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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Influence of baroclinic vorticity production on unsteady drag coefficient in shock–particle interaction

The influence of baroclinic vorticity production on the unsteady drag coefficient in shock–particle interaction is numerically studied in this work. Numerical simulations are performed for shock–particle interaction utilizing a high–resolution axisymmetric solver for the Euler equations that allows for multi-material interface and shock propagation in both the particle and surrounding medium. We consider an aluminum particle in nitromethane and allow for particle deformation. We compute the vorticity production and unsteady drag coefficient as a function of time to explain the complex physical mechanisms that occur during shock–particle interaction. We observe baroclinic vorticity production as the shock propagates over the particle and find that the vorticity is primarily generated at the surface of the particle. After the passage of the shock over the particle, the generated vortex traverses downstream, thus creating a sharpened particle edge and low pressure on the downstream side of the particle, followed by the trapping of the vortex at the particle edge. These mechanisms lead to the generation of a quasi-steady drag force even after the passage of the shock, thus suggesting the importance of baroclinic vorticity production to the unsteady drag coefficient. Finally, we compute the unsteady drag coefficient for various shock Mach numbers and particle ellipticities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Pion interferometry at 200 GeV using anisotropic hydrodynamics

In this paper, we continue our phenomenological studies of heavy-ion collisions using 3 + 1 D anisotropic hydrodynamics (aHydro). In previous works, we compared quasiparticle aHydro (aHydroQP) with ALICE 2.76 TeV Pb-Pb and BNL Relativistic Heavy Ion Collider 200 GeV Au-Au collision results. At both energies, the agreement was quite good between aHydroQP and the experimental data for many observables. In this work, we present comparisons of the Hanbury Brown–Twiss (HBT) radii and their ratios determined using π + π + pairs produced in 200 GeV Au-Au collisions. We first present comparisons with STAR results for the HBT radii and their ratios. We then present comparisons with PHENIX results for the HBT radii and their ratios. In both cases, we find reasonable agreement between aHydroQP predictions and available experimental results for the ratios of HBT radii. At the level of the radii themselves, in some cases quantitative differences on the order of 10–20% remain, which deserve further research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Model investigation of the longitudinal broadening of the transverse momentum two-particle correlator

Here, the multiphase transport model is used to investigate the longitudinal broadening of the transverse momentum two-particle correlator C 2 (Δη,Δφ), and its utility to extract the specific shear viscosity, η/s, of the quark-gluon plasma formed in ultrarelativistic heavy ion collisions. The results from these model studies indicate that the longitudinal broadening of C 2 (Δη,Δφ) is sensitive to the value of η/s. However, reliable extraction of the longitudinal broadening of the correlator requires the suppression of possible self-correlations associated with the definition of the collision centrality.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Large baryon densities achievable in high-energy heavy-ion collisions outside the central rapidity region

Nuclei are nearly transparent to each other when they collide at high energy, but the collisions do produce high-energy density matter in the central rapidity region where most experimental measurements are made. What happens to the receding nuclear fireballs? We calculate the energy loss of the nuclei using the color glass condensate model. We then use a simple space-time picture of the collision to calculate the baryon and energy densities of the receding fireballs. For central collisions of large nuclei at the BNL Relativistic Heavy Ion Collider and the CERN Large Hadron Collider we find baryon densities more than ten times that of normal nuclear matter. Furthermore, these results provide initial conditions for subsequent hydrodynamic evolution and could test the equation of state at very high baryon densities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2012

