Industrial Computational Fluid Dynamics Research Articles

Convergence Acceleration of Favre-Averaged Non-Linear Harmonic Method

Abstract This paper develops a numerical procedure to accelerate the convergence of the Favre-averaged non-linear harmonic (FNLH) method. The scheme provides a unified mathematical framework for solving the sparse linear systems formed by the mean flow and the time-linearized harmonic flows of FNLH in an explicit or implicit fashion. The approach explores the similarity of the sparse linear systems of FNLH and leads to a memory-efficient procedure, so that its memory consumption does not depend on the number of harmonics to compute. The proposed method has been implemented in the industrial computational fluid dynamics solver Hydra. Three test cases are used to conduct a comparative study of explicit and implicit schemes in terms of convergence, computational efficiency, and memory consumption. Comparisons show that the implicit scheme yields better convergence than the explicit scheme and is also roughly 7–10 times more computationally efficient than the explicit scheme with four levels of multigrid. Furthermore, the implicit scheme consumes only approximately 50% of the memory required by the explicit scheme with four levels of multigrid. Compared with the full-annulus unsteady Reynolds-averaged Navier–Stokes simulations, the implicit scheme produces comparable results to URANS with computational time and memory consumption that are two orders of magnitude smaller.

Concept of Computational Fluid Dynamics Design and Analysis Tool for Food Industry: A Bibliometric

Technology that is currently in demand is CFD. By simulating fluid flow around a product on a computer, the computational fluid dynamics (CFD) technique allows designers of new products to be tested. This research aims to analyze the bibliometrics of CFD publications as a design tool in the food industry to determine concepts, trends, and contributions of previous research. Computational Fluid Dynamics (CFD) is a technology used to test product designs through computer simulations of fluid flow around the product. The use of technology in various industries, such as the food industry, is essential to create better products or services. This research uses a bibliometric analysis method supported by theoretical analysis. This research consists of 5 steps, namely (i) determining the research theme for formulating keywords, (ii) collecting publication documents, (iii) data processing, (iv) bibliometric analysis, and (v) preparing a report. The keywords used in this research are "Computational Fluid Dynamics Design (CFD) in Food Industry." The results of the publication search found a total of 211 documents from 1992 to 2023. The average number of publications was 6.59. The trend of CFD publications in the food industry was first carried out in 1992. The development of this publication has been fluctuating, and there has been an increase in publications in the last five years (2019 - 2023). Research publications regarding CFD in the food industry are grouped into 20 subject areas. Contributions to this research consisted of 159 authors, 160 affiliates, and 51 countries. Completing this research will likely provide information regarding publication sources and contributions made by several scientists from various affiliates and countries worldwide.

A graph neural network-based framework to identify flow phenomena on unstructured meshes

Driven by the abundant data generated from computational fluid dynamics (CFD) simulations, machine learning (ML) methods surpass the deterministic criteria on flow phenomena identification in the way that they are independent of a case-by-case threshold by combining the flow field properties and the topological distribution of the phenomena. The current most popular and successful ML models based on convolutional neural networks are limited to structured meshes and unable to directly digest the data generated from unstructured meshes, which are more widely used in real industrial CFD simulations. We proposed a framework based on graph neural networks with the proposed fast Gaussian mixture model as the convolution kernel and U-Net architecture to detect flow phenomena based on a graph hierarchy generated by the algebraic multigrid method embedded in the open-source CFD solver, code_saturne. We demonstrate the superiority of the proposed kernel and U-Net architecture, along with the generality of the framework to unstructured mesh and unseen case, on detecting the vortices once trained on a single backward-facing step case. Our proposed framework can be trivially extended to detect more flow phenomena in three dimensional cases, which is ongoing work.

