Thermal-fluid Model Research Articles

Thermal fluid closures and pressure anisotropies in numerical simulations of plasma wakefield acceleration

We investigate the dynamics of plasma-based acceleration processes with collisionless particle dynamics and non-negligible thermal effects. We aim at assessing the applicability of fluid-like models, obtained by suitable closure assumptions applied to the relativistic kinetic equations, thus not suffering from statistical noise, even in the presence of a finite temperature. The work here presented focuses on the characterization of pressure anisotropies, which crucially depend on the adopted closure scheme, and hence are useful to discern the appropriate thermal fluid model. To this aim, simulation results of spatially resolved fluid models with different thermal closure assumptions are compared with the results of particle-in-cell simulations at changing temperature and amplitude of plasma oscillations.

Thermal Energy Storage With Horizontal Thermocline Tank for Sludge Drying Application

Solar thermal technologies can be an attractive option for the decarbonization of process heat applications; in particular, thermal energy storage is a high value proposition for continuous processes that may operate at a range of thermal conditions. A thermal-fluid model is developed to investigate the buoyant flow in a horizontal thermocline storage tank for a sludge-drying application. The process conditions and tank geometry considered are unique compared to the domestic water heating application typically considered in the literature and well suited for parabolic trough collectors. It was found that good separation of hot and cold fluids can be achieved with the long horizontal tank geometry depending on the inlet configuration. Uniform flow distribution along the length of the tank is required to establish a thermocline. Assuming desirable inlet conditions can be achieved, the tank outlet temperature predicted by the thermal-fluid model shows good agreement with the system-level performance model.

The effect of the laser beam intensity profile in laser-based directed energy deposition: A high-fidelity thermal-fluid modeling approach

Modeling the thermal and fluid flow fields in laser-based directed energy deposition (DED-LB) is crucial for understanding process behavior and ensuring part quality. However, existing models often fail to accurately predict these fields due to simplifying assumptions, particularly regarding powder particle-induced attenuation in laser power and energy density distribution, and the variable material properties and process parameters. The present work introduces a high-fidelity multi-phase thermal-fluid model driven by a combination of the discrete element method (DEM) and the finite volume method (FVM). Incorporating an enhanced attenuation model for laser energy enables a more precise approximation of powder particle-induced attenuation effects in the laser power and energy density distribution. The study focuses on the influence of laser beam intensity profiles during DED-LB of austenitic stainless steel (AISI 316 L), with model validation conducted through experimental measurements of deposited track dimensions for different beam shapes. The results of numerical simulations demonstrate the critical impact of powder-induced attenuation on the laser power and intensity profiles. Neglecting laser energy attenuation, a common assumption in numerical simulations of DED-LB, leads to overestimations of the absorbed energy of the laser beam, affecting thermal and fluid flow fields, and melt pool dimensions. The present study unravels the complex relationship between the attenuation coefficient (due to the powder stream) and powder stream characteristics, describing the variations of the attenuation coefficient with changes in the powder mass flow rate and powder stream incidence angle. The findings show the critical effects of laser beam shaping on melt pool behavior in DED-LB, with square beams inducing larger melt pool volumes and circular beams creating smaller but deeper melt pools. The proposed enhanced thermal-fluid modeling framework offers a robust approach for optimizing laser-based additive manufacturing across diverse materials and laser systems.

An efficient local moving thermal-fluid framework for accelerating heat and mass transfer simulation during welding and additive manufacturing processes

