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At least 37 records · Page 2

Potential quantum advantage for simulation of fluid dynamics

Numerical simulation of turbulent fluid dynamics needs to either parametrize turbulence—which introduces large uncertainties—or explicitly resolve the smallest scales—which is prohibitively expensive. Here, we provide evidence through analytic bounds and numerical studies that a potential quantum speedup can be achieved to simulate fluid dynamics using quantum computing. Specifically, we provide a lattice Boltzmann formulation of fluid dynamics for which we give evidence that low-order Carleman linearization is much more accurate than previously believed for these systems. This is achieved via a combination of reformulating the Navier-Stokes nonlinearity (u·$\triangledown$u) to lattice-Boltzmann nonlinearity (u 2 ) and accurately linearizing the dynamical equations, which effectively trades nonlinearity for additional degrees of freedom that add negligible expense in the quantum solver. Based on this, we apply a quantum algorithm for simulating the Carleman-linearized lattice Boltzmann equation and provide evidence that its cost scales logarithmically with system size compared with polynomial scaling in the best known classical algorithms. In this paper, we suggest that a quantum advantage may exist for simulating fluid dynamics, paving the way for simulating nonlinear multiscale transport phenomena in a wide range of disciplines using quantum computing.

42 ENGINEERING↗

Comparative Assessment of U-Net-Based Deep Learning Models for Segmenting Microfractures and Pore Spaces in Digital Rocks

Segmentation of high-resolution X-ray microcomputed tomography (µCT) images is crucial in digital rock physics (DRP), affecting the characterization and analysis of microscale phenomena in the porous media. The complexity of geological structures and nonideal scanning conditions pose significant challenges to conventional image segmentation approaches. Motivated by the recent increasing popularity of deep learning (DL) techniques in image processing, this work undertakes a comparative study of DL models, specifically U-Net and its variants, for segmenting multiple targets with distinguished features in digital rocks, including discrete fracture networks (DFNs), pore spaces, and solid rock. Particularly, DFNs have a smaller volumetric fraction over others, bringing in a substantial challenge of imbalanced segmentation. The primary focus is to evaluate the architecture and feature enhancement strategies of various DL models, including U-Net, attention U-Net, residual U-Net, U-Net++, and residual U-Net++. The models were designed as 2.5D, utilizing a central 2D image and its two adjacent upper and lower 2D images as input to provide a pseudo-3D context. In addition, because the ground truth of segmentation was unknown for real-world digital rocks, we created a benchmark data set following the inverse operations of segmentation. The data synthesis started from the label images (i.e., solid rock, pore spaces, and DFNs), followed by simulating partial volume blurring, adding random background noise, and introducing ring artifacts to mimic real raw X-ray µCT images. The data set, which included various rock types (i.e., sandstone and artificial data), scanning resolution, and magnitudes of noise and artifacts, was divided into training and testing data sets with a 90% and 10% ratio, respectively. Moreover, in addition to the conventional pixel-wise evaluation metrics, the physics-based metric of the lattice-Boltzmann method (LBM) simulated permeability provided more comprehensive assessments. The results demonstrated that the residual connections, nested architectures, and redesigned skip connections contribute to the model performance and give the residual U-Net++ the highest accuracy. The improvements were mainly on the boundaries and small targets, especially the DFNs, which dominate the interconnectivity and therefore affect the permeability greatly. This study also rigorously evaluated the efficiency and generalization of each model, demonstrating that the sophisticated architectures achieved excellent practicability and maintained robust performance on completely unseen data, ensuring their suitability for diverse and challenging DRP applications.

58 GEOSCIENCES↗

Multiphase Transport in Porous Media: Gas-Liquid Separation Using Capillary Pressure Gradients International Space Station (ISS) Flight Experiment Development

