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NASA Ames Center personnel presented data on stages of code development and corresponding experiments in the application of computational fluid dynamics for aeronautical investigations. Specific subjects included algorithms, grid generation, facilities, instrumentation, and data acquisition. Numerical simulation and flow modelling were described to show the procedure for calibration and validation.
A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and a visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) results, was chosen to interactively display the reconstructed light sheet images with the numerical surface geometry for the model or aircraft under study. The photogrammetric reconstruction technique and the image processing and computer graphics techniques and equipment are described. Results of the computer-aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images with CFD solutions in the same graphics environment is also demonstrated.
The use of sub-scale wind tunnel test data to predict the behavior of commercial transport high lift systems at in-flight Reynolds number is limited by the so-called 'inverse Reynolds number effect'. This involves an actual deterioration in the performance of a high lift device with increasing Reynolds number. A lack of understanding of the relevant flow field physics associated with numerous complicated viscous flow interactions that characterize flow over high-lift devices prohibits computational fluid dynamics from addressing Reynolds number effects. Clearly there is a need for research that has as its objective the clarification of the fundamental flow field physics associated with viscous effects in high lift systems. In this investigation, a detailed experimental investigation is being performed to study the interaction between the slat wake and the boundary layer on the primary airfoil which is known as a confluent boundary layer. This little-studied aspect of the multi-element airfoil problem deserves special attention due to its importance in the lift augmentation process. The goal of this research is is to provide an improved understanding of the flow physics associated with high lift generation. This process report will discuss the status of the research being conducted at the Hessert Center for Aerospace Research at the University of Notre Dame. The research is sponsored by NASA Ames Research Center under NASA grant NAG2-905. The report will include a discussion of the models that have been built or that are under construction, a description of the planned experiments, a description of a flow visualization apparatus that has been developed for generating colored smoke for confluent boundary layer studies and some preliminary measurements made using our new 3-component fiber optic LDV system.
Time evolution of plane, cosmic-ray modified shocks has been simulated numerically for the case with parallel magnetic fields. Computations were done in a 'three-fluid' dynamical model incorporating cosmic-ray and Alfven-wave energy transport equations. Nonlinear feedback from the cosmic rays and Alfven waves is included in the equation of motion for the underlying plasma, as is the finite propagation speed and energy dissipation of the Alfven waves. Exploratory results confirm earlier, steady state analyses that found these Alfven transport effects to be potentially important when the upstream Alfven speed and gas sound speeds are comparable. As noted earlier, Alfven transport effects tend to reduce the transfer of energy through a shock from gas to energetic particles. These studies show as well that the timescale for modification of the shock is altered in nonlinear ways. It is clear, however, that the consequences of Alfven transport are strongly model dependent and that both advection of cosmic rays by the waves and dissipation of wave energy in the plasma will be important to model correctly when quantitative results are needed. Comparison is made between simulations based on a constant diffusion coefficient and more realistic diffusion models allowing the diffusion coefficient to vary in response to changes in Alfven wave intensity. No really substantive differences were found between them.
This viewgraph presentation reviews the flow analysis of the propulsion feedlines in the X-34. The objective of the analysis was to determine the flow development at the engine interface, and to predict the pressure drop in the feedline. The presentation shows the design of the feedlines, and the computational grids. It reviews the numerical method, which included solving the curvilinear coordinate transport equations. Line graphs review the computational fluid dynamic results. The results and conclusions are also presented.
A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.
