Search Results (31)

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Advances in numerical modeling are essential for heat-transfer applications in electronics cooling, renewable energy, and sustainable construction. This review explores key methods like Computational Fluid Dynamics (CFD), the Finite Element Method (FEM), the Finite Volume Method (FVM), and multiphysics modeling, alongside emerging strategies such as Adaptive Mesh Refinement (AMR), machine learning (ML), reduced-order modeling (ROM), and high-performance computing (HPC). While these techniques improve accuracy and efficiency, they also increase computational energy demands, contributing to a growing carbon footprint and sustainability concerns. Sustainable computing practices, including energy-efficient algorithms and renewable-powered data centers, offer potential solutions. Additionally, the increasing energy consumption in numerical modeling highlights the need for optimization strategies to mitigate environmental impact. Future directions point to quantum computing, adaptive models, and green computing as pathways to sustainable thermal management modeling. This study systematically reviews the latest advancements in numerical heat-transfer modeling and, for the first time, provides an in-depth exploration of the roles of computational energy optimization and green computing in thermal management. This review outlines a roadmap for efficient, environmentally responsible heat-transfer models to meet evolving demands. Full article

This paper presents a numerical sketch-based methodology to achieve optimal product design solutions, bridging the gap between initial conceptual sketches and advanced engineering analyses. The proposed approach enables the transformation of simple hand-drawn sketches into digital models suitable for complex computational simulations and design optimization. Using computer vision algorithms, sketches are processed to generate digital design components that serve as inputs for Finite Element Analysis (FEA). In order to further enhance the overall design process, topology optimization (TO) is also performed, iteratively refining the geometry to achieve optimal material distribution for improved structural performance. Additionally, Adaptive Mesh Refinement (AMR) techniques are applied to ensure computational efficiency and accuracy by dynamically refining the mesh in regions of high complexity or stress concentration. The synergy of sketch-based modeling, FEA, TO, and AMR demonstrates significant potential in reducing design cycles while maintaining high-performance standards. Finally, it should be noted that the proposed pipeline consists of a fully automated procedure, hence it could reduce the learning curve for the designers, enabling companies to onboard employees faster and integrate advanced design techniques into their workflows without extensive training. The above-mentioned modules render the introduced approach particularly suitable for applications in product design development that can be utilized in several industries like mechanical, manufacturing, and furniture. Full article

The early stages of hydrogen–air and methane–air flame dynamics and the development and evolution of tulip flames in closed tubes of various aspect ratios and in a semi-open tube are studied by solving the fully compressible reactive Navier–Stokes equations using a high-order numerical method coupled to detailed chemical models for stoichiometric hydrogen/air and methane/air mixtures. The use of adaptive mesh refinement (AMR) provides adequate resolution of the flame reaction zone, pressure waves, and flame–pressure wave interactions. The purpose of this study is to gain a deeper insight into the influence of chemical kinetics on the combustion regimes leading to the formation of a tulip flame and its subsequent evolution. The simulations highlight the effect of the flame thickness, flame velocity, and reaction order on the intensity of the rarefaction wave generated by the flame during the deceleration phase, which is the principal physical mechanism of tulip flame formation. The obtained results explain most of the experimentally observed features of tulip flame formation, e.g., faster tulip flame formation with a deeper tulip shape for faster flames compared to slower flames. Full article

Internal airflow dynamics play a crucial role in spray drying engineering by governing particle transport and, consequently, the quality of dried products. For this application, airflow dynamics represent short- and long-timescale behaviors across the main jet and recirculation regions and have been related, among other factors, to spray chamber design. This study examines the parametric effects of key geometrical design parameters on internal airflow dynamics using Design of Experiments (DOE) methodologies and 3D Computational Fluid Dynamics (CFD) simulations. The CFD model adopts a cost-efficient approach, including adaptive mesh refinement (AMR) methods, enabling running multiple simulation cases while retaining turbulence-resolving capabilities. The results provide quantitative parameter–response relationships, offering insights into the impact of chamber geometry on complex airflow behaviors. Among the parameters studied, the chamber aspect ratio strongly influences the strength of external recirculation flows. The inlet swirl primarily governs the stability of central and recirculating flows, while the conical–cylindrical section topology, in conjunction with the jet Reynolds number, affects flow impingement on walls, predominantly caused by the precession and reversal of the central jet. This methodology demonstrates significant potential for future studies on particle drying, equipment, process scale-up, and alternative chamber configurations in spray drying systems. Full article