Assessment of Engineering Turbulence Models in Buoyant Diabatic Turbulent Flow

Turbulent heat transfer in buoyancy-dominated flows is a challenging problem for computational fluid dynamics (CFD). Many authors attribute model error in these conditions to the Reynolds analogy. We leverage a brand-new direct numerical simulation database to evaluate the performance of several popular turbulence models in buoyant diabatic channel flow. We find that heat transfer results are relatively accurate, with a Nusselt number error less than 20%. However, the turbulent flow solution is very inaccurate, with wall shear overpredicted by up to 100%. This indicates significant turbulence model error in such flows. We determined that the dominant sources of model error are missing physics in the algebraic Reynolds stress framework and the simple buoyancy production term used in industrial CFD. We suggest that future modeling efforts focus on these two sources of model error. We demonstrate that the Reynolds analogy is not the dominant source of model error.

Resolvent analysis of a finite wing in transonic flow

Shock waves interacting with turbulent boundary layers on wings can result first in self-sustained flow unsteadiness and eventually in structural vibration. Due to its importance to modern wing design and aircraft certification, the transonic flow physics continue to be investigated intensively. Herein we focus the discussion on three main aspects. First, we assess a practical implementation of an iterative resolvent algorithm in the linear harmonic incarnation of an industrial computational fluid dynamics code for computing optimal forcing and response modes. This heavily relies on the efficient solution of large sparse linear systems of equations. Second, we showcase its application as a predictive tool to detect transonic buffet flow unsteadiness, well before a global stability analysis can first identify its dynamics through weakly damped eigenmodes, using the NASA common research model at wind-tunnel conditions. Third, we discuss its ability to uncover modal physics, not identifiable through global stability analysis, revealing higher-frequency wake and wingtip vortex modes while shedding some light on the elusive finite wing equivalent of the aerofoil buffet mode. We demonstrate that earlier computational limitations of resolvent analysis, when solving the truncated singular value decomposition using matrix-forming methods with direct matrix factorisation, have been overcome ready for industrial use.

Industrial practice and CFD investigation of a multi-chamber fluidized bed reactor for MnO2 ore reduction

The multi-chamber fluidized bed reactor (MCFBR) is beneficial to the higher solids conversion rate, but the complex configuration needs special methodology for the rational design and smooth operation. In this study, an actual plant data of MCFBR for the reduction of MnO2 ore were analyzed, which indicated that the recovery rate of Mn was confirmed to be kept above 95% normally. To investigate the multi-chamber fluidized bed hydrodynamics and reaction characteristics, the 3D computational fluid dynamics (CFD) numeration coupled with structure-based transfer model and multi-chamber calculation method was established. The effect of mesoscale structure on the prediction of multi-chamber reaction process was evaluated as well. The simulation results showed that the model was able to calculate the gas–solid reaction behavior more accurately than the traditional model without taking mesoscale structure into account. The computed tanks-in-series number of 2.0 is less than the actual chamber number of 4.0 for the wide gap between the vertical baffle and the side wall. The quantitative effects of partition configuration, fluidized structure, and operating condition on the solids conversion rate were estimated as well.

Accelerating legacy applications with spatial computing devices

Heterogeneous computing is the major driving factor in designing new energy-efficient high-performance computing systems. Despite the broad adoption of GPUs and other specialized architectures, the interest in spatial architectures like field-programmable gate arrays (FPGAs) has grown. While combining high performance, low power consumption and high adaptability constitute an advantage, these devices still suffer from a weak software ecosystem, which forces application developers to use tools requiring deep knowledge of the underlying system, often leaving legacy code (e.g., Fortran applications) unsupported. By realizing this, we describe a methodology for porting Fortran (legacy) code on modern FPGA architectures, with the target of preserving performance/power ratios. Aimed as an experience report, we considered an industrial computational fluid dynamics application to demonstrate that our methodology produces synthesizable OpenCL codes targeting Intel Arria10 and Stratix10 devices. Although performance gain is not far beyond that of the original CPU code (we obtained a relative speedup of times 0.59 and times 0.63, respectively, for a single optimized main kernel, while only on the Stratix10 we achieved times 2.56 by replicating the main optimized kernel 4 times), our results are quite encouraging to drawn the path for further investigations. This paper also reports some major criticalities in porting Fortran code on FPGA architectures.

