Application Of Fluid Dynamics Research Articles

Wind and structural response monitoring of a lighting pole for the study of downburst effects on structures

Wind excited response of structures due to downbursts has been studied using wind tunnel simulations, computational fluid dynamics applications, and analytical procedures in the previous two decades. However, the studies have not been validated with full-scale wind and structural response measurements. To fill this research gap, continuous wind-and-structural response monitoring of three slender structures was implemented through the European research council-funded project, THUNDERR. This paper focuses on one of the monitored structures, describing the monitoring system, the dynamic and aerodynamic properties, and the registered data during two downburst events. The wind-excited response of the monitored structure during two case studies of downbursts is analyzed. The correlation between the wind speed and structural displacement parameters was also studied and the square of mean wind speed was found to be highly correlated with the mean displacement and the standard deviation of the fluctuating displacement. The fluctuating components of wind speed and top displacement were found to be partially correlated. The simplicity of the selected structure, and the possibility of obtaining both the quasi-steady and resonant components of the structural response from strain registrations, will make this study a benchmark for the validation of methods and simulations of downburst wind load.

Numerical simulation modelling on whole municipal solid waste incineration process by coupling multiple software for the analysis of grate speed and air volume ratio

Uncertainties in the calorific value and composition of municipal solid waste (MSW), the variability in operations, equipment performance decline, maintenance needs, and other dynamic factors make it challenging for operational experts to accurately gauge the overall combustion impact under fluctuating conditions. There is a need for a visual numerical simulation of the full MSW incineration (MSWI) process, with a focus on the effectiveness of the grate speed and air volume ratio. Unfortunately, software like Aspen Plus struggles to visually depict the effect of typically manipulated variables such as grate speed, and it is not well-suited for simulating solid-phase combustion and flue gas treatment. In response to these challenges, our study introduces a numerical simulation method for the MSWI process using a multi-software coupling approach. This simulation method incorporates (a) the use of custom software for simulating solid-phase combustion on the grate, (b) the application of Computational Fluid Dynamics (CFD) software for gas-phase combustion in the furnace, and (c) the utilization of chemical process simulation software for non-grate solid-phase combustion. The benchmark condition was determined using real-time running data from the Beijing MSWI Power Plant. The results show that for the incinerator’s third flue, flue gas G1, and flue gas G3, the relative errors between the simulated and actual values for flue gas temperature and oxygen concentration were 0.3% and 1.1%, 3.5% and 20%, and 0.2% and 20% respectively. In addition, we used eight non-benchmark conditions to study the effects of grate speed and air volume ratio. When the grate speed was gradually increased from 6 m/h to 8 m/h, O2, CO2, sulfur dioxide (SO2), sulfur trioxide(SO3), nitrogen monoxide (NO), and nitrogen oxide (NO2) at G1 had error fluctuation ranges of 5.9%− 48.5%, 2.5%− 11.5%, 10.42–28.57%, 7–23%, 29.10–45.52%, and 24.39–48.78%, respectively. When the primary air ratio was gradually increased from 0.84 to 0.96, the O2 concentration at G1 exhibited a steady upward trend. The simulation results provide insights into the adjustment range of the manipulated variables and offer additional support for the visualized and optimized control operation of the MSWI plant.

Detecting Under-Resolved Flow Physics Using Supervised Machine Learning

The accuracy of flow simulations is a major concern in computational fluid dynamics (CFD) applications. A possible outcome of inaccuracy in CFD results is missing a major feature in the flowfield. Many methods have been proposed to reduce numerical errors and increase overall accuracy, but these are not always efficient or even feasible. In this study, the principal component analysis (PCA) has been performed on compressible flow simulations around an airfoil to map the high-dimensional CFD data to a lower-dimensional PCA subspace. A machine learning classifier based on the extracted principal components has been developed to detect the simulations that miss the separation bubble behind the airfoil. The evaluative measures indicate that the model is able to detect most of the simulations where the separation region is poorly resolved. Moreover, a single mode responsible for the missing flow separation was uncovered that could be the subject of future studies. The results demonstrate that a machine learning model based on the principal components of the dataset is a promising tool for detecting possible missing flow features in CFD.