Numerical prediction of melt pool morphology and temperature distribution of thermomechanical processes (welding, additive manufacturing) plays an important role in understanding the relationships between process parameters and the quality of manufactured parts. The heat conduction models are limited in their predictability because the transport phenomena relevant to the melt pool dynamic are ignored. In contrast, the multiphysics model allows consideration of the heat transfer, free surface evolution, and transport phenomena in the melt pool, leading to more accurate predictions. However, the computational cost of multiphysics models makes them impractical for part-scale simulations. In this paper, a local moving thermal-fluid framework based on the finite element method is presented, which allows solving the thermal-fluid problem only in the small moving zone containing the melt pool and the heat transfer problem in the rest part. Therefore, this new proposed moving thermal-fluid (MTF) framework is predictive as well as the full thermal-fluid model, while it is much more efficient than a full thermal-fluid model since there are much fewer degrees of freedom (DOF) to solve. Finally, numerical validation tests in welding and additive manufacturing simulations highlight its computational efficiency and high-fidelity, and a relative error of less than 2.6% was observed in predicting melting pool dimensions compared to full thermal-fluid model. In the part-scale simulation of laser welding benchmark, the MTF model takes only 62 h in place of about three weeks required by a full thermal-fluid model.

Performance mapping of silicon-based solar cell for efficient power generation and thermal utilization: Effect of cell encapsulation, temperature coefficient, and reference efficiency

Characteristic Performance Maps (CPMAPs) are developed for silicon-based solar cells, based on a massive parametric study implemented by a validated thermal-fluid model. These CPMAPs reveal the variation of thermal-, energy-, and exergy-related performance indicators. The studied solar cell integrated with a generic heat sink satisfies the temperature demand within safe solar concentration range. The developed sets of CPMAPs investigate the effect of cell encapsulation, temperature coefficient, and reference efficiency. Findings indicate that reducing the thermal resistance of the intermediate layers between the silicon layer and the heat sink significantly elevates the maximum allowable concentration ratio. Besides, decreasing the thermal resistance of the intermediate layers enhanced the overall exergy efficiency. Furthermore, solar cells with lower temperature coefficients exhibit a minimal impact on expanding the safe range of solar concentration. However, the CPMAPs indicate that such cells are recommended for concentrator photovoltaic systems due to their ability to mitigate the inevitable decrease in electrical efficiency associated with high temperatures under high solar concentration. The use of high-reference efficiency cells slightly expands the safe range of solar concentration and leads to higher electrical exergy efficiency, albeit at the expense of reduced thermal exergy efficiency. Low-reference efficiency cells exhibit a higher potential for combined heat and power applications due to increasing the overall exergy efficiency. In contrary, high-reference efficiency cells are found to be more suitable for power generation applications. The proposed CPMAPs have significant implications, providing a novel roadmap for future research in the quantitative selection and design of photovoltaic systems.

Effect of cooling rate on microstructure and mechanical properties of AlCrFe2Ni2 medium entropy alloy fabricated by laser powder bed fusion

The mechanical properties and serviceability of the alloy fabricated by laser powder bed fusion (L-PBF) additive manufacturing (AM) strongly depend on the phase composition and microstructure, which are affected by the thermal condition of the process, such us cooling rate. In this study, AlCrFe2Ni2 medium entropy alloy (MEA) was fabricated by L-PBF under varying cooling rate via changing process parameters. The phase transformation, microstructure and mechanical properties were experimentally investigated using X-ray diffraction (XRD), scanning transmission electron microscopy (TEM), scanning electron microscope (SEM) and electron backscatter diffraction (EBSD). The cooling rate was numerically calculated using a well-tested multi-physic thermal fluid model. The results showed that cooling rate had a significant effect on phase composition, microstructure and mechanical properties. The as-built MEA with lower cooling rate showed a nano-size structure composed of BCC and ordered B2 phases and a higher yield strength of 2055 MPa. While for the higher cooling rate, the as-built MEA showed a homogeneous structure consisted of single ordered B2 phase and a lower yield strength of 1544 MPa. The threshold value of cooling rate for phase transformation was between 4.9 × 106 K/s and 6.0 × 106 K/s. Through the strengthening mechanism analysis, it was crucial to achieve the nano-size dual-phase microstructure by manipulating cooling for obtaininng desirable mechanical properties in L-PBF AMed AlCrFe2Ni2 MEA.

Topology Optimization Method of a Cavity Receiver and Built-In Net-Based Flow Channels for a Solar Parabolic Dish Collector.