Motion Imagery and Robotics Application (MIRA): Standards-Based Robotics

This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets. The innovation developed under this program provides a simulation tool that combines modeling of the diverse disciplines of rocket plume impingement gas dynamics, granular soil material liberation, and soil debris particle kinetics into one unified simulation system. The Unified Flow Solver (UFS) developed by CFDRC enabled the efficient, seamless simulation of mixed continuum and rarefied rocket plume flow utilizing a novel direct numerical simulation technique of the Boltzmann gas dynamics equation. The characteristics of the soil granular material response and modeling of the erosion and liberation processes were enabled through novel first principle-based granular mechanics models developed by the University of Florida specifically for the highly irregularly shaped and cohesive lunar regolith material. These tools were integrated into a unique simulation system that accounts for all relevant physics aspects: (1) Modeling of spacecraft rocket plume impingement flow under lunar vacuum environment resulting in a mixed continuum and rarefied flow; (2) Modeling of lunar soil characteristics to capture soil-specific effects of particle size and shape composition, soil layer cohesion and granular flow physics; and (3) Accurate tracking of soil-borne debris particles beginning with aerodynamically driven motion inside the plume to purely ballistic motion in lunar far field conditions.

Martinez, Lindolfo↗
NASA NTRS2007

On Flow Stagnation in a Tube Radiator

An analysis of the physical process for occurrence of flow stagnation in a space tube-radiator is performed and the mechanism and mathematic description for the flow stagnation are presented. Two causes for pressure drop unbalance between tubes of the radiator are identified: non-uniform cooling environment and different local flow resistances between the tubes. This analysis provides a theoretical basis for experimental simulations of the flow stagnation in a ground-based lab as well as two suggested methods to experimentally simulate flow stagnation. Criteria for the flow stagnation, depending on the viscosity data regressive polynomial, are derived from the extreme condition of the pressure drop in colder tubes. A preliminary numerical calculation is conducted for a space tube-radiator model which confirms the physical and mathematical analyses. The prediction by the criteria for flow stagnation in the tube-radiator model coincides with the numerical calculation result.

Motil, Brian↗
NASA NTRS2014

What Was Learned in Predicting Slender Airframe Aerodynamics with the F16-XL Aircraft

The CAWAPI-2 coordinated project has been underway to improve CFD predictions of slender airframe aerodynamics. The work is focused on two flow conditions and leverages a unique flight data set obtained with the F-16XL aircraft for comparison and verification. These conditions, a low-speed high angle-of-attack case and a transonic low angle-of-attack case, were selected from a prior prediction campaign wherein the CFD failed to provide acceptable results. In re-visiting these two cases, approaches for improved results include better, denser grids using more grid adaptation to local flow features as well as unsteady higher-fidelity physical modeling like hybrid RANS/URANS-LES methods. The work embodies predictions from multiple numerical formulations that are contributed from multiple organizations where some authors investigate other possible factors that could explain the discrepancies in agreement, e.g. effects due to deflected control surfaces during the flight tests, as well as static aeroelastic deflection of the outer wing. This paper presents the synthesis of all the results and findings and draws some conclusions that lead to an improved understanding of the underlying flow physics, and finally making the connections between the physics and aircraft features.

Rizzi, Arthur↗
NASA NTRS1943

Experimental Investigation of a Model of a Two-Stage Turboblower

In the present paper an investigation is made of two stages of a multistage turboblower having a vaneless diffuser behind the impeller and guide vanes at the inlet to the nest stage. The method employed was that of investigating the performance of the successive elements of the blower (the impeller, vaneless diffuser, ets.) whereby the kinematics of the flow through the blower could be followed and the pressure at the different points computed. The character of the flow and the physical significance of the loss coefficients could thereby be determined so as to secure the best agreement of the computed with the actual performance of the blower. Since the tests were carried out for various delivery volumes, the dependence of the coefficients on a number of factors (angle of attack, velocities, etc.) could be obtained. The distribution of the losses that occur during the transformation of dynamic pressure at the impeller exit into static pressure could be found and likewise the range within which the friction coefficient varies in the vaneless diffuser. With the aid of factors having a certain physical significance, the centrifugal blower could be computed on the basis of a more or less schematical consideration of the phenomena occuring during the air flow through it, and the use of arbitrary factors and recourse to the geometrical similtude law thus avoided. The present investigation largely summarizes all the previous work af the CHI Blower Section on the different elements of a centrifugal blower. Some considerations on the analysis of model test data for application to full-scale are presented in the appendix.