Theoretical analysis of new techniques applied to applications in fluid dynamics

ABSTRACT In this research study, we explore new proofs of theorems related to a novel technique by the name of the natural Adomian decomposition method (NADM), and then we apply it to find new exact solutions to nonlinear partial differential equations under proper initial conditions. Our solutions to nonlinear differential equations are given in series format, with convergence analysis for the proposed scheme. The new approach in this work can be considered as an alternative technique for the ones in the literature, to handle KdV-type equations such as the fifth-order Korteweg–de Vries (efKdV) equation, which is a crucial equation in fluid dynamics for the description of nonlinear wave processes. The new technique is a novel one to treat applications in the fields of mathematics, biology, engineering, physics, and other areas of science.

HipBone: A performance-portable graphics processing unit-accelerated C++ version of the NekBone benchmark

We present hipBone, an open-source performance-portable proxy application for the Nek5000 (and NekRS) computational fluid dynamics applications. HipBone is a fully GPU-accelerated C++ implementation of the original NekBone CPU proxy application with several novel algorithmic and implementation improvements which optimize its performance on modern fine-grain parallel GPU accelerators. Our optimizations include a conversion to store the degrees of freedom of the problem in assembled form in order to reduce the amount of data moved during the main iteration and a portable implementation of the main Poisson operator kernel. We demonstrate near-roofline performance of the operator kernel on three different modern GPU accelerators from two different vendors. We present a novel algorithm for splitting the application of the Poisson operator on GPUs which aggressively hides MPI communication required for both halo exchange and assembly. Our implementation of nearest-neighbor MPI communication then leverages several different routing algorithms and GPU-Direct RDMA capabilities, when available, which improves scalability of the benchmark. We demonstrate the performance of hipBone on three different clusters housed at Oak Ridge National Laboratory, namely, the Summit supercomputer and the Frontier early-access clusters, Spock and Crusher. Our tests demonstrate both portability across different clusters and very good scaling efficiency, especially on large problems.

Optimizing throughput of Seq2Seq model training on the IPU platform for AI-accelerated CFD simulations

Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for simulation, where traditional numerical simulations are supported by artificial intelligence approaches. We focus specifically on a program for training machine learning models supporting a computational fluid dynamics application. We use custom TensorFlow provided by the Poplar Software Development Kit to adapt the program for the IPU-POD16 platform and investigate its ease of use and performance scalability. Training a model on data from OpenFOAM simulations allows us to get accurate simulation state predictions in test time. We describe how to optimize multi-threading runtime options and utilize the popdist library to overcome a performance bottleneck in feeding training data to the IPU on the host side. Due to communication overheads, using data parallelism to utilize two IPUs instead of one does not improve the throughput. However, once the intra-IPU costs have been paid, the hardware capabilities for inter-IPU communication allow for good scalability. Increasing the number of IPUs from two to 16 improves the throughput from 560.8 to 2805.8 samples/s. Additionally, the experimental results show that reducing the precision of input data storage from FP32 to FP16 allows to improve training throughput by 12%, while tuning selected runtime variables, by up to 6.3%.

Symmetry analysis and invariant solutions of Riabouchinsky Proudman Johnson equation using optimal system of Lie subalgebras

The Lie symmetry analysis of the Riabouchinsky Proudman Johnson (RPJ) equation is discussed in this research. In the onset, we derive the geometric vector fields using the classical Lie symmetry technique. Here, we have a four-dimensional Lie algebra. A five-dimensional optimal system is then obtained utilising this four-dimensional Lie algebra. After that, due to the similarity reduction, nonlinear ordinary differential equations (ODEs) are obtained. These nonlinear ODEs are very significant to reveal the dynamical profile of the solution regions of the RPJ equation. The obtained solutions have applications in fluid dynamics and are helpful for recent research because they are associated to Reynolds numbers. For the purpose of understanding the physical significance of the identified solutions, Mathematica simulations of those solutions are also provided.