NASA possesses a wealth of historical cryogenic experiments that provide valuable insights into the design, troubleshooting, and understanding involved in the complex fluid and thermodynamics of managing cryogenic propellants. One approach to leveraging these historical datasets is by simulating these experiments to validate the accuracy of simulation environments and constituent models. This study focused on simulating a selection of the K site test series for both static and sloshing pressurized liquid methane draining experiments conducted at NASA in the 1970’s, utilizing computational fluid dynamics. The simulations were performed in the ANSYS FLUENT environment using the Volume of Fluid (VOF) numerical approach. A k-omega turbulence model was used with interfacial turbulence damping, and accurately predicted the amount of pressurant needed to maintain the required tank pressure throughout the static drain. The static simulation predicted the temperature stratification in the ullage observed at the end of the drain. During the methane expulsion with sloshing test, many features were successfully captured using the k-omega turbulence model with interfacial turbulence damping included. The rate of phase change and liquid temperature was overpredicted compared to the experimental measurements. The overprediction may be attributed to uncertainties in the vessel geometry, methane pressurant temperature and composition, and methodological differences in how the sloshing frequency was adjusted during the expulsion.
A finite volume based network analysis procedure has been applied to model unsteady flow without and with heat transfer. Liquid has been modeled as compressible fluid where the compressibility factor is computed from the equation of state for a real fluid. The modeling approach recognizes that the pressure oscillation is linked with the variation of the compressibility factor; therefore, the speed of sound does not explicitly appear in the governing equations. The numerical results of chilldown process also suggest that the flow and heat transfer are strongly coupled. This is evident by observing that the mass flow rate during 90-second chilldown process increases by factor of ten.
Motivations (Ensure a Higher Level of Confidence in the Predictability & Reliability of Numerical Simulation for Multiscale Complex Nonlinear Fluid Problems) - The last two decades have been an era when computation is ahead of analysis & when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems & non-traditional fields (Especially when computations offer the ONLY way of generating this type of data limited simulations). - At present some of the numerical uncertainties can be explained and minimized by traditional numerical analysis and standard CFD practices. However, such practices, usually based on linearized analysis, MIGHT NOT be sufficient for strongly nonlinear and/or stiff problems. - We need a good understanding of the nonlinear behavior of numerical schemes being used as an integral part of code verification, validation and certification.
Fluid models are essential for understanding and predicting low-temperature plasma (LTP) behavior in various scientific and industrial settings. This paper provides an introductory tutorial on fluid modeling of LTPs, covering model formulation, implementation, and computational simulations. The tutorial focuses on five main components of the formulation of LTP fluid models: fluid flow, energy, chemistry, electromagnetism, and material properties, as well as in essential aspects of model implementations, including multiscale phenomena, multiphysics coupling, and numerical convergence. Designed for students and early-career researchers, this work offers a practical foundation for developing and using fluid models, from in-house computational codes to commercial software, bridging fundamental theory with real-world applications.
Our work in directional solidification has been in the following areas: (1) Dynamics of dendrites including rigorous mathematical analysis of the resulting equations; (2) Examination of the near-structurally unstable features of the mathematically related Hele-Shaw dynamics; (3) Numerical studies of steady temperature distribution in a vertical Bridgman device; (4) Numerical study of transient effects in a vertical Bridgman device; (5) Asymptotic treatment of quasi-steady operation of a vertical Bridgman furnace for large Rayleigh numbers and small Biot number in 3D; and (6) Understanding of Mullins-Sererka transition in a Bridgman device with fluid dynamics is accounted for.
Numerical simulations of an unstable supersonic slab-symmetric jet are described. The instabilities within the jet are characterized by growing internal body waves and their coupled surface waves that are also predicted in linear perturbation theory. The characteristic theory of fluid dynamics is used to help interpret the wave morphologies. It is demonstrated that these waves can be excited by imposing an arbitrary disturbance. From the numerical simulations, it is found that the sound waves propagating against the flow slow down as they propagate outward, and they grow in amplitude. These waves eventually disrupt the jet at a certain length. This disruption length is related to the jet Mach number and the perturbation intensity. Thus, the Mach number of a jet observed with a radio telescope can be estimated by measuring the disruption length and estimating the perturbation intensity. The jet Mach numbers in radio tailed sources determined in this way agree quite well with estimates from ram pressure bending arguments. The wiggles and flares observed in many extragalactic jets, especially in tailed radio sources, appear to be intimately related to instabilities and the jet disruption process.