The design of a thermal cavity receiver and the arrangement of the fluid flow layout within it are critical in the construction of solar parabolic dish collectors, involving the prediction of the thermal-fluid physical field of the receiver and optimization design. However, the thermal-fluid analysis coupled with a heat loss model of the receiver is a non-linear and computationally intensive solving process that incurs high computational costs in the optimization procedure. To address this, we implement a net-based thermal-fluid model that incorporates heat loss analysis to describe the receiver's flow and heat transfer processes, reducing computational costs. The physical field results of the net-based thermal-fluid model are compared with those of the numerical simulation, enabling us to verify the accuracy of the established thermal-fluid model. Additionally, based on the developed thermal-fluid model, a topology optimization method that employs a genetic algorithm (GA) is developed to design the cavity receiver and its built-in net-based flow channels. Using the established optimization method, single-objective and multi-objective optimization experiments are conducted under inhomogeneous heat flux conditions, with objectives including maximizing temperature uniformity and thermal efficiency, as well as minimizing the pressure drop. The results reveal varying topological characteristics for different optimization objectives. In comparison with the reference design (spiral channel) under the same conditions, the multi-objective optimization results exhibit superior comprehensive performance.

Comprehensive studies of SS316L/IN718 functionally gradient material fabricated with directed energy deposition: Multi-physics & multi-materials modelling and experimental validation

Metallic Functionally gradient materials (FGMs) are featured by gradually distributed metallic compositions generating unique mechanical and physical property gradients. As a major metal additive manufacturing process, Directed Energy Deposition (DED) has become an important process for manufacturing multi-materials parts. Fabricating metallic FGMs with the DED process has been studied experimentally in recent years. However, there is a lack of an effective modelling tool to predict the material composition gradients, FGM geometry, and the FGMs building process. The goal of this research is to fill this gap by establishing a novel multi-physics & multi-material thermal fluid model to fundamentally investigate the building process of FGMs with DED. In addition to the thermal distribution, phase change, and molten pool dynamics, the material distribution and geometry of the FGM part can be predicted with the model. As a demonstration, a DED fabrication process for Stainless Steel 316L/Inconel 718 FGM structure was simulated with this modelling tool. After that, the simulation results were validated with experimentally observed material composition and FGM geometry. The novelty of this study is the simulation of FGM part fabricated with DED process by fully considering multiple physics and multiple materials.

Additional Cover

The cover image is based on the Research Article Net-based thermal-fluid model and hybrid optimization of cooling channels by Jun Liu et al., https://doi.org/10.1002/nme.7075.

Numerical study of thermal fluid dynamics and solidification characteristics during continuous wave and pulsed wave laser welding

Pulsed wave (PW) mode laser welding is often preferred under conditions where specific heat input and tailorable cooling rate are required. Previous works on numerical modelling of laser welding mainly focus on continuous wave (CW) mode, while physical understanding of PW mode from numerical investigation is scarce. In this work, a 3D multi-physics thermal fluid model is developed considering both CW and PW modes laser welding. The main physical factors involving heat transfer, thermal fluid flow, Fresnel absorption, recoil pressure induced by metal evaporation, Marangoni effect driven by surface tension, free surface tracing, and laser multiple reflections inside the keyhole are included in this model. The model is tested and validated against the corresponding experimental results for laser welds of stainless steel 316 L. The simulated weld fusion cross sections and surface molten pool agree well with the experimentally observed results for both CW and PW modes. The results show that PW mode exhibits a higher depth of penetration and a smaller molten pool at the same heat input with CW mode. In CW mode laser welding, the shape of keyhole is unstable, while its depth keeps relatively stable. There are two main flow patterns in the molten pool of CW mode welding: an outward flow from keyhole outlet to the rear weld pool and a clockwise flow from the keyhole tip to the rear weld pool. While for PW mode, keyhole and molten pool show periodic behaviors with a period of the laser energy output used. The periodic fluid flow pattern is mainly affected by the gradually changed surface tension and suddenly changed recoil pressure. Furthermore, it is found that a finer microstructure with a smaller secondary dendrite arm spacing is obtained in PW mode due to a higher cooling rate from both the calculated and experimentally measured results.