A Scalable Algorithm for Shape Optimization with Geometric Constraints in Banach Spaces

This work develops an algorithm for PDE-constrained shape optimization based on Lipschitz transformations. Building on previous work in this field, the $p$-Laplace operator is utilized to approximate a descent method for Lipschitz shapes. In particular, it is shown how geometric constraints are algorithmically incorporated avoiding penalty terms by assigning them to the subproblem of finding a suitable descent direction. A special focus is placed on the scalability of the proposed methods for large scale parallel computers via the application of multigrid solvers. The preservation of mesh quality under large deformations, where shape singularities have to be smoothed or generated within the optimization process, is also discussed. It is shown that the interaction of hierarchically refined grids and shape optimization can be realized by the choice of appropriate descent directions. The performance of the proposed methods is demonstrated for energy dissipation minimization in fluid dynamics applications.

An effective high-order five-point stencil, based on integrated-RBF approximations, for the first biharmonic equation and its applications in fluid dynamics

PurposeThe purpose of this paper is to present a new discretisation scheme, based on equation-coupled approach and high-order five-point integrated radial basis function (IRBF) approximations, for solving the first biharmonic equation, and its applications in fluid dynamics.Design/methodology/approachThe first biharmonic equation, which can be defined in a rectangular or non-rectangular domain, is replaced by two Poisson equations. The field variables are approximated on overlapping local regions of only five grid points, where the IRBF approximations are constructed to include nodal values of not only the field variables but also their second-order derivatives and higher-order ones along the grid lines. In computing the Dirichlet boundary condition for an intermediate variable, the integration constants are used to incorporate the boundary values of the first-order derivative into the boundary IRBF approximation.FindingsThese proposed IRBF approximations on the stencil and on the boundary enable the boundary values of the derivative to be exactly imposed, and the IRBF solution to be much more accurate and not influenced much by the RBF width. The error is reduced at a rate that is much greater than four. In fluid dynamics applications, the method is able to capture well the structure of steady highly non-linear fluid flows using relatively coarse grids.Originality/valueThe main contribution of this study lies in the development of an effective high-order five-point stencil based on IRBFs for solving the first biharmonic equation in a coupled set of two Poisson equations. A fast rate of convergence (up to 11) is achieved.

A Review on Recent Developments of RCCI Engines Operated with Alternative Fuels

Environmental concerns over automotive exhaust emissions and consumer demand for higher fuel efficiency have led to the development of low-temperature combustion concepts. The reactivity-controlled compression ignition (RCCI) engine is one among them and has the potential to reduce NOx and smoke emissions simultaneously. In this concept, a low-reactivity fuel is injected into the intake port and another high-reactivity fuel is injected into the cylinder directly. This results in reactivity stratification and provides more control over the rate of heat release. However, operating parameters such as reactivity of fuels, premixing ratio, injection strategies, exhaust gas recirculation ratio, piston bowl geometry, and compression ratio influence emissions formation. The article reviews recent developments on the effect of the above operating parameters on the performance and emission characteristics of RCCI engines operated with alternative fuels. The combustion strategies used to extend the RCCI mode to higher loads are also reviewed. Applications of computational fluid dynamics (CFDs) to design the combustion chamber for RCCI engines are discussed. The need for further improvements in the CFD models for RCCI engines is explained. After presenting a thorough review of recent literature, directions for future research on RCCI engines are proposed.

Special Issue: Applications of Computational Fluid Dynamics to the Built Environment

With ever-increasing computational power and the capability of numerical methods, it is now possible to accurately simulate flow conditions in a virtual environment [...]