Advances in the understanding of multiphase flow characteristics under variable gravity conditions will ultimately lead to improved and as of yet unknown process designs for advanced space missions. Such novel processes will be of paramount importance to the success of future manned space exploration as we venture into our solar system and beyond. In addition, because of the ubiquitous nature and vital importance of biological and environmental processes involving airwater mixtures, knowledge gained about fundamental interactions and the governing properties of these mixtures will clearly benefit the quality of life here on our home planet. The techniques addressed in the current research involving multiphase transport in porous media and gas-liquid phase separation using capillary pressure gradients are also a logical candidate for a future International Space Station (ISS) flight experiment. Importantly, the novel and potentially very accurate Lattice-Boltzmann (LB) modeling of multiphase transport in porous media developed in this work offers significantly improved predictions of real world fluid physics phenomena, thereby promoting advanced process designs for both space and terrestrial applications.This 3-year research effort has culminated in the design and testing of a zero-g demonstration prototype. Both the hydrophilic (glass) and hydrophobic (Teflon) media Capillary Pressure Gradient (CPG) cartridges prepared during the second years work were evaluated. Results obtained from ground testing at 1-g were compared to those obtained at reduced gravities spanning Martian (13-g), Lunar (16-g) and zero-g. These comparisons clearly demonstrate the relative strength of the CPG phenomena and the efficacy of its application to meet NASAs unique gas-liquid separation (GLS) requirements in non-terrestrial environments.LB modeling software, developed concurrently with the zero-g test effort, was shown to accurately reproduce observed CPG driven gas-liquid separation phenomena. The design and fabrication of a micropost plate-lamina Hele-Shaw (HS) cell was performed which served as a computationally attainable geometric structure facilitating direct comparison between physical phenomena observed in our laboratory and the LB software predictions.

Wheeler, Richard R., Jr.↗

Direct Numerical Simulation of an Airfoil with Sand Grain Roughness on the Leading Edge

As part of a computational study of acoustic radiation due to the passage of turbulent boundary layer eddies over the trailing edge of an airfoil, the Lattice-Boltzmann method is used to perform direct numerical simulations of compressible, low Mach number flow past an NACA 0012 airfoil at zero degrees angle of attack. The chord Reynolds number of approximately 0.657 million models one of the test conditions from a previous experiment by Brooks, Pope, and Marcolini at NASA Langley Research Center. A unique feature of these simulations involves direct modeling of the sand grain roughness on the leading edge, which was used in the abovementioned experiment to trip the boundary layer to fully turbulent flow. This report documents the findings of preliminary, proof-of-concept simulations based on a narrow spanwise domain and a limited time interval. The inclusion of fully-resolved leading edge roughness in this simulation leads to significantly earlier transition than that in the absence of any roughness. The simulation data is used in conjunction with both the Ffowcs Williams-Hawkings acoustic analogy and a semi-analytical model by Roger and Moreau to predict the farfield noise. The encouraging agreement between the computed noise spectrum and that measured in the experiment indicates the potential payoff from a full-fledged numerical investigation based on the current approach. Analysis of the computed data is used to identify the required improvements to the preliminary simulations described herein.

Ribeiro, Andre F. P.↗

Physics Informed Broadband Noise Source Identification and Prediction of an Ideally Twisted Rotor

This work aims at a physics based approach for the prediction and isolation of broadband noise emanating from different regions of an ideally twisted rotor. A preliminary prediction was conducted using a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) implemented within the software suite, PowerFLOW. Regions of particular interest to broadband noise were investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor. These regions were then isolated and treated as individual Ffowcs Williams-Hawkings (FW-H) surfaces for three run conditions at a much finer spatial resolution to delineate the broadband noise from these separate regions from the total acoustic spectra. These predictions were then compared to experimentally acquired data as well as to semi-empirical prediction methods to highlight the acoustic contributions of various broadband noise generation mechanisms as well as to exemplify and explain shortcomings in the semi-empirical methodology.

Christopher S Thurman↗

Computational Prediction of Broadband Noise from a Representative Unmanned Aerial System Rotor

This work details the application of a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) employed by the software suite, PowerFLOW. This LBM-VLES simulation predicted the aeroacoustic noise emanating from a representative, small unmanned aircraft system rotor, namely, the DJI-9450 in a hover condition. Predicted total aerodynamic loading as well as 2D aerodynamic loading along discrete spanwise sections of a rotor blade were compared to lower fidelity predictions and experimental results acquired in the Structural Acoustic Loads and Transmission anechoic chamber facility at the NASA Langley Research Center. The total acoustic spectra were decomposed into tonal and broadband components, which showed that broadband noise was a dominant contributor above 1 kHz for this rotor. These data were then compared to experimentally acquired data, showing good agreement up to approximately 11 kHz. Above 11 kHz, however, a grid sensitivity study showed dependency of the highest resolvable frequency on the spatial resolution of the computational domain, explaining the roll off in predicted data. Individual broadband noise sources were further investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor, providing evidence that blade self-noise was the prominent noise source. Using these results, blade wake interaction noise was seen to be negligible for this particular rotor, which was further validated by calculating blade vortex miss distances and comparing to theory.