Laminar–Turbulent Transition Prediction on Industrial Computational Fluid Dynamics Applications

This paper presents Ansys Fluent laminar–turbulent transition results using the shear stress transport model applied to the workshop cases of the First American Institute of Aeronautics and Astronautics Computational Fluid Dynamics (CFD) Transition Modeling Prediction Workshop. The key objectives of this workshop were to assess the current state-of-the-art laminar–turbulent transition models in an industrial Computational Fluid Dynamics environment and to determine and document the best practices to simulate laminar–turbulent transition flows. Sensitivity of the shear stress transport model to mesh refinement was established on a zero-pressure-gradient flat plate. Two other cases [a two-dimensional natural laminar flow (NLF) (1)-0416F airfoil, and a scaled Common Research Model (CRM)-NLF aircraft model] were selected as validation cases using a hierarchy of structured and unstructured meshes. Due to the complexity of the geometry and the airflow around the Common Research Model (CRM)- Natural laminar Flow (NLF) aircraft model, mesh adaptation cycles were also conducted to capture the shock, the wake, and the wing-tip vortices produced by the CRM-NLF. The accuracy of the model is evaluated using transition location measurements obtained with temperature-sensitive paint, pressure coefficient distributions at multiple wingspan stations, and aerodynamic coefficients at numerous angles of attack. The outcome of these comparisons will provide guidelines to conduct laminar–turbulent transition simulations with the model on simple and complex aerospace designs.

Acoustic Mode Attenuation in Ducts (Using CFD) with Time-Domain Impedance Boundary Condition

In the framework of improving aircraft nacelle design to comply international regulation on aircraft noise, a time-domain impedance boundary condition (TDIBC) based on the oscillo-diffusive representation is implemented in an industrial computational fluid dynamics (CFD) solver under a characteristic formalism, in order to take into account acoustic liner attenuation. A validation of such TDIBC is carried out, first on a two-dimensional benchmark case, then on a more realistic three-dimensional cylindrical configuration, with focus on the acoustic modal content and its attenuation with and without flow. Unsteady Reynolds-averaged Navier–Stokes computations are performed, with the grazing flow being considered laminar. Good agreement is found between the CFD results and the references (computational aeroacoustics results and experiments), with differences in the order of for most cases. The formulation chosen for the TDIBC proved to have no significant impact on numerical stability or computational time.

Integration of Mixed Reality to CFD in Industry 4.0: A Manufacturing Design Paradigm

Simulation, as a pillar technology of Industry 4.0, is a key tool for improving manufacturing processes. Simulation is an indispensable set of technological tools and methods for the successful implementation of digital manufacturing, since it allows for the experimentation and validation of product, process, and system design and configuration. The value of simulation is evident, especially in today’s volatile manufacturing environment, which is influenced by globalization and ever-increasing demands for higher levels of product customization and personalization. Moreover, a significant manufacturing issue is the interoperability and communication among the several simulation tools. To that end, an Industrial Internet of Things (IIoT) framework for simulation and visualization of selected monitored values based on Mixed Reality (MR) and Computational Fluid Dynamics (CFD) in a cloud-computing environment for intuitive data visualization on smart devices is presented in this paper. As such, in light of the possibilities offered by digital technologies such as CFD simulation, smart factories can gain a competitive advantage because of the low cost, low risk, and the provided useful insights. The range of CFD applications encountered in process manufacturing and engineering varies greatly depending on the industry. Summarizing, this review paper identifies the gaps in current practices, and future trends and challenges to be met on the field are outlined. The contribution of the research work extends to the proposal of a workflow for the integration of Mixed Reality (MR) to the CFD simulation, in an attempt to create simulation holograms on the user’s field of view.