Dovjik, s.↗
DOE OSTI2017

Flowing liquid lithium plasma-facing components – Physics, technology and system analysis of the LiMIT system

The use of low atomic number liquid metals has been shown to have the potential to solve many of the prevalent problems like erosion and radiation losses associated with the interaction of fusion plasma with the plasma facing component (PFC) structures in tokamaks. Since the first evidence of lithium increasing plasma performance in TFTR [1], the benefits of using lithium in fusion environments have been seen in many devices, including CDX-U [2], NSTX [3], LTX [4], and DIII-D [5]. While both fast flow and slow flow concepts have been studied with regards to liquid lithium first wall alternatives, this report will focus on efforts placed on fast flow research and will mainly focus on advancements in the LiMIT device that help to eliminate concerns over the broad use of liquid lithium. Due to the promising TFTR results along with results obtained at the University of Illinois at Urbana-Champaign [6], suitably designed trench structures holding liquid lithium could be an appropriate fast flow candidate for PFC modules in future fusion devices. There are four potential shortcomings of this approach: (1) Droplet ejection, (2) Wetting control, (3) Tritium retention, and (4) Limited heat flux handling. Droplet ejection is discussed in a companion publication [7], while this paper addresses the topics of wetting control and heat flux handling. Limitations in wetting and prevention of lithium creep (i.e. getting and keeping the lithium only where it should be) have been solved by laser-texturing the base material with extreme short laser pulses (pico – femto second) of high power (several 10 s of W). Micro- and nano-structuring results indicate that the textured substrates displayed significant change in their wetting properties, increasing the temperature needed to wet from 310 °C to 390 °C. Lastly, initial designs for the Lithium Metal Infused Trenches (LiMIT) [6] showed dryout above 3 MW/m 2 , but new designs of the trench shaping show potential to be able to handle up to 10 MW/m 2 . Dryout is accompanied by lithium evaporation which is shown to mitigate the incident heat flux, which may be viewed as beneficial [8]. The advances shown here will increase the viability of the LiMIT system in large-scale testing, and allow for extensive design iteration to begin tackling the large powers and heat fluxes present in reactor-relevant systems.

36 MATERIALS SCIENCE↗
NASA NTRS2016

What Was Learned in Predicting Slender Airframe Aerodynamics with the F-16XL Aircraft

The second Cranked-Arrow Wing Aerodynamics Project, International, coordinated project has been underway to improve high-fidelity computational-fluid-dynamics predictions of slender airframe aerodynamics. The work is focused on two flow conditions and leverages a unique flight data set obtained with the F-16XL aircraft for comparison and validation. These conditions, a low-speed high-angle-of-attack case and a transonic low-angle-of-attack case, were selected from a prior prediction campaign wherein the computational fluid dynamics failed to provide acceptable results. In revisiting these two cases, approaches for improved results include better, denser grids using more grid adaptation to local flow features as well as unsteady higher-fidelity physical modeling like hybrid Reynolds-averaged Navier-Stokes/unsteady Reynolds-averaged Navier-Stokes/large-eddy simulation methods. The work embodies predictions from multiple numerical formulations that are contributed from multiple organizations where some authors investigate other possible factors that could explain the discrepancies in agreement (e.g., effects due to deflected control surfaces during the flight tests as well as static aeroelastic deflection of the outer wing). This paper presents the synthesis of all the results and findings and draws some conclusions that lead to an improved understanding of the underlying flow physics, finally making the connections between the physics and aircraft features.