Simple, Fast Nitric Oxide Planar Laser-Induced Fluorescence Model for Computational Fluid Dynamics Applications

The current work demonstrates the efficacy of a simple and fast model for nitric oxide (NO) laser-induced fluorescence (LIF). The model is validated with experimental LIF spectra computed from captured images of fluorescence from a gas cell filled with a known amount of NO. These data are obtained for several segments of the NO fluorescence spectrum. The selected segments encompass LIF lines with rotational quantum numbers appropriate for low-to-moderate temperature flows. The spectra obtained using the current model are also compared to those obtained from other theoretical models, namely, LIFBASE and LINUS. The current model is based on a previously developed version of a two-level fluorescence model and is developed specifically for applications in computational fluid dynamics (CFD) where rapid on-the-fly evaluations are required due to the potentially large number of grid cells for which LIF is being computed. Good agreement between the experimental and theoretical results provides confidence in current LIF modeling for use with CFD. An example application of the current model in a Mach 6.5 hypersonic mixing flowfield is also presented.

Local wind in urban canyons of a residential area in Quito-Ecuador

This study evaluates the behavior of the wind from its speed in representative urban canyons of residential buildings in the city of Quito. The methodology was based on the selection of case studies from the area of Concepción located in the north of the city to build simplified models according to their aspect ratio height / width (H / W) in blocks of 250 m by 250 m. In each case includes multiple configurations of urban canyons, giving priority to the west-east and north-south orientations, which are simulated by the application of Computational Fluid Dynamics (CFD). The local wind is evaluated according to pedestrian height and their predominant direction obtained from the historical information obtained from the weather station in the area. The results show that the predominant relationship of the wind retains higher speeds when it flows canyons with a lower H/W ratio.

A review of computational fluid dynamics application to investigate tropical cyclone wind speeds

A review of computational fluid dynamics application to investigate tropical cyclone wind speeds

Application of computational fluid dynamics (CFD) methods to analyze energy efficiency of indirect evaporative coolers

This paper proposes a method based on computational fluid dynamics to determine pressure drop and air distribution characteristics in recuperative exchangers. The numerical calculations were performed for a representative counter-flow heat exchanger with a relatively complex structure, providing a large heat exchange surface. To verify a proposed method, the empirical calculations based on known analytical solutions for straight channels with various shapes of cross-sections were also performed. Numerical and empirical calculations were compared with certified data obtained according to standards EN 308: 1997 standards. The verification showed that the numerical methods properly predict the pressure drop in operating parameters of the exchanger, within the uncertainty of experimental data. The empirical methods calculation accuracy strongly depends on the assumptions made before.

A Novel Multivariate Spectral Local Quasilinearization Method (MV-SLQLM) for Modelling Flow, Moisture, Heat, and Solute Transport in Soil

Conventionally, the problem of studying the transport of water, heat, and solute in soil or groundwater systems has been numerically solved using finite difference (FD) or finite element (FE) methods. FE methods are attractive over FD methods because they are geometrically flexible. However, recent studies demonstrate that spectral collocation (SC) methods converge exponentially faster than FD or FE methods using a few grid points or on coarse grids. This work proposes and applies a multivariate spectral local quasilinearization method (MV-SLQLM) to model the transportation and interaction of soil moisture, heat, and solute concentration in a nonbare soil ridge. The MV-SLQLM uses a quasilinearization method (QLM) to linearize any nonlinear equations and then employs a local linearization method (LLM) to decouple the linearized system of PDEs to form a sequence of equations that are solved in a computationally efficient manner. The MV-SLQLM is thus an extension of the bivariate spectral local linearization method (BI-SLLM) that fails to deal with a 2D problem and is a modification of the MV-SQLM whose efficiency is compromised when operating on high dense solution matrices. We use the residual error norms of the difference between successive iterations to affirm convergence to the expected solution. To illustrate the application and check the solution accuracy, we conduct systematic analyses of the effect of model parameters on distribution profiles. Findings are in good agreement with theory and literature, thereby revealing suitability of the MV-SLQLM to solve coupled nonlinear PDEs with environmental fluid dynamics applications.