Electroencephalographic (EEG) source localization is a fundamental tool for clinical diagnoses and brain-computer interfaces. We investigate the impact of model complexity on reconstruction accuracy by comparing the widely used three-layer boundary element method (BEM) as an inverse method against a five-layer BEM accelerated by the fast multipole method (BEM-FMM) and coupled with adaptive mesh refinement (AMR) as forward solver. Modern BEM-FMM with AMR can solve high-resolution multi-tissue models efficiently and accurately. We generated noiseless 256-channel EEG data from 15 subjects in the Connectome Young Adult dataset, using four anatomically relevant dipole positions, three conductivity sets, and two head segmentations; we mapped localization errors across the entire grey matter from 4000 dipole positions. The average location error among our four selected dipoles is ∼5$\mathrm{m}$$\mathrm{m}$ (±2$\mathrm{m}$$\mathrm{m}$) with an orientation error of ∼${12}^{\circ }$ (±$7^{\circ }$). The average source localization error across the entire grey matter is ∼9$\mathrm{m}$$\mathrm{m}$ (±4$\mathrm{m}$$\mathrm{m}$), with a tendency for smaller errors on the occipital lobe. Our findings indicate that while three-layer models are robust under noiseless conditions, substantial localization errors (10–20$\mathrm{m}$$\mathrm{m}$) are common. Therefore, models of five or more layers may be needed for accurate source reconstruction in critical applications involving noisy EEG data. Full article

The finite element discretization of computational physics problems frequently involves the manual generation of an initial mesh and the application of adaptive mesh refinement (AMR). This approach is employed to selectively enhance the accuracy of resolution in regions that encompass significant features throughout the simulation process. In this paper, we introduce Adaptnet, a Graph Neural Networks (GNNs) framework for learning mesh generation and adaptation. The model is composed of two GNNs: the first one, Meshnet, learns mesh parameters commonly used in open-source mesh generators, to generate an initial mesh from a Computer Aided Design (CAD) file; while the second one, Graphnet, learns mesh-based simulations to predict the components of an Hessian-based metric to perform anisotropic mesh adaptation. Our approach is tested on structural (Deforming plate–Linear elasticity) and fluid mechanics (Flow around cylinders–steady-state Stokes) problems. Our findings demonstrate the model’s ability to precisely predict the dynamics of the system and adapt the mesh as needed. The adaptability of the model enables learning resolution-independent mesh-based simulations during training, allowing it to scale effectively to more intricate state spaces during inference. Full article

As the need for handling complex geometries in computational fluid dynamics (CFD) grows, efficient and accurate mesh generation techniques become paramount. This study presents an adaptive mesh refinement (AMR) technology based on cell-based Cartesian grids, employing a distance-weighted least squares interpolation for finite difference discretization and utilizing immersed boundary methods for wall boundaries. This facilitates effective management of both transient and steady flow problems. Validation through supersonic flow over a forward-facing step, subsonic flow around a high Reynolds number NHLP airfoil, and supersonic flow past a sphere demonstrated AMR’s efficacy in capturing essential flow characteristics while wisely refining and coarsening meshes, thus optimizing resource utilization without compromising accuracy. Importantly, AMR simplified the capture of complex flows, obviating manual mesh densification and significantly improving the efficiency and reliability of CFD simulations. Full article

A rotating detonation engine (RDE) is a highly promising detonation-based propulsion system and has been widely researched in recent decades. In this study, BYCFoam, the latest gaseous version of the BYRFoam family, is developed specifically for RDE simulations. It is based on the standard compressible flow solver rhoCentralFoam in OpenFOAM and incorporates several enhancements: improved reconstruction variables and flux schemes; detailed chemistry and transport properties; the utilization of an adaptive mesh refinement (AMR) and dynamic load balancing (DLB). A series of comprehensive numerical tests are conducted, including the shock-tube problem, shock-wave diffraction, homogeneous ignition delay, premixed flame, planar detonation, detonation cellular structure and rotating detonation combustor (RDC). The results demonstrate that BYCFoam can accurately and efficiently simulate the deflagration and detonation processes. This solver enhances the capability of the BYRFoam family for the in-depth exploration of RDE in future research. Full article

In tsunami studies, understanding the intricate dynamics in the swash area, characterised by the shoaling effect, remains a challenge. In this study, we employed the adaptive mesh refinement (AMR) method to model tsunami inundation and propagation in the Onagawa town physical flume experiment. Using the open-source flow solver Basilisk, we implemented the Saint-Venant (SV) equations, Serre–Green–Naghdi (SGN) equations, and a nonhydrostatic multilayer (ML) extension of the SGN equations. A hydraulic bore tsunami-like wave was used as the input boundary condition. The objective was to assess the efficiency of the AMR method with nonhydrostatic tsunami models in overcoming limitations in 2D and quasi-3D models in flume experiments, particularly with respect to improving accuracy in arrival time and run-up detection. The results indicate improved performance of the SGN and SV models in determining tsunami arrival times. The ML model demonstrated enhanced wave run-up simulations on complex built-in terrain. The refined roughness coefficient determined using the ML solver captured the arrival time well in the northern section of the Onagawa model, albeit with a 1 s delay. The AMR method offered a computationally stable solution with an 86.3% reduction in computational time compared to a constant grid. While effective, the nonhydrostatic models entail the use of a great deal of computational resources. Full article