Digitally manufactured air plasma-on-water reactor for nitrate production

The sustainable production of food to support the increasing world population is one of humanity’s most pressing challenges. Plasma activated water, produced using renewable energy, can help fulfill plants’ needs in sustainable agriculture approaches. The design, implementation, and characterization of a digitally manufactured air plasma-on-water reactor (POWR) for the synthesis of nitrate as green nitrogen fertilizer is presented. The interaction of air plasma-generated reactive oxygen and nitrogen species with water produces nitrate (NO3 −) and related species, which are the main nitrogen-containing nutrients for plants. The mild conditions of the operation of the POWR opens the possibility to use plastics, particularly through digital manufacturing strategies such as 3D-printing, for its fabrication. A pin-to-plate reactor configuration powered by high-voltage alternating power is chosen due to its simplicity and efficacy. A computational thermal-fluid model is used to evaluate the design and attain expected operational characteristics. The experimental characterization of the POWR encompassed design and operation parameters, namely electrode-water spacing, air flow rate, and voltage level. A machine learning approach is implemented to extract and quantify characteristic features of the plasma–water interaction, such plasma volume and plasma–water interface area. Experimental results revealed that the nitrate production rate varies linearly with dimensionless plasma volume. The design, fabrication, and characterization methods presented can be adapted to other POWRs and help enable on-demand nitrogen fertilizer production at low environmental and economic cost.

An efficient multidisciplinary design research for the integrated low speed permanent magnet motor system based on analytical and numerical hybrid analysis

This paper proposed an efficient high-accuracy multidisciplinary design process for the integrated system of low speed permanent magnet synchronous motor (PMSM). The method combined the analytical models and numerical models together to get an efficient way to design the integrated motor. In the proposed method, a magnetic equivalent circuit (MEC) model of the motor is established first based on one modular structure of the motor, and the finite element analysis (FEA) numerical model is used to correct the results of the analytical model next. Then the iron loss, copper loss, and switching loss from the results of the electromagnetic model are loaded to a proposed simplified lumped parameter fluid-thermal model. This fluid-thermal coupled analytical model cuts the fluid flow into several parts depends on the parameters of the cooling path, each parts act as a current controlled voltage source coupled with these parameters. And because this coupled model has controlled sources, the conventional node voltage method is not suitable anymore, so a more universal list parameter calculation method is proposed for this coupled model. Finally, the computational fluid dynamics (CFD) model is used to correct the results of the analytical model as well. The aim of the above analytical models is to quickly get the suitable multidisciplinary pre-design or design trends, and this pre-work or trends will reduce the design process time of the high-accuracy numerical models.

Slit flow and thermal analysis of micropolar fluids in a symmetric channel with dynamic and permeable

The mass and thermal flow of micropolar fluid in a channel having permeable and moving walls perpendicular to the flow-direction is considered here. A mathematical formulation for this physical problem is made using the Eringen's micropolar fluid-thermal model. Closed form solutions for temperature, microspin of aciculate particle and velocity are derived using the double perturbation method followed by the similarity transformation for the Newtonian/micropolar fluids. The perturbation parameters are the Reynolds number (that controls the wall-injection/suction) and the wall dilation parameter (that controls the rate of flow through the pores). Usually the no-spin conditions are imposed on studying the micropolar fluid-flows, but we consider no-spin condition in this attempt in order to highlight effect of micropolar spin boundary layer in the vicinity of the walls of the channel. The convergence of the perturbation method is checked, that sounds well. The results obtained for particular case (Newtonian fluid) are compared with alike literature and they are found satisfactory. The results for velocity, temperature, shear stress, thermal transfer rate and spin are presented for different values of physical parameters quantitatively and qualitatively.