The role of phase transition by inception and surface reactions for the synthesis of silicon nanoparticles in a hot-wall reactor – Simulation and experiment

A novel Eulerian particle model tailored for the application in computational fluid dynamics (CFD) is presented. The model is based on a bivariate moment method and features a full coupling with the gas-phase by kinetic formulations for inception, and activated and non-activated surface reactions. A new formulation for the particle composition accounts for the volatile content and its emission. The model is applied in the context of silicon nanopowder synthesis from monosilane, where a validation is performed with a well-established hot-wall reactor experiment from the literature. It is characterized by high precursor concentrations at moderate heating temperature of 853 K. Further, a new experiment was conducted for the comparison with the new model approach in a three-dimensional, transient simulation. The semi-industrial hot wall reactor features an unsteady complex flow field with buoyancy driven recirculation. The simulations enable new insights into the unsteady flow, mixing and nanoparticle formation process and contribute to their understanding. For the validation, residence-time dependent data for the precursor concentration, the primary particle size, and the particle number concentration are compared with results of the simulation at different stages. A comparison with the results of stochastic methods serves as further benchmark for the presented model. An excellent agreement with the experimental data is obtained, if essential growth mechanisms are considered. For the semi-industrial hot-wall reactor experiment, the BET surface and particle diameter, as well and the precursor consumption, are compared to the results of the new model and to a description with inception, coagulation, and sintering only. Due to the absence of crucial activated and non-activated surface reactions, the latter model predicts values that deviate more than one order of magnitude from the experimental data, while the new model shows an overall good agreement.

Shape Optimization Algorithms for Fluid Dynamics Applications

AbstractIn this work we present a comparison between shape optimization algorithms in different vector spaces. The main goal is to optimize the surface of an object with respect to a physical quantity. The main focus is on applications that require large element deformations as part of the optimization process, as for instance the removal and creation of geometric singularities such as edges and corners. The algorithms take into account the prevention of element degeneracy and overlapping, for instance by enforcing inequality constraints. For this purpose, an approach in the Hilbert space is compared to another in Banach spaces. The former is based on a nonlinear extension equation, whereas the p‐Laplace operator is used in the latter. Computational results are presented in the context of fluid dynamics applications, where the contour of an object is optimized with respect to the energy dissipation.

Research Progress in Numerical Simulation of Aircraft Wing Flow Field

Computational fluid dynamics has important application value and theoretical significance in engineering. Fluid mechanics has emerged as a way out of many engineering design problems. In recent years, applying fluid mechanics in the aircraft field has brought a breakthrough to problems that could not be solved previously. This paper mainly introduces the development history of the application of computational fluid dynamics in the direction of the wing and the specific application of this technology in the numerical simulation of the wing flow field. The aerodynamic characteristics of aircraft wings are related to the flight performance of the aircraft. The influence of wing aerodynamic characteristics, wing lift drag coefficient, and wing noise is a hot research issue. The influence of flow field research methods (such as numerical simulation) on the optimization and improvement process of the wing is analyzed, and the numerical results and simulation results of the flow field are found. The future development trend of the wing is proposed. Finally, it is believed that changes in airfoils will have a significant impact on aircraft performance.

Research on the pressure distribution under different airfoil types of aircraft

Airfoils produce life force for aircraft, which is the reason for planes flying in the sky. The formation of the airfoil depends on its shape, so airfoil designs play an important role in airplane designs. The airfoil design is also prioritized in the process of aircraft design, its speed of creating affecting the progress of the entire project. The goal of airfoil’s design is not simply to create “good” wings, because it does not exist. This means that when airfoils are adapting to a certain airflow or flying condition, their performance might not be satisfied due to environmental variations. Therefore, the application of Computational Fluid Dynamics (CFD) techniques and the Small Disturbance Equation, this study uses python to perform numerical analysis to simulate the surface pressure of the ideal wings under certain flying statues, and then applying a series of algorithms to calculate the shape of the target airfoils, which can find the most suitable airfoil shape under the flying circumstances. According to the researches, the best possible wings satisfying which the pressure below be as larger as possible than the pressure above to produce lift force, is f(x) = k*(x-1)∧4 for downside and f(x) = k*sin(pi(x-1)) for the top. Besides, after a series of calculations, this paper realized that the smaller the k value can be, the better fit it is to an ideal simulated airfoil shape.