Christopher S. Thurman↗

Physics-Informed Broadband Noise Source Identification and Prediction of an Ideally Twisted Rotor

This work aims to provide a physics-based approach for the prediction and isolation of broadband noise emanating from different regions of an ideally twisted rotor. A preliminary prediction was conducted using a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) implemented within the software suite, PowerFLOW. Regions of particular interest to broadband noise were investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor. These regions were then treated as individual Ffowcs Williams and Hawkings (FW-H) surfaces and simulated for three run conditions at a finer spatial resolution to identify the broadband noise from these separate regions and isolate it from the total acoustic spectra. These predictions were then compared to experimentally acquired data and to semiempirical prediction methods to highlight the acoustic contributions of various broadband noise generation mechanisms as well as to exemplify and explain shortcomings in the semiempirical methodology.

Christopher S Thurman↗

Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 2 - Airframe Noise Simulations

Aeroacoustic simulations of a sub-scale, generic, low-boom supersonic aircraft model at low speeds were carried out using the Lattice-Boltzmann Very Large Eddy Simulation software PowerFLOW® and a Ffowcs Williams and Hawkings approach. The objective was to characterize the airframe noise signature of the configuration and determine the similarities and differences to conventional subsonic aircraft. We quantified the noise produced by the flap and landing gear by simulating the aircraft with and without deployment of these components. Mach number scaling of the far-field noise levels was examined by performing simulations at different flow speeds. We demonstrate that a solid surface formulation does not capture the aircraft acoustic field properly, while a carefully constructed permeable surface formulation yields far-field spectra that compare very favorably to results from direct probing of the simulated flow field.

low boom↗

Summary of the 5th Propulsion Aerodynamics Workshop Nozzle Test Case: Heated Nozzle Exhaust Passing Over A Film-Cooled Plate

This paper summarizes findings from the fifth AIAA Propulsion Aerodynamics Workshop nozzle test case. The experimental configuration examined by workshop participants was a subsonic nozzle with a square exit blowing a heated exhaust over a film-cooled plate. Computational fluid dynamics solutions were obtained and compared to experimental measurements of flow velocities and temperatures, as well as plate surface temperatures. The heated nozzle operated with a Mach 0.3 exit flow at a static temperature ratio of 2.7. Cooling air blowing ratios of 0, 1, and 2 were considered. Computational meshes for the flow domain were provided for participants. Workshop participants from eight separate organizations represented government, industry, and academia. A variety of flow solutions were obtained: Most of the flow solutions employed a Reynolds-averaged Navier-Stokes (RANS) approach, but scale-resolving simulations were used in some cases, including wall-modeled large-eddy simulation (LES), and a few hybrid RANS-LES approaches. One Lattice-Boltzmann solver was employed. For heat transfer to the test article, many participants used a conjugate heat transfer approach. Effects of mesh sensitivity, flow solution approach, and wall heat transfer approach are considered. In general, a fully three-dimensional conjugate heat transfer approach enabled better prediction of surface temperatures than simpler wall temperature boundary treatments. Also, the scale resolving approaches provided better prediction of static temperatures in the flow immediately above the plate consisting of the hot jet exhaust boundary layer interacting with the cooling film. Comparisons of plate surface friction drag and heat transfer obtained from the computations are also presented.

nozzle↗

Summary of the 5th Propulsion Aerodynamics Workshop Nozzle Test Case: Heated Nozzle Exhaust Passing Over A Film-Cooled Plate

This paper summarizes findings from the fifth AIAA Propulsion Aerodynamics Workshop nozzle test case. The experimental configuration examined by workshop participants was a subsonic nozzle with a square exit blowing a heated exhaust over a film-cooled plate. Computational fluid dynamics solutions were obtained and compared to experimental measurements of flow velocities and temperatures, as well as plate surface temperatures. The heated nozzle operated with a Mach 0.3 exit flow at a static temperature ratio of 2.7. Cooling air blowing ratios of 0, 1, and 2 were considered. Computational meshes for the flow domain were provided for participants. Workshop participants from eight separate organizations represented government, industry, and academia. A variety of flow solutions were obtained: Most of the flow solutions employed a Reynolds-averaged Navier-Stokes (RANS) approach, but scale-resolving simulations were used in some cases, including wall-modeled large-eddy simulation (LES), and a few hybrid RANS-LES approaches. One Lattice-Boltzmann solver was employed. For heat transfer to the test article, many participants used a conjugate heat transfer approach. Effects of mesh sensitivity, flow solution approach, and wall heat transfer approach are considered. In general, a fully three-dimensional conjugate heat transfer approach enabled better prediction of surface temperatures than simpler wall temperature boundary treatments. Also, the scale resolving approaches provided better prediction of static temperatures in the flow immediately above the plate consisting of the hot jet exhaust boundary layer interacting with the cooling film. Comparisons of plate surface friction drag and heat transfer obtained from the computations are also presented.

