used.

Coupling of two methods, the finite element method and the boundary element method, respectively, has proved to be computationally exceedingly advantageous, particularly in case of moving domains.

As specific case studies computer simulation of an induction heating problem and a mushy‐state forming problem are considered. A thorough discussion on the coupling effects, characterizing the evolutions of respective physical quantities' fields, is given, and their impact on those evolutions is identified.

This paper presents efficient numerical strategies for the solution of a certain class of multi‐physics and multi‐domain problems.

A multi-physics process model is developed to analyze reactive melt infiltration (RMI) fabrication of ceramic-matrix composite (CMC) materials and components. The paper aims to discuss this issue.

Within this model, the following key physical phenomena governing this process are accounted for: capillary and gravity-driven unsaturated flow of the molten silicon into the SiC/SiC CMC preform; chemical reactions between the silicon melt and carbon (either the one produced by the polymer-binder pyrolysis or the one residing within the dried matrix slurry); thermal-energy transfer and source/sink phenomena accompanying reactive-flow infiltration; volumetric changes accompanying chemical reactions of the molten silicon with the SiC preform and cooling of the as-fabricated CMC component to room temperature; development of residual stresses within, and thermal distortions of, the as-fabricated CMC component; and grain-microstructure development within the SiC matrix during RMI.

The model is validated, at the material level, by comparing its predictions with the experimental and modeling results available in the open literature. The model is subsequently applied to simulate RMI fabrication of a prototypical gas-turbine engine hot-section component, i.e. a shroud. The latter portion of the work revealed the utility of the present computational approach to model fabrication of complex-geometry CMC components via the RMI process.

To the authors’ knowledge, the present work constitutes the first reported attempt to apply a multi-physics RMI process model to a gas-turbine CMC component.

This paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach for its better understanding.

A systematic review of the literature available in the area of continuum modelling practices adopted for the powder bed fusion (PBF) AM processes for the deposition of powder layer over the substrate along with quantification of residual stress and distortion. Discrete element method (DEM) and finite element method (FEM) approaches have been reviewed for the deposition of powder layer and thermo-mechanical modelling, respectively. Further, thermo-mechanical modelling adopted for the PBF AM process have been discussed in detail with its constituents. Finally, on the basis of prediction through thermo-mechanical models and experimental validation, distortion mitigation/minimisation techniques applied in PBF AM processes have been reviewed to provide a future direction in the field.

The findings of this paper are the future directions for the implementation and modification of the continuum modelling approaches applied to PBF AM processes. On the basis of the extensive review in the domain, gaps are recommended for future work for the betterment of modelling approach.

This paper is limited to review only the modelling approach adopted by the PBF AM processes, i.e. modelling techniques (DEM approach) used for the deposition of powder layer and macro-models at process scale for the prediction of residual stress and distortion in the component. Modelling of microstructure and grain growth has not been included in this paper.

This paper presents an extensive review of the FEM approach adopted for the prediction of residual stress and distortion in the PBF AM processes which sets the platform for the development of distortion mitigation techniques. An extensive review of distortion mitigation techniques has been presented in the last section of the paper, which has not been reviewed yet.

The purpose of this paper is to build a flow stress model and microstructure evolution models which can be used to fulfill the multi-physics prediction of hot forging process, in this way the process design can be virtually verified and optimized. This is especially crucial for micro-alloyed steel forging which microstructure determines the component properties, since the downstream quenching is usually not needed.

First, hot compression tests have been completed; second, experimental data are used to build the flow stress model and models for microstructure evolution; third, programming has been finished to integrate the proposed models into the commercial finite element method (FEM) code; fourth, case study is conducted to simulate multi-stage hot forging process of micro-alloyed steel F38MnV piston; and fifth, simulation results are validated by experiment.

First, simulation results in grain size and phase volume fraction are in well agreement with experimental ones; second, the austenite grain is dramatically refined by the dynamic recrystallization in pre-forging process and static recrystallization in the two intervals has no obvious change during the following final forging and cooling above the Ae3 temperature; third, during the cooling process below the Ae3 temperature, ferrite and pearlite transformation begin from the thin skirt to the thick skirt and piston bottom because of different cooling speeds at different areas.

First, flow stress model, dynamic recrystallization model, static recrystallization model, austenite grain growth model and phase transformation models are established for a micro-alloyed steel; second, the multi-physics FEM simulation of multi-stage hot forging of industrial piston has been conducted and verified by experiment, which show good agreement.

The friction stir welding (FSW) process comprises several highly coupled (and non‐linear) physical phenomena: large plastic deformation, material flow transportation, mechanical stirring of the tool, tool‐workpiece surface interaction, dynamic structural evolution, heat generation from friction and plastic deformation. This paper aims to present an advanced finite element (FE) model encapsulating this complex behaviour and various aspects associated with the FE model such as contact modelling, material model and meshing techniques are to be discussed in detail.

The numerical model is continuum solid mechanics‐based, fully thermo‐mechanically coupled and has successfully simulated the FSW process including plunging, dwelling and welding stages.

The development of several field variables are quantified by the model: temperature, stress, strain. Material movement is visualized by defining tracer particles at the locations of interest. The numerically computed material flow patterns are in very good agreement with the general findings from experiments.

The model is, to the best of the authors' knowledge, the most advanced simulation of FSW published in the literature.