Design and analysis of exhaust manifold for multi-cylinder diesel engine with monolith catalytic converter using CFD

This paper discusses the challenges in converting the existing multi-cylinder diesel ventilation system into an innovative model of the manifold with monolithic. Reactant gases after treatment of car engines are increasingly being used for the benefit of environmental quality, especially in the large metropolitan region of the country, through the use of exhaust systems to bring an end to their main pollutants. A well-conditioned exhaust system increases the performance of the engine. The performance of the manifold has a significant impact on engine efficiency. With the accelerated growth of modern technology and numerical methods, computer simulation has become a valuable method for research and development of fluid flow systems. The industrial CFD (Computational Fluid Dynamics) software was used to analyze the exhaust manifold system. In order to enhance the fundamental understanding of manifold operations, extensive knowledge was obtained on the flow property distribution and heat transfer. Various calculations were performed to research the parametric impacts of working conditions and math on the exhibition of manifolds. Proposals were made to improve complex plan and execution.

A Machine-Learnt Wall Function for Rotating Diffusers

Abstract Data-driven tools and techniques have proved their effectiveness in many engineering applications. Machine-learning has gradually become a paradigm to explore innovative designs in turbomachinery. However, industrial computational fluid dynamics (CFD) experts are still reluctant to embed similar approaches in standard practice and very few solutions have been proposed so far. The aim of the work is to prove that standard wall treatments can obtain serious benefits from machine-learning modeling. Turbomachinery flow modeling lives in a constant compromise between accuracy and the computational costs of numerical simulations. One of the key factors of the process is defining a proper wall treatment. Many works point out how insufficient resolutions of boundary layers may lead to incorrect predictions of turbomachinery performances. Wall functions are universally exploited to replicate the physics of boundary layers where grid resolution does not suffice. Widespread wall functions were derived by the observation of a few canonical flows, further expressed as a simple polynomial of Reynolds number and turbulent kinetic energy. Despite their popularity, these functions are frequently applied in flows where the ground assumptions cease to be true, such as rotating passages or swirled flows. In these flows, the mathematical formulations of wall functions do not account for the distortion on the boundary layer due to the combined action of centrifugal and Coriolis forces. Here, we will derive a wall function for rotating passages, through means of machine-learning. The algorithm is directly implemented in the NS equations solver. Cross-validation results show that the machine-learnt wall treatment is able to effectively correct the turbulent kinetic energy field near the solid walls, without impairing the accuracy of the Reynolds-averaged numerical simulations (RANS) turbulence model in any way.

An Overview of Hybrid RANS–LES Models Developed for Industrial CFD

An overview of scale-resolving simulation (SRS) methods used in ANSYS Computational Fluid Dynamics (CFD) software is provided. The main challenges, especially when computing boundary layers in large eddy simulation (LES) mode, will be discussed. The different strategies for handling wall-bound flows using combinations of RANS and LES models will be explained, along with some specific application examples. It will be demonstrated that the stress-blended eddy simulation (SBES) approach is optimal for applications with a mix of boundary layers and free shear flows due to its low cost and its ability to handle boundary layers in both RANS and wall-modeled LES (WMLES) modes.

Investigation of heat-transfer and fluid dynamic of nanofluids used in heating building

This paper proposes an approach to investigating numerically the behavior of pressure drop and heat transfer flowing through a pipe under constant wall heat flux for copper (II) oxide (CuO), aluminum oxide (Al2O3) and silicon dioxide (SiO2) nanofluids. This approach consists of (a) using the industrial computational fluid dynamics code Ansys CFX 15 for all the simulations reported in this paper, (b) validating the numerical results for the flow of water by comparing the Nusselt number and friction factor in a circular tube used in heating buildings in cold regions and (c) evaluating the use of the three nanofluids in heating buildings. An excellent concordance is obtained with the water- and nanofluid-associated theoretical–empirical heat transfer and pressure drop correlations. Numerical results showed that the use of nanofluids in heating buildings is more efficient. From the thermal condition, the aluminum oxide nanofluid is more effective than the copper (II) oxide and silicon dioxide nanofluids, and the performance index of the aluminum oxide nanofluid is also higher compared with those of copper (II) oxide and silicon dioxide nanofluids. The analysis shows that using nanofluids in heat exchangers could reduce volumetric and mass flow rates. Nanofluids require smaller heating systems, which are able to distribute the same quantity of thermal energy using base fluids. This will also reduce environmental pollutants because smaller heating units use less power.

