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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Effect of Drag Model on Heatshield Recession due to Particle Impacts for Martian Spacecraft

A spacecraft entering the Martian atmosphere during a dust storm may experience recession to the heatshield due to dust particle impacts. Aerodynamic drag is the primary force that determines the trajectory of the dust particles through the shock layer. This paper examines the effect of particle drag model on the heatshield recession. Three particle drag models are assessed including two that are intended to be applicable over a wide range of particle flow conditions. Particle trajectories are computed in conditions measured during the 2007 major global dust storm. It was found that accounting for Knudsen number and compressibility effects made a large difference in the estimated particle impact velocity. The two drag models that were valid for transitional, compressible particle flow environments predicted only slightly-different amounts of heatshield recession due to dust particle impacts. A brief description of the effects of non-spherical particles on drag coefficients is provided.

Heatshield↗
NASA NTRSDate not supplied

The Effect of Drag Model on Heatshield Recession due to Particle Impacts for Martian Spacecraft

A spacecraft entering the Martian atmosphere during a dust storm may experience recession to the heatshield due to dust particle impacts. Aerodynamic drag is the primary force that determines the trajectory of the dust particles through the shock layer. This paper examines the effect of particle drag model on the heatshield recession. Three particle drag models are assessed including two that are intended to be applicable over a wide range of particle flow conditions. Particle trajectories are computed in conditions measured during the 2007 major global dust storm. It was found that accounting for Knudsen number and compressibility effects made a large difference in the estimated particle impact velocity. The two drag models that were valid for transitional, compressible particle flow environments predicted only slightly-different amounts of heatshield recession due to dust particle impacts. A brief description of the effects of non-spherical particles on drag coefficients is provided.

Heatshield↗
NASA NTRSDate not supplied

Assessment of Particle Drag Models Using L2K and GBK Experimental Data

Properly assessing the drag force is an important element to computing the trajectories of particles traveling through a shock layer. This study will use experimental data in the German Aerospace Center (DLR) L2K arcjet to evaluate the ability of various particle drag models to reproduce the experimental particle velocity data.

particle flows↗
NASA NTRS1989

Atmospheric drag model calibrations for spacecraft lifetime prediction

Although solar activity prediction uncertainty normally dominates decay prediction error budget for near-Earth spacecraft, the effect of drag force modeling errors for given levels of solar activity needs to be considered. Two atmospheric density models, the modified Harris-Priester model and the Jacchia-Roberts model, to reproduce the decay histories of the Solar Mesosphere Explorer (SME) and Solar Maximum Mission (SMM) spacecraft in the 490- to 540-kilometer altitude range were analyzed. Historical solar activity data were used in the input to the density computations. For each spacecraft and atmospheric model, a drag scaling adjustment factor was determined for a high-solar-activity year, such that the observed annual decay in the mean semimajor axis was reproduced by an averaged variation-of-parameters (VOP) orbit propagation. The SME (SMM) calibration was performed using calendar year 1983 (1982). The resulting calibration factors differ by 20 to 40 percent from the predictions of the prelaunch ballistic coefficients. The orbit propagations for each spacecraft were extended to the middle of 1988 using the calibrated drag models. For the Jaccia-Roberts density model, the observed decay in the mean semimajor axis of SME (SMM) over the 4.5-year (5.5-year) predictive period was reproduced to within 1.5 (4.4) percent. The corresponding figure for the Harris-Priester model was 8.6 (20.6) percent. Detailed results and conclusions regarding the importance of accurate drag force modeling for lifetime predictions are presented.

