Search Results (102)

We propose a coupled gas–particle two-phase model for particle transport in a compressible carrier gas with interphase momentum and energy exchange, and we incorporate a diffusion-based mechanism to represent gas–particle reactions. The governing equations are discretized in an Arbitrary Lagrangian–Eulerian (ALE) finite-volume framework using an HLLC-type two-dimensional Riemann solver (HLLC-2D). The solver employs a nodal-conservation construction that enforces consistency between numerical fluxes and nodal contact velocities, which helps reduce spurious oscillations near discontinuities on moving meshes. In addition, a particle-search-based Courant–Friedrichs–Lewy(CFL)-like time-step restriction is introduced to enhance robustness in coupled simulations. Numerical tests are presented to assess the method and to illustrate particle-induced modifications of wave dynamics, as well as reaction-driven variations in velocity and temperature fields. Full article

Thermo-hydrodynamic (THD) lubrication is a key mechanism in injection pumps, where frictional heating and heat transfer strongly influence lubrication performance. Accurate numerical modeling remains challenging due to the nonlinear coupling of temperature- and pressure-dependent fluid properties and the high computational cost of iterative solvers. The rising relevance of bio-hybrid fuels, however, demands the investigation of a great number of fuel mixtures and conditions, which is currently infeasible with traditional solvers. Physics-informed neural networks (PINNs) have recently been applied to lubrication problems; existing approaches are typically restricted to stationary cases or rely on data to improve training. This work presents a novel, purely physics-based PINN framework for solving coupled, transient THD lubrication problems in injection pumps. By embedding the Reynolds equation, energy conservation laws, and temperature- and pressure-dependent fluid models directly into the loss function, the proposed approach eliminates the need for any simulation or experimental data. The PINN is trained solely on physical laws and validated against an iterative solver for 16 transient test cases across two fuels and eight operating scenarios. The good agreement of PINN and iterative solver demonstrates the strong potential of PINNs as efficient, scalable surrogate models for transient THD lubrication and iterative design applications. Full article

This study investigates the thermal characteristics of two hybrid nanofluids, single-walled carbon nanotubes with titanium dioxide ($SWCNT-Ti{O}_2$) and multi-walled carbon nanotubes with copper ($MWCNT-Cu$), as they flow over an inclined, porous, and longitudinally stretched cylindrical surface with kerosene as the base fluid. The model takes into consideration all of the consequences of magnetohydrodynamic (MHD) effects, thermal radiation, and Arrhenius-like energy of activation. The outcomes of this investigation hold practical significance for energy storage systems, nuclear reactor heat exchangers, electronic cooling devices, biomedical hyperthermia treatments, oil and gas transport processes, and aerospace thermal protection technologies. The proposed hybrid ANN–numerical framework provides an effective strategy for optimizing the thermal performance of hybrid nanofluids in advanced thermal management and energy systems. A set of coupled ordinary differential equations is created by applying similarity transformations to the governing nonlinear partial differential equations that reflect conservation of mass, momentum, energy, and species concentration. The boundary value problem solver bvp4c, which is based in MATLAB (R2020b), is used to solve these equations numerically. The findings demonstrate that, in comparison to the $MWCNT-Cu/kerosene$ nanofluid, the $SWCNT-Ti{O}_2$/kerosene hybrid nanofluid improves the heat transfer rate (Nusselt number) by up to $23.6\%$. When a magnetic field is applied, velocity magnitudes are reduced by almost $15\%$, and the temperature field is enhanced by around $12\%$ when thermal radiation is applied. The impact of important dimensionless variables, such as the cylindrical surface’s inclination angle, the medium’s porosity, the magnetic field’s strength, the thermal radiation parameter, the curvature ratio, the activation energy, and the volume fraction of nanoparticles, is investigated in detail using a parametric study. According to the comparison findings, at the same flow and thermal boundary conditions, the $SWCNT-Ti{O}_2$/kerosene hybrid nanofluid performs better thermally than its $MWCNT-Cu$/kerosene counterpart. These results offer important new information for maximizing heat transfer in engineering systems with hybrid nanofluids and inclined porous geometries under intricate physical conditions. With its high degree of agreement with numerical results, the ANN model provides a computationally effective stand-in for real-time thermal system optimization. Full article

This paper focuses on optimisation of material parameters to describe the elastoplastic stress–strain relationship in finite element solvers. Two new methods are introduced to minimise the numerical error that occurs in the interspace between the experimental cyclic stress–strain curve and its representation using multilinear interpolation. Specifically, both methods are integrated into a Prandtl operator approach, which can be used to simulate the elastoplastic response of mechanical components subjected to variable thermomechanical loadings. The improvement as compared to standard interpolation is most substantial when the number of yield planes is limited, especially in the case of bilinear stress–strain curves. The innovation of this study is an algorithm that optimises positions of the stress–strain points across the temperature range of interest considering several input temperatures. It is shown that these methods are especially applicable for optimisation of material parameters when the stress–strain curves are available for a range of test temperatures that are needed for simulating thermomechanical fatigue. The improvement in the interpolation using these methods is exhibited for two materials with available experimental results: stainless steel EN 1.4512 and polyamide PA12. Full article