Rizzi, Arthur↗
DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗
DOE OSTI2018

Modulating factors of hydrologic exchanges in a large-scale river reach: Insights from three-dimensional computational fluid dynamics simulations

Hyporheic exchange is a critical mechanism shaping hydrological and biogeochemical processes along a river corridor. Recent studies on quantifying the hyporheic exchange were mostly limited to local scales due to field inaccessibility, computational demand, and complexity of geomorphology and subsurface geology. Surface flow conditions and subsurface physical properties are well known factors on modulating the hyporheic exchange, but quantitative understanding of their impacts on the strength and direction of hyporheic exchanges at reach scales is absent. In this study, a high resolution computational fluid dynamics (CFD) model that couples surface and subsurface flow and transport is employed to simulate hyporheic exchanges in a 7-km long reach along the main-stem of the Columbia River. Assuming that the hyporheic exchange does not affect surface water flow conditions due to its negligible magnitude compared to the volume and velocity of river water, we developed a one-way coupled surface and subsurface water flow model using the commercial CFD software STAR-CCM+. The model integrates the Reynolds-averaged Navier-Stokes (RANS) equation solver with a realizable k-e two-layer turbulence model, a two-layer all y^+ wall treatment, and the volume of fluid (VOF) method, and is used to simulate hyporheic exchanges by tracking the free water-air interface as well as flow in the river and the subsurface porous media. The model is validated against measurements from acoustic Doppler current profiler (ADCP) in the stream water and hyporheic fluxes derived from a set of temperature profilers installed across the riverbed. The validated model is then employed to systematically investigate how hyporheic exchanges are influenced by surface water fluid dynamics strongly regulated by upstream dam operations, as well as subsurface structures (e.g. thickness of riverbed and subsurface formation layers) and hydrogeological properties (e.g. permeability). The results suggest that the thickness of riverbed alluvium layer is the dominant factor for reach-scale hyporheic exchanges, followed by the alluvium permeability, the depth of the underlying impermeable layer, and the assumption of hydrostatic pressure.

Bao, Jie↗
DOE OSTI2022

A gradient-based deep neural network model for simulating multiphase flow in porous media

We report simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO 2 storage sites, where CO 2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

42 ENGINEERING↗
NASA NTRS1987

Vibrational and rotational analysis of the emission spectra of the arc jet flow

Applying atomic and molecular physics to the analysis of the radiation emitted from the arc jet flow provides a means for determining the species and excitation temperature of the constituents of the flow. A rotational and vibrational analysis of the spectra obtained from the radiation emitted in the shock layer and in the free stream of the jet flow was performed, specifically, in the shock layer bands of the First Negative Group of ionized molecular nitrogen and in the free stream of the gamma-system of nitric oxide.

Blount, Charles E.↗
NASA NTRSDate not supplied

Acoustic Insights into Flow Condensation Mechanisms

Two-phase thermal management systems, with both boiling and condensation processes, offer great potential and heat transfer coefficients that are orders of magnitude higher than traditional single-phase systems. However, two-phase flows can suffer from a wide range of interfacial instabilities leading to significant thermal performance degradation. In this study, we aim to detect regime transitions and characterize dominating physical mechanisms of flow condensation, such as turbulent diffusion in annular liquid film and interfacial waves, using an integrated system of acoustic, modal, and optical sensing techniques and thermofluidic characterizations. A wideband acoustic emissions sensor and high-sensitivity accelerometer are utilized to capture acoustic and vibrational signatures that signal the onset of liquid film formation and interfacial waves during flow pattern transitions. Compared to optical imaging, wideband acoustic emission sensing allows for higher sampling rates to capture high-frequency interface oscillations critical to the flow regime transitions and works well even for condensation in opaque tubes. Acoustic features (e.g., amplitude, frequency, energy, duration) are correlated with thermofluidic processes (e.g., capillary flows, turbulent flows, boiling, condensation). By relating thermal performance metrics with these dynamic signatures in acoustic and modal regimes, we explore the ability to probe and monitor critical flow regime transitions and transport efficiency in flow condensation.

Acoustic Modal Regimes↗