Smart proxy technology leverages the art of artificial intelligence and machine learning in order to build accurate and very fast proxy models for highly complex numerical simulation models. In this project, smart proxy technology is used to replicate the results of a highly complex single phase CFD simulation with reasonable degree of accuracy while reducing the computational cost associated with such CFD simulations. The CFD model under study simulates the combustion of natural gas under various conditions such as varying natural gas composition and flow rate, inlet air flow rate and temperature, and outlet pressure in a High-Pressure Combustion Facility (B6 Combustor) with more than 4 million simulation cells. Only eight CFD simulation runs were used to create a smart proxy model that replicates the detail distribution of Pressure, Temperature, Nitrogen, Oxygen and Carbon-dioxide concentration in the CFD simulation model in seconds with less than 10% error.
Several turbulent and nonturbulent solutions of the Navier-Stokes equations are obtained. The unaveraged equations are used numerically in conjunction with tools and concepts from nonlinear dynamics, including time series, phase portraits, Poincare sections, Liapunov exponents, power spectra, and strange attractors. Initially neighboring solutions for a low-Reynolds-number fully developed turbulence are compared. The turbulence is sustained by a nonrandom time-independent external force. The solutions, on the average, separate exponentially with time, having a positive Liapunov exponent. Thus, the turbulence is characterized as chaotic. In a search for solutions which contrast with the turbulent ones, the Reynolds number (or strength of the forcing) is reduced. Several qualitatively different flows are noted. These are, respectively, fully chaotic, complex periodic, weakly chaotic, simple periodic, and fixed-point. Of these, we classify only the fully chaotic flows as turbulent. Those flows have both a positive Liapunov exponent and Poincare sections without pattern. By contrast, the weakly chaotic flows, although having positive Liapunov exponents, have some pattern in their Poincare sections. The fixed-point and periodic flows are nonturbulent, since turbulence, as generally understood, is both time-dependent and aperiodic.
The built environment of spaceships is host to a microbial community that affects crew and craft alike. While the static composition of this community has been characterized and its temporal dynamics examined, the mechanisms controlling its make-up and evolutionary trajectory are not understood. Systematic analyses of microbial diversity show consistent patterns in community composition and function. Understanding these patterns' ecological origins remains a significant challenge, as it requires connecting processes at varying temporal and spatial scales. However, it is clear that the state and trajectories of microbial communities are in-part determined by their physical environment. In this regard, the spaceflight environment includes numerous interacting factors that differentiate it from Earth environments, including an altered atmospheric composition, reduced gravity (and thus altered fluid dynamics), and increased ionizing radiation. These factors impart selective pressures on microbial communities that affect their evolutionary trajectories and thus the risks and benefits these communities represent to crew and craft. The radiation environment of space leads to chronic exposure to low doses and is difficult to mimic on Earth. Thus, little is known about how microbial communities in spacecraft will respond and evolve. Therefore, given the limitations of existing studies, we aim to empirically determine how exposure to low doses of ionizing radiation for thousands of cell divisions affects rates of mutation accumulation in bacteria and the trajectory of their evolution. In this way, we will provide a critical set of data for designing safe and robust space missions. Here we discuss our progress towards this aim, including the construction of exposure facilities, our culturing and analysis approach, and preliminary data.
This paper focuses on the evolution of advection upstream splitting method(AUSM) schemes. The main ingredients that have led to the development of modern computational fluid dynamics (CFD) methods have been reviewed, thus the ideas behind AUSM. First and foremost is the concept of upwinding. Second, the use of Riemann problem in constructing the numerical flux in the finite-volume setting. Third, the necessity of including all physical processes, as characterised by the linear (convection) and nonlinear (acoustic) fields. Fourth, the realisation of separating the flux into convection and pressure fluxes. The rest of this review briefly outlines the technical evolution of AUSM and more details can be found in the cited references. Keywords: Computational fluid dynamics methods, hyperbolic systems, advection upstream splitting method, conservation laws, upwinding, CFD
Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions
Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.