When a submarine encounters an emergency situation, it should take emergency-surfacing actions by moving upward with a large angle of attack in the vertical plane. Previous research has often neglected the effect of vertical plane motion on the lateral force (F_y), rolling moment (M_x), and yawing moment (M_z). To examine the flow characteristics of submarines at high angles of attack on the vertical plane, the SST-DDES method is adopted in conjunction with adaptive mesh refinement (AMR) technology, and the new Omega vortex detection method is employed as the AMR criterion for numerical calculations. The obtained results are then appropriately verified by conducting water tank experiments, and the effects of different angles of attack and heel angles on F_y, M_x, and M_z are methodically examined. The results reveal that, in the flow around the vertical plane of a submarine, the influence of F_y and M_z cannot be ignored. In addition, when the vertical velocity of the hull is greater than 0.6 m/s, the influence of M_x cannot be overlooked either. When the angle of attack on the vertical plane of the submarine is greater than 25°, the effects of F_y, M_x, and M_z cannot be neglected, and the effect of M_z is particularly prominent, with its amplitude close to or greater than the average value of the pitch moment (M_y). The obtained results reveal that the presence of the heel angle (θ) intensifies the forces on the hull for F_y, M_x, and M_z, and the forces caused by the vertical velocity at F_y, M_x, and M_z cannot be neglected. These findings can provide a mechanical analysis basis for the analysis of nonlinear motion phenomena during submarine surfacing. Full article

In the combustion chamber of scramjets, fuel jets interact with supersonic airflow in the form of a liquid jet in crossflow (LJIC). It is difficult to achieve adequate jet–crossflow mixing and the efficient combustion of fuel in an instant. Large eddy simulation (LES), the coupled level-set and volume of fluid (CLSVOF) method, and an adaptive mesh refinement (AMR) framework are used to simulate supersonic LJICs in this article. This way, LJIC atomization characteristics and mechanisms can be further explored and analyzed in detail. It is found that the surface waves of the liquid column exist in a two-dimensional form, including vertical and spanwise directions. Column breakup occurs when all the spanwise surface waves between adjacent vertical surface waves break up. Bow shock waves, composed of multiple connected arcuate shock waves, are dynamic and will change with the evolution of the liquid column. The vortex ring movement of supersonic LJICs, whose trends in the vertical and spanwise directions are different, is relatively complex, which is due to the complex and time-dependent shape of liquid columns. Full article

To save computational time and physical memory in welding thermo-mechanical analysis, an accurate adaptive mesh refinement (AMR) method was proposed based on the feature of moving heat source during the welding. The locally refined mesh was generated automatically according to the position of the heat source to solve the displacement field. A background mesh, without forming a global matrix, was designed to maintain the accuracy of stress and strain after mesh coarsening. The solutions are always carried out on the refined computational mesh using a selective integration scheme. To evaluate the performance of the developed method, a fillet welding joint was first analyzed via validation of the accuracy of conventional FEM by experiment. Secondly, a larger fillet joint and its variations with a greater number of degrees of freedom were analyzed via conventional FEM and current AMR. The simulation results confirmed that the proposed method is accurate and efficient. An improvement in computational efficiency by 7 times was obtained, and memory saving is about 63% for large-scale models. Full article

The investigation of cavitating trailing vortices emerging from marine propellers is of great interest in the industry. With the help of computational fluid dynamics (CFD), studying the cavitating trailing vortices may be facilitated. However, limitations in computational power raise the necessity to execute numerical simulations as efficiently as possible. The time-efficient simulation of cavitating trailing vortices interacting with rigid bodies is especially challenging due to the continuous change of cavity locations. This study investigates the usability, capability, and practicability of automatic adaptive refinement at every calculation time step for transient Reynolds-averaged Navier–Stokes (RANS) and large eddy CFD simulations of the cavitating tip and hub vortices, utilizing the Schnerr–Sauer cavitation model, in the presence of a rudder located in the propeller slipstream and for an isolated propeller, with additional focus on the computational effort necessary for using high frequency updating adaptive mesh refinement (AMR). It is found that AMR is suitable for resolving cavities with relative motion to the propeller and in interaction with slipstream obstacles. However, the computation time is significantly increased, which renders this method useful only if a classic AMR is not possible due to geometrical limitations. Even in the cases that benefit from the automated AMR, numerical instabilities may lead to unphysical pressure fluctuations, which reduce the suitability of the method for the evaluation of underwater radiated noise. Full article

The use of adaptive meshing strategies to perform cost-effective transient simulations of spray drying processes is evaluated. These simulations are often computationally expensive, given the large differences between the characteristic times of the central jet and those of the unsteady flow developed at its periphery. Managing the computational cost through the control of the grid resolution by regions is inadequate in many of these applications since the grid resolution requirements change dynamically within the domain. These conditions are related to the unsteady nature of the flow in both the central jet and the flow recirculation zones. Therefore, the application of adaptive mesh refinement (AMR) strategies is recommended. In this paper, general AMR criteria based on relative errors are evaluated by testing three mesh adaptation criteria: velocity gradient, pressure gradient, and vorticity. This evaluation is performed using a low-cost turbulence model with eddy resolution (DDES) in two different types of drying chambers, in which experimental measurements are available. The use of AMR exerts appreciable effects on decreasing computational costs and contributes to the capture of large eddies in critical regions. The present approach provides an appropriate balance between solution accuracy and computational cost. By using a correct AMR configuration, it is possible to obtain results similar to those obtained on a fixed grid but reducing the computational costs by 3 to 5 times. Full article