nozzle↗

Prediction of Broadband Blade-Wake Back-Scatter Noise from a Hovering Ideally Twisted Rotor using OVERFLOW2-ANOPP2

This work illustrates the use of a hybrid RANS/LES framework for the prediction of broadband noise via integral formulations from an ideally twisted hovering rotor. Four simulations were conducted, which investigated the effect of different turbulence modeling and spatiotemporal resolutions. The aerodynamic performance and aeroacoustics predicted by these four computational cases were compared against data acquired in the Small Hover Anechoic Chamber at the NASA Langley Research Center and against previous simulations conducted using the lattice-Boltzmann solver, PowerFLOW. The simulation case with the finest spatial resolution had the most favorable aerodynamic performance and broadband noise comparison with measured data; however, the simulation case utilizing the SST-DDES turbulence model predicted the most accurate tonal noise signature. Aerodynamic flowfield visualizations identified near-wake trailing edge vortex shedding, perpendicular blade-vortex interactions, and tip vortex formation, which are known to cause broadband noise. The fluid dynamics associated with a new broadband noise source, blade-wake back-scatter, were also identified. Lastly, a broadband noise source visualization technique was utilized to confirm the presence of blade-wake back-scatter as a dominant broadband noise source.

blade-wake back-scatter↗

A Study on Computational Cost Reduction of Simulations of Phase-Change Material (PCM) Embedded Heat Exchangers

Thermal storage can be implemented using Phase-Change Materials (PCM), which absorb significant latent heat with a relatively small temperature change. PCM phase-change processes are transient and are driven by thermal diffusion and natural convection – the latter, especially for melting process. Modeling and simulation of PCM heat exchangers (HX’s) is typically computationally intensive due to the relatively complex time-dependent physics. Most of the PCM modeling work in the literature uses high-order modeling tools such as Computational Fluid Dynamics (CFD) and Lattice-Boltzmann Method (LBM). For design purposes, the existing PCM modeling approaches are not practical, limiting researchers in their ability to investigate new ideas and different PCM’s with faster turnarounds. This paper presents a study investigating the reduction of computational cost of PCM embedded HX’s CFD models by evaluating the feasibility of spatial reduction without losing accuracy. The analysis consists of comparing full and partial domain under full melting conditions. The subject of this study is a single straight tube with circular transverse fins in the vertical orientation, using PCM’s with 35oC nominal melting temperature. Different tube and fin dimensions are investigated. Results indicate that the reduced domain reproduces - in half the run time - the same behavior as the full domain since the buoyancy effects are localized and patterned. The outputs from the partial domain simulation were used to build a non-general correlation for the PCM heat transfer characteristics and demonstrated how it can be implemented in a Finite Control Volume Reduced Order Model (ROM). The ROM can accurately reproduce the CFD simulations at 4 to 5 orders of magnitude faster.

25 ENERGY STORAGE↗

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗

Learning a general model of single phase flow in complex 3D porous media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

36 MATERIALS SCIENCE↗

Capturing membrane structure and function in lattice Boltzmann models

Here, we develop a mesoscopic approach to model the nonequilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A general closure rule is developed to describe mass transport across the membrane, which is able to account for protein-mediated diffusion based on a coarse-grained representation. We demonstrate that our model is able to recover the Goldman equation from first principles and show that hyperpolarization occurs when membrane charging dynamics are controlled by multiple relaxation timescales. The approach provides a promising way to characterize non-equilibrium behaviors that arise due to the role of membranes in mediating transport based on realistic three-dimensional cell geometries.

59 BASIC BIOLOGICAL SCIENCES↗

Effective permeability of an immiscible fluid in porous media determined from its geometric state

Based on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeability function of saturation only that is process or path dependent with an underlying dependency on pore structure and wettability. For applications (fuel cells to underground CO 2 storage), it is imperative to determine the effective phase permeability relationships where the traditional approach is based on the inverse modeling of time-consuming experiments. The underlying reason is that the fundamental upscaling step from pore to Darcy scale, which links the pore structure of the porous medium to the continuum hydraulic conductivities, is not solved. Herein, we develop an artificial neural network (ANN) that relies on fundamental geometrical relationships to determine the mechanical energy dissipation during creeping immiscible two-fluid flow. Finally, the developed ANN is based on a prescribed set of state variables based on physical insights that predict the effective permeability of 4500 unseen pore-scale geometrical states with R 2 = 0.98.

42 ENGINEERING↗