Binebrink, A. L.↗
DOE OSTI2021

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

Here, the accuracy of coarse-grained Euler-Lagrangian simulations of fluidized beds heavily depends on the mesoscale drag models to account for the influences of the unresolved sub-grid structures. Traditional filtered drag models are regressed with mesoscale markers such as voidage and slip velocities. In this research, a filtered drag was regressed with both mesoscale and macro-scale markers using fine grid Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations. The traditional non-linear regression method was compared with machine learning regression using an Artificial Neural Network (ANN) implemented in PyTorch and coupled with MFiX. The new drag showed higher accuracy than the Wen-Yu drag and another filtered drag derived from the two-fluid model. The nonlinear regression shows slightly better results than ANN regression in cases with similar R 2 values. The utilization of the gas inlet velocity as an additional macro-scale marker reduced the errors by up to 55.3% in the tested cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Assessment of Particle Drag Models Using GBK Experimental Data

Developing a simulation capability to model dust-laden flows requires the ability to accurately predict the velocity of a particle as it travels through a shock layer, nozzle plume, or the flow of an experimental facility. The primary mechanism that determines the particle velocity is the drag force acting on the particle. The drag force is typically expressed in terms of the frontal area of the particle, its velocity relative to the surrounding fluid, the density of the surrounding fluid, and a non-dimensional drag coefficient. As part of the ESM project, an integrated CFD-particle trajectory code named US3D-DUST is being developed]. This code uses a Lagrangian-based framework that computes the trajectories of individual particles in the flow. Several of the most commonly-used spherical drag models have been implemented in US3D-DUST. In this study, the US3D-DUST code will be used to simulate particle flows in the GBK facility. Differences in particle velocities predicted using the different drag models will be compared against recent GBK data

Dusty flow↗
DOE OSTI2025

Development and Evaluation of a General Drag Model for Gas-Solid Flows via Deep Learning

This project presents the development and evaluation of a general drag model for gas–solid multiphase flows using deep learning techniques. A comprehensive database of more than 4,000 experimental and numerical data points for spherical and non spherical particles was compiled, incorporating geometric features such as sphericity, aspect ratio, and orientation. Several predictive approaches—including traditional em pirical correlations, machine learning, and deep neural networks—were benchmarked, with the proposed Drag Coefficient Correlation-aided Deep Neural Network (DCC DNN) demonstrating superior accuracy. To account for particle–particle interactions, additional drag data were generated using CFD-based simulations of packed and flu idized beds, leading to the development of a retrained model capable of incorporat ing volume fraction effects. Integration of the trained model with the MFiX CFD solver was achieved using FTorch, enabling drag predictions during discrete element method (DEM) simulations. Validation against experimental data for single particles and fluidized beds confirmed the model’s improved predictive ability, particularly for non-spherical geometries. While the model performed strongly under fluidized con ditions, limitations remained in unfluidized regimes, suggesting a need for expanded datasets. Overall, this study demonstrates the feasibility of combining deep learning with physics-informed CFD to improve drag modeling for gas–solid flows, with promis ing implications for scaling multiphase simulations in industrial applications.

42 ENGINEERING↗
DOE OSTI2020

An Assessment of the Drag Models in the Case of a Shock Interacting With a Fixed Bed of Point Particles

Abstract In this work, three-dimensional Euler–Lagrange (EL) point-particle simulations of a shock wave interacting with a fixed bed of particles are carried out. The results from the particle-resolved (PR) simulations are used to assess the performance of the point-particle drag models during short time scales. We demonstrate that in a one-way coupled regime, the point-particle simulations recover the dominant gas dynamic features of the flow and are in a good agreement with the exact Riemann solution of a shock traveling through a sudden area contraction. Although the PR simulations are inviscid, we show that a dissipative drag is necessary to predict the mean behavior of the gas. As a model for the inviscid shock-induced (SI) drag two different models are presented in lieu of the quasi-steady drag. Finally, two-way coupled simulations are performed at four different particle volume fractions {0.10, 0.15, 0.20, 0.25} and three different incident shock Mach numbers {1.22, 1.66, 3.0} and compared against the data from PR inviscid simulations. At a lower Mach number (1.22), averaged flow quantities from the two-way coupled simulations agree well with the PR simulations. As the Mach number increases, we observe that the discrepancies between the point-particle and the PR simulations grow. A sensitivity analysis of the drag models involved reveals a strong influence of the inviscid-unsteady force on the gas quantities especially in the case of a strong shock interacting with a dense bed of particles. The use of Mach correlation beyond the subcritical regime coupled with the model for volume fraction correction is identified as a probable cause for the additional drag.