Development of a multi-scale topology optimization method for thermal-fluid problems

In this presentation, we discuss how to optimize both microstructure and macrostructure in the topology optimization of 3D thermal fluid. First, the 3D thermal fluid model is approximated by a 2D thermal fluid field. Next, a proxy model of microstructural properties is constructed by learning the relationship between microstructure geometry, permeability, thermal conductivity, and heat transfer coefficient through off-line numerical analysis. The macrostructure optimization is then formulated as a microstructure selection problem from the surrogate model. Finally, a simple numerical example confirms the validity of the method. In this study, as a specific example, topology optimization is performed with two design variables on a two-dimensional model of a 3D forced air-cooled heat sink with prismatic fins. The properties of the 3D prismatic fins are analyzed individually in advance and learned offline using an RBF network so that they can be used in the two-dimensional topology optimization, which requires differentiation.

A multi-grid Cellular Automaton model for simulating dendrite growth and its application in additive manufacturing

The dendrite growth in casting and additive manufacturing is rather important and related to the formation of some defects. However, quantitatively simulating the growth of dendrites with arbitrary crystallographic orientations in 3-dimension(3D) is still very challenging. In the present work, we develop a multi-grid Cellular Automaton (CA) model for the dendrite growth. In this model, the interfacial area is further discretized into a child grid, on which the decentered octahedron growth algorithm is performed. The model is comprehensively and quantitatively verified by comparing with the prediction of analytical models and a published x-ray imaging observation result, proving that the model is quantitatively and morphologically accurate. After that, with the temperature gradient and cooling rate extracted from a finite-volume-method(FVM)-based thermal-fluid model, the model was applied in reproducing the dendrite growth process of nickel-based superalloy during a single-track electron beam melting process. The simulation results agree fairly well with the experimental observation, demonstrating the feasibility and effectiveness of using the model in additive manufacturing.

Multi-physics modeling of powder bed fusion process and thermal stress near porosity

In this research, a novel Comprehensive Modeling Framework (CMF) was established to investigate Laser Powder Bed Fusion (L-PBF) and thermal stress formed in the process. The CMF integrates two physical modeling components: thermal-fluid model and thermal–mechanical model. As first merit, almost all the physical fundamentals, like melting, solidification, evaporation, molten pool, and thermal stress are involved in CMF. CMF’s second merit is embodied in an innovative fluid–structure interface, which can help to precisely mesh powder bed and inner pores, and accurately interpolate temperature data between two models. As validation, a single-track Ti6Al4V L-PBF case was simulated with the CMF model.

Study on the evolution process of recast layer for fast EDM drilling based on observation experiment and a novel thermal-fluid coupling model

The existence of a recast layer of film cooling holes on turbine blades imposes a crucial problem that affects the quality of fast electrical discharge machining (EDM) drilling. This paper focuses on an evolution process from molten material generation to recast layer formation. Single pulse discharge observation experiments with a high speed camera and a self-built observation platform were carried out to observe the formation and movement of the molten material. A novel thermal-fluid coupling model is proposed to combine fast EDM drilling methods with special materials and geometric properties of film cooling hole machining. A heat transfer module, a turbulent flow computational fluid dynamics module, a phase change module and a level set method are combined in this model. The complete process of generation, flow and solidification of molten materials is investigated by simulation with a single pulse discharging. The simulation results agree well with the experimental observation results. A thermal-mechanical coupling analysis of a molten material evolution process is carried out based on the temperature, velocity and pressure fields from the thermal-fluid model. Simulation results show that the molten material is generated at 1 μs after the starting of a discharge, and solidifies within 20 μs after the ending of the discharge. Under the influence of a high-speed flushing fluid, molten materials will not splash into a gap channel along the radial directions. Most of the molten material enters the gap channel along the workpiece surface with a velocity of over 25 m s−1. The moving direction of the molten material is consistent with that of a flushing fluid. The thickness of a recast layer gradually increases from bottom to top in the fast EDM drilling.

High-fidelity modelling of thermal stress for additive manufacturing by linking thermal-fluid and mechanical models

The prediction of thermal stress and distortion is a prerequisite for high-quality additive manufacturing (AM). The widely applied thermo-mechanical model using the finite element method (FEM) leaves much to be improved due to their oversimplifications on material deposition, molten pool flow, etc. In this study, a high-fidelity modelling approach by linking the thermal-fluid (computational fluid dynamics, CFD) and mechanical models (named as CFD-FEM model) is developed to predict the thermal stress for AM taking into account the influences of thermal-fluid flow. Profiting from the precise temperature profiles and melt track geometry extracted from the thermal-fluid model as well as the remarkable flexibility of the quiet element method of FEM, this work aims at simulating the thermal stress distribution by involving physical changes in the AM process, e.g., melting and solidification of powder particles, molten pool evolution and inter-track inter-layer re-melting. Unlike the conventional thermo-mechanical analysis, in this approach, thermal stress calculation is purely based on a mechanical model where the thermal loads are applied by using a linear interpolation function to spatially and temporally map the temperature values from the thermal-fluid model's cell centres into the FEM element nodes. With the proposed approach, the thermal stress evolution in the AM process of single track, multiple tracks and multiple layers are simulated, where the rough surfaces and internal voids can be well incorporated. Moreover, a conventional thermo-mechanical simulation of two tracks with predefined track geometry is conducted for cross comparison. Finally, the simulated thermal stress distribution can rationally explain the crack distribution observed in the experiments.

An Energy Graph-Based Approach to Fault Diagnosis of a Transcritical CO2 Heat Pump

The objective of this paper is to describe an energy-based approach to visualize, identify, and monitor faults that may occur in a water-to-water transcritical CO 2 heat pump system. A representation using energy attributes allows the abstraction of all physical phenomena present during operation into a compact and easily interpretable form. The use of a linear graph representation, with heat pump components represented as nodes and energy interactions as links, is investigated. Node signature matrices are used to present the energy information in a compact mathematical form. The resulting node signature matrix is referred to as an attributed graph and is populated in such a way as to retain the structural information, i.e., where the attribute points to in the physical system. To generate the energy and exergy information for the compilation of the attributed graphs, a descriptive thermal–fluid model of the heat pump system is developed. The thermal–fluid model is based on the specifications of and validated to the actual behavioral characteristics of a physical transcritical CO 2 heat pump test facility. As a first step to graph-matching, cost matrices are generated to represent a characteristic residual between a normal system node signature matrix and a faulty system node signature matrix. The variation in the eigenvalues and eigenvectors of the characteristic cost matrices from normal conditions to a fault condition was used for fault characterization. Three faults, namely refrigerant leakage, compressor failure and gas cooler fouling, were considered. The paper only aims to introduce an approach, with the scope limited to illustration at one operating point and considers only three relatively large faults. The results of the proposed method show promise and warrant further work to evaluate its sensitivity and robustness for small faults.

Fluid-thermal modeling of hypersonic vehicles via a gas-kinetic BGK scheme-based integrated algorithm

In our previous paper (doi: 10.1016/j.ijheatmasstransfer.2019.119016), the gas-kinetic BGK scheme was used to simulate both hypersonic flow and structural heat transfer, between which loose coupling was adopted for solving two-dimensional fluid-thermal problems. To model the unitive and continuous fluid-thermal processes more actually, this paper presents a BGK scheme-based integrated algorithm and the research object is extended to three-dimensional hypersonic vehicles. To start with, an appropriate BGK model is constructed for the unified macroscopic governing equations, the effectiveness of which is verified by the Chapman-Enskog expansion analysis. Then following similar procedures in the original scheme, the gas distribution function at each cell interface is derived, from which the numerical fluxes can be evaluated. The dual-time stepping approach, together with an implicit JFNK–BGK method, is applied to efficiently obtain time-accurate solutions. With an effective parallelization strategy that is in line with the integrated algorithm, the computational efficiency is improved. As another aspect which distinguishes from the loosely-coupled methods, the fluid-structure interface conditions are also addressed. For validation, several test cases are investigated, including an individual hypersonic flow, an individual transient heat transfer, and two fluid-thermal problems. By comparison with other methods and analysis of the computed results, features of the developed method are demonstrated.