A new thermal-hydraulics/thermomechanics coupling methodology for the modeling of the behavior of sodium-cooled fast reactors fuel subassemblies under irradiation

The fuel pin bundles of Sodium-cooled Fast Reactors (SFR) undergo significant geometrical changes during their irradiation, which affect the flow and temperature distributions of the coolant in the fuel subassembly, the knowledge of which is necessary for safety assessments. Since the phenomena responsible for the deformation of the fuel bundles, namely the swelling and creep of the cladding, strongly depend on temperature, a coupling between the thermal-hydraulic and thermomechanical evolutions of the fuel subassemblies exists. This paper introduces a novel methodology for the numerical simulation of SFR subassemblies, based on the coupling between the industrial Computational Fluid Dynamics (CFD) code Star-CCM+ and a specialized numerical tool dedicated to the modeling of the thermomechanical behavior of SFR fuel subassemblies during irradiation, DOMAJEUR2. The coupling is implemented via the exchange of the diametral deformation of the claddings, calculated by DOMAJEUR2, and their associated temperature distributions, obtained with Star-CCM+. The sodium mass flow rate reduction expected in the deformed geometries is also taken into account.The developed methodology is employed to study a 7-pin SFR bundle. It is shown that, for high irradiation doses, taking the coupling into account leads to a lower end of life bundle deformation than with the traditional non-coupled simulations, consequence of the calculated temperature increase, induced by the deformation itself. The existence of operational limits on both the maximal cladding temperature and the maximal swelling in SFR highlights the relevance of these results in the context of reactor safety. Additionally, a comparison of two different thermomechanical models, one based on 1D pipe finite elements and the other on volumetric finite elements, shows that they are in good agreement. Finally, the high temperature gradients on the circumference of the fuel pin claddings are shown to have a minor effect on their diametral strain.

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

For computational fluid dynamics (CFD) applications with a large number of grid points/cells, parallel computing is a common efficient strategy to reduce the computational time. How to achieve the best performance in the modern supercomputer system, especially with heterogeneous computing resources such as hybrid CPU+GPU, or a CPU + Intel Xeon Phi (MIC) co-processors, is still a great challenge.An in-house parallel CFD code capable of simulating three dimensional structured grid applications is developed and tested in this study. Several methods of parallelization, performance optimization and code tuning both in the CPU-only homogeneous system and in the heterogeneous system are proposed based on identifying potential parallelism of applications, balancing the work load among all kinds of computing devices, tuning the multi-thread code toward better performance in intra-machine node with hundreds of CPU/MIC cores, and optimizing the communication among inter-nodes, inter-cores, and between CPUs and MICs.Some benchmark cases from model and/or industrial CFD applications are tested on the Tianhe-1A and Tianhe-2 supercomputer to evaluate the performance. Among these CFD cases, the maximum number of grid cells reached 780 billion. The tuned solver successfully scales up to half of the entire Tianhe-2 supercomputer system with over 1.376 million of heterogeneous cores. The test results and performance analysis are discussed in detail.