Engineering↗
NASA NTRS2006

Atmospheric drag model for Cassini orbit determination during low altitude Titan flybys

On April 16, 2005, the Cassini spacecraft performed its lowest altitude flyby of Titan to date, the Titan-5 flyby, flying 1027 km above the surface of Titan. This document discusses the development of a Titan atmospheric drag model for the purpose of the orbit determination of Cassini. Results will be presented for the Titan A flyby, the Titan-5 flyby as well as the most recent low altitude Titan flyby, Titan-7. Different solutions will be compared against OD performance in terms of the flyby B-plane parameters, spacecraft thrusting activity and drag estimates. These low altitude Titan flybys were an excellent opportunity to observe the effect of Titan's atmospheric drag on the orbit determination solution and results show that the drag was successfully modeled to provide accurate flyby solutions.

orbit determination↗
DOE OSTI2025

Developing Drag Models for Non-Spherical Particles through Machine Learning

The overarching goal of this project is to produce comprehensive experimental and numerical datasets for gas-solid flows in well-controlled settings to understand the aerodynamic drag of non-spherical particles in the dense regime. The datasets and the gained knowledge will be utilized to train deep neural networks in TensorFlow to formulate a general drag model for use directly in NETL MFiX-DEM module in order to help to advance the accuracy and prediction fidelity of the computational tools that will be used in designing and optimizing fluidized beds and chemical looping reactors.

42 ENGINEERING↗
DOE OSTI2022

CTF Improved Drag Model and Flow Regime Transition Criteria

The demand for accurate prediction of two-phase flow behavior in a boiling water reactor (BWR) requires a comprehensive understanding of flow regime, void fraction, heat transfer, and pressure drop. The CTF subchannel code, which is used for the Thermal/Hydraulic (T/H) solution in the Consortium for Advanced Simulation of Light Water Reactors (CASL)-developed Virtual Environment for Reactor Application (VERA) core simulator, is being further developed for BWR applications. In support of this goal, the present work highlights some of the two-phase closure model developments towards improving the CTF void fraction prediction, especially for subcooled boiling. The drift-flux approach has been well-developed for upward dispersed two-phase flows and proven to be accurate in predicting void fraction in bubbly and slug flow regimes. In this work, these kinematic constitutive relations for the drift-flux velocity have been implemented into CTF to describe the interfacial drag of bubbly flow as an alternative to the existing model for better void fraction prediction. The success of these constitutive relations also relies on a good flow regime map that accounts for flow conditions and channel geometry. A more reliable flow regime transition criteria that account for the flow condition has also been implemented in this study for modeling the flow regime transition criteria. The newly implemented models are shown to give improved void fraction predictions in comparison to experimental data.

Hizoum, Belgacem↗
DOE OSTI2020

Lagrangian and Eulerian drag models that are consistent between Euler-Lagrange and Euler-Euler (two-fluid) approaches for homogeneous systems

The undisturbed flow of a particle is of fundamental importance since it controls both the undisturbed flow force and the perturbation force (which includes quasisteady, added-mass, and history forces). Here we use the pairwise interaction extended point particle framework to evaluate the undisturbed flow of each particle through superposition of the perturbation flow induced by all its neighbors. This approach allows calculation of various statistics related to undisturbed fluid velocity under conditions of both stationary and nonstationary particles. In a random distribution of stationary particles, while the macroscale undisturbed flow is slowly varying, the microscale undisturbed flow that arises due to the perturbation flow of neighbors varies substantially from one particle to another and this in turn leads to large variation in the hydrodynamic force exerted on the particles. The effect of particle motion is generally to increase the particle-to-particle variation in the undisturbed fluid velocity of the particles. We observe that this increase is greater for the transverse component than for the streamwise component. As a result, with increasing random particle motion, the distribution of undisturbed fluid-velocity fluctuation becomes