This study aims to qualitatively and quantitatively assess the ability of the flow solver “reactingFoam” of the open-source OpenFOAM software v.2506 for a control-volume-based computational fluid dynamics (CFD) solver in treating the reacting flow problem of a popular benchmarking bluff-body-stabilized turbulent diffusion (non-premixed) flame, that is, the HM1 flame. The HM1 flame has a fuel stream composed of 50% hydrogen (H₂) and 50% methane (CH₄) by mole. Thus, the acronym “HM1” stands for “hydrogen–methane, with level 1 of jet speed”. This fuel stream is surrounded by a coflow of oxidizing air jet. This flame was studied experimentally at the University of Sydney. A measurement dataset of flow and chemical fields was compiled and made available freely for validating relevant computational models. We simulate the HM1 flame using the reactingFoam solver and report here various comparisons between the simulation results and the experimental results to aid in judging the feasibility of this open-source CFD solver. The computational modeling was conducted using the specialized wedge geometry, suitable for axisymmetric problems. The turbulence–chemistry interaction (TCI) was based on the Chalmers’ partially stirred reactor (CPaSR) model. The two-equation k-epsilon framework is used in modeling the small eddy scales. The four-step Jones-Lindstedt (JL) reaction mechanism is used to describe the chemical kinetics. Two meshes (coarse and fine) were attempted, and a converged (mesh-independent) solution was nearly attained. Overall, we notice good agreement with the experimental data in terms of resolved profiles of the axial velocity, mass fractions, and temperature. For either mesh resolution, the overall deviation between the computational results and the experimental results is approximately 8% (mean absolute deviation) and 10% (root mean square deviation). These are favorably low. The current study, and the presented details about the reactingFoam solver and its implementation, can be viewed as a good case study in CFD modeling of reacting flows. In addition, the information we provide about the measurement dataset, the emphasized recirculation zone, the entrainment phenomena, and the irregularity in the radial velocity can help other researchers who may use the same HM1 data. Full article

The role of wall roughness in heat and mass transfer for fully developed viscous flows in square microchannels is investigated here. Since the roughness, which is the key geometrical feature to be investigated, introduces high velocity gradients at the wall, the effect of the viscous dissipation is considered. A fully developed flow in the forced convection regime is assumed. This assumption allows the two-dimensional treatment of the problem; thus, the velocity and temperature fields are simulated on the microchannel cross-section. The boundary roughness is modeled by randomly throwing points around the nominal square cross-section perimeter and by connecting those points to generate a simple polygon. This modification of the nominal square shape of the cross-section influences the velocity and temperature fields, which are computed by employing a finite element method solver. The heat and mass transfer is studied by calculating the Nusselt and the Poiseuille numbers as a function of roughness amplitude at the boundary. Each Nusselt and Poiseuille number is obtained by employing an averaging procedure over a sample of a thousand cases. Full article

This study presents numerical analyses of the thermal, metallurgical, and mechanical processes involved in welding. The temperature fields were computed by solving the transient heat transfer equation using the ABAQUS/Standard 2024 finite element solver. Two types of moving heat sources were applied: a surface Gaussian distribution and a volumetric model, both implemented via DFLUX subroutines to simulate welding on butt-jointed plates. The simulation accounted for key welding parameters, including current, voltage, welding speed, and plate dimensions. The thermophysical properties of the INC 738 LC nickel superalloy were used in the model. Solidification characteristics, such as dendritic arm spacing, were estimated based on cooling rates around the weld pool. The model also calculated transverse residual stresses and applied a hot cracking criterion to identify regions vulnerable to cracking. The peak transverse stress, recorded in the heat-affected zone (HAZ), reached 1.1 GPa under Goldak’s heat input model. Additionally, distortions in the welded plates were evaluated for both heat source configurations. Full article

This work aims to explore the magnetohydrodynamic mixed convection boundary layer flow (MHD-MCBLF) on a slanted extending cylinder using Eyring–Powell fluid in combination with Levenberg–Marquardt algorithm–artificial neural networks (LMA-ANNs). The thermal properties include thermal stratification, which has a higher temperature surface on the cylinder than on the surrounding fluid. The mathematical model incorporates essential factors involving mixed conventions, thermal layers, heat absorption/generation, geometry curvature, fluid properties, magnetic field intensity, and Prandtl number. Partial differential equations govern the process and are transformed into coupled nonlinear ordinary differential equations with proper changes of variables. Datasets are generated for two cases: a flat plate (zero curving) and a cylinder (non-zero curving). The applicability of the LMA-ANN solver is presented by solving the MHD-MCBLF problem using regression analysis, mean squared error evaluation, histograms, and gradient analysis. It presents an affordable computational tool for predicting multicomponent reactive and non-reactive thermofluid phase interactions. This study introduces an application of Levenberg–Marquardt algorithm-based artificial neural networks (LMA-ANNs) to solve complex magnetohydrodynamic mixed convection boundary layer flows of Eyring–Powell fluids over inclined stretching cylinders. This approach efficiently approximates solutions to the transformed nonlinear differential equations, demonstrating high accuracy and reduced computational effort. Such advancements are particularly beneficial in industries like polymer processing, biomedical engineering, and thermal management systems, where modeling non-Newtonian fluid behaviors is crucial. Full article

Within the 21st century, in the Maritime Silk Road, wave energy, a clean renewable source, is drawing more interest, especially in areas with power shortages. This paper investigates wave energy in ships, particularly in a hybrid electric bulk carrier, by designing a system that supplements the existing power setup with oscillating buoy wave energy converters. The system includes diesel generators (DGs), a wave energy generation system, heterogeneous energy storage (consisting of battery storage (BS) and thermal storage (TS)), a combined cooling heat and power (CCHP) unit, and a power-to-thermal conversion (PtC) unit. To ensure safe and reliable navigation despite uncertainties in wave energy output, onboard power loads, and outdoor temperature, a robust coordination method is adopted. This method employs a two-stage robust optimization (RO) strategy to coordinate the various onboard units across different time scales, minimizing operational costs while satisfying all operational constraints, even in the worst-case scenarios. By applying constraint linearization, the robust coordination model is formulated as a mixed-integer linear programming (MILP) problem and solved using an efficient solver. Finally, the effectiveness of the proposed method is validated through case studies and comparisons with existing ship operation benchmarks, demonstrating significant reductions in operational costs and robust performance under various uncertain conditions. Notably, the simulation results for the Singapore–Trincomalee route show an 18.4% reduction in carbon emissions compared to conventional systems. Full article

This study explores the computational analysis of catalytic combustion in cylindrical reactors using the Finite Volume Method (FVM) within Ansys Fluent. Through the incorporation of a combustion channel to facilitate diesel combustion, Ansys Fluent is utilized to predict the fluid dynamics during catalytic combustion. An extensive reaction mechanism file containing all related reactions is added into Ansys Fluent to model the catalytic combustion of methane. In this study, the catalyzed combustion of a methane, hydrogen, and air mixture is simulated on a heated platinum wall within a cylindrical channel using a 2D axisymmetric solver. Two mechanism files are employed: one defining gaseous species and the other including surface species definitions and surface reactions. Volumetric reactions are excluded from this analysis. The cylindrical channel comprises three sections: inlet, catalytic, and outlet, with the catalyzed reactions occurring on the wall surface of the catalytic section. The simulation results exhibit a gradual decrease in the mass fraction of reactants as catalytic combustion proceeds within the chamber, accompanied by a simultaneous increase in product formation. In particular, the presence of a catalytic channel within the combustion chamber catalyzes the combustion reaction, resulting in a higher chamber temperature. This study also presents predicted mass fraction profiles for both reactants and combustion products, highlighting the efficiency of Computational Fluid Dynamics (CFD) simulations in predicting chemical processes, particularly catalytic combustion. This research contributes to the understanding of complex phenomena such as catalytic combustion and underscores the potential of CFD simulations in explaining complicated chemical processes. Full article

Li ion batteries are emerging as the mainstream source for propulsion in the automotive industry. Subjecting a battery to extreme conditions of charging and discharging can negatively impact its performance and reduce its cycle life. Assessing a battery’s electrical and thermal behaviour is critical in the later stages of developing battery management systems (BMSs). The present study aims at the thermal modelling of a 3.3 Ah cylindrical 26650 lithium iron phosphate cell using ANSYS 2024 R1 software. The modelling phase involves iterating two geometries of the cell design to evaluate the cell’s surface temperature. The multi-scale multi-domain solution method, coupled with the equivalent circuit model (ECM) solver, is used to determine the temperature characteristics of the cell. Area-weighted average values of the temperature are obtained using a homogeneous and isotropic assembly. A differential equation is implemented to estimate the temperature due to the electrochemical reactions and potential differences. During the discharge tests, the cell is subjected to a load current emulating the Worldwide Harmonised Light Vehicles Test Procedure (WLTP). The results from the finite element model indicate strikingly similar trends in temperature variations to the ones obtained from the experimental tests. Full article

Phase change modeling in porous media is among the important challenges in many essential engineering problems, including thermal management, energy conservation or recovery, and heat transfer. One particularly efficient method of dissipating heat in a porous material is transpiration cooling with phase change. It is one of the most innovative cooling methods available for removing excessive heat flux from engine components such as combustors or gas turbine blades. There is, however, a lack of in-depth understanding of the interconnected mechanisms involved in such an application. In this work, an innovative numerical solver built on the OpenFOAM environment is constructed in order to explore the phase change process in a porous medium. The volume-of-fluid method and the Lee phase change model are applied in this numerical approach. The effects of coolant flow mass rate, heat flux, and porosity of porous structure on temperature and saturation distribution are investigated and discussed. The effects of both the external heat flux and the coolant mass flow rate under fixed porosity are also studied. The phase change is then delayed in the porous matrix when the amount of the injected coolant is increased. It reduces the area of two-phase and vapor regions. Also, a considerable rise in the upper surface temperature is obtained when the input heat flux or the porosity is separately enhanced. Full article

A standalone hybrid renewable energy system (HRES) that combines different types of renewable energy sources and storages offers a sustainable energy solution by reducing reliance on fossil fuels and minimizing greenhouse gas emissions. In this paper, a standalone hybrid renewable energy system (HRES) involving wind turbines, photovoltaic (PV) modules, diesel generators (DG), and battery banks is proposed. For this purpose, it is necessary to size and run the proposed system for feeding a residential load satisfactorily. For two typical winter and summer weeks, weather historical data, including irradiance, temperature, wind speed, and load profiles, are used as input data. The overall optimization framework is formulated as a bi-level mixed-integer nonlinear programming (BMINLP) problem. The upper-level part represents the sizing sub-problem that is solved based on economic and environmental multi-objectives. The lower-level part represents the energy management strategy (EMS) sub-problem. The EMS task utilizes the model predictive control (MPC) approach to achieve optimal technoeconomic operational performance. By the definition of BMINLP, the EMS sub-problem is defined within the constraints of the sizing sub-problem. The MATLAB R2023a environment is employed to execute and extract the results of the entire problem. The global optimization solver “ga” is utilized to implement the upper sub-problem while the “intlinprg” solver solves the lower sub-problem. The evaluation metrics used in this study are the operating, maintenance, and investment costs, storage unit degradation, and the number of CO₂ emissions. Full article

In the present work, Combined Heat and Mass Exchanger Networks (CHAMENs) with multiple utilities were synthesized using the pinch technology, the Microsoft Excel and GAMS programs for comparing process flowsheets. Due to the lack of information about streams that can transfer heat and mass, these were generated by combining streams that can only transfer heat and streams that can only transfer mass. On one hand, energy balances and mass balances were made when a common value of an open interval was bounded by source and target values of a stream and, on the other hand, by an open interval bounded by values based on information from the dataset. The CHAMEN formulation was resolved using the Generalized Reduced Gradient method from Microsoft Excel^® and the DICOPT solver from GAMS. When there were problems in convergence of a solution, initial values for solving the problem using the Solver Tool were obtained by changing the solving method or resolving the Heat Exchanger Network and the Mass Exchanger Network models separately. Heat and mass transfer per interval bounded by values based on information from the dataset can be used in designing the CHAMEN by hand. Six examples are presented in this work and they include streams exchanging heat and mass jointly and streams exchanging them separately. Two of the six examples presented were designed at the threshold–temperature and threshold–composition difference. For the first time using a mixed-integer linear programming framework, the heating of a stream with its own energy after cooling for the mass transferring process is reported. Full article

The primary research aim of this manuscript was to present a simplified absorber model and analyse the simulation results of the absorber model created to which, by design, only water was added and the outlet flue gas temperature was optimal. The obtained simulation results of the simplified absorber model were appropriately compared with the operational results of absorbers operating in professional WtE installations. This study focused on the simulation duration. The primary tool used in the paper is OpenFOAM (v2112). Two solvers were used for the calculations: ReactingParcelFoam and LTSReactingParcelFoam. They ran numerical tests on simplified absorber models. We evaluated the results according to the simulation time. We also examined the difference between the measured and calculated flue gas outlet temperatures. The results will guide further research on the absorber. They will speed up and improve the modelling of chemical processes. The only challenge was to define the chemical reactions and add a calcium molecule to the water droplet model. This work shows that we can simplify the absorber’s geometric model. It kept a low relative error and cuts the compute time. Using a local time step instead of a global one in numerical calculations significantly reduced their run time. It did this without increasing the relative error. The research can help develop complex three-phase flow models in the absorber in the future. Full article