Statistical Approach for Computational Fluid Dynamics State-of-the-Art Assessment: N-Version Verification and Validation

A statistical approach for computational fluid dynamics (CFD) state-of-the-art (SoA) assessment is presented for specified benchmark test cases and validation variables, based on the combination of solution and N-version verification and validation (V&V). Solution V&V estimates the systematic numerical and modeling errors/uncertainties. N-version verification estimates the random simulation uncertainty. N-version validation estimates the random absolute error uncertainty, which is combined with the experimental and systematic numerical uncertainties into the SoA uncertainties and then used to determine whether or not the individual codes/simulations and the mean code are N-version validated at the USoAi and USoA intervals, respectively. The scatter is due to differences in models and numerical methods, grid types, domains, boundary conditions, and other setup parameters. Differences between codes/simulations and implementations are due to myriad possibilities for modeling and numerical methods and their implementation as CFD codes and simulation applications. Industrial CFD codes are complex software with many user options such that even in solving the same application, different results may be obtained by different users, not necessarily due to user error but rather the variability arising from the selection of various models, numerical methods, and setup options. Examples are shown for ship hydrodynamics applications using results from the Seventh CFD Ship Hydrodynamics and Second Ship Maneuvering Prediction Workshops. The role and relationship of individual code solution V&V versus N-version V&V and SoA assessment are discussed.

CFD Modeling of Combustion in Biomass Furnace

Due to the need for the optimization of industrial furnaces Computational Fluid Dynamics (CFD) is an important and indispensable tool for understanding for instance the mixing between flue gases, combustion air and the pollutant formation.This paper reports a computational fluid dynamics analysis of an industrial biomass boiler. The analysis was carried out using a CFD model for the combustion of the volatile gases released from the biomass combustion in the grate.The results obtained for the temperature, velocity and concentration of species fields within the boiler are now being used to enable the analysis and optimization of the combustion process. Moreover, the results show that inside the furnace the mixing of the gases with the combustion air could be improved, for instance through the optimization of the secondary air flow in relation to the operating conditions of the boiler, which would lead to the lower pollutant emissions.

On the role and challenges of CFD in the aerospace industry

ABSTRACTThis article examines the increasingly crucial role played by Computational Fluid Dynamics (CFD) in the analysis, design, certification, and support of aerospace products. The status of CFD is described, and we identify opportunities for CFD to have a more substantial impact. The challenges facing CFD are also discussed, primarily in terms of numerical solution, computing power, and physical modelling. We believe the community must find a balance between enthusiasm and rigor. Besides becoming faster and more affordable by exploiting higher computing power, CFD needs to become more reliable, more reproducible across users, and better understood and integrated with other disciplines and engineering processes. Uncertainty quantification is universally considered as a major goal, but will be slow to take hold. The prospects are good for steady problems with Reynolds-Averaged Navier-Stokes (RANS) turbulence modelling to be solved accurately and without user intervention within a decade – even for very complex geometries, provided technologies, such as solution adaptation are matured for large three-dimensional problems. On the other hand, current projections for supercomputers show a future rate of growth only half of the rate enjoyed from the 1990s to 2013; true exaflop performance is not close. This will delay pure Large-Eddy Simulation (LES) for aerospace applications with their high Reynolds numbers, but hybrid RANS-LES approaches have great potential. Our expectations for a breakthrough in turbulence, whether within traditional modelling or LES, are low and as a result off-design flow physics including separation will continue to pose a substantial challenge, as will laminar-turbulent transition. We also advocate for much improved user interfaces, providing instant access to rich numerical and physical information as well as warnings over solution quality, and thus naturally training the user.

CFD studies of the propagation and extinction of flame in an under-ventilated and over-ventilated enclosure

This piece of work is a contribution to the model-building and numerical simulation of fire phenomenon concerning fire outbreak, in confined enclosures. The numerical tool that has been used is the industrial Computational Fluid Dynamics (CFD) code called Fire Dynamics Simulator (FDS), in its 5.5.3 version. The chosen configuration of Foote and Chen et al. has allowed us to evidence the ventilation phenomena. The results of calculations that we carried out under over-ventilation conditions were satisfactory. A gap is nevertheless observed between calculations and measurements when the measurement point is located close to the air inlet duct. In under-ventilated conditions, the results are equally satisfactory, but appear to require heat flow sensitivity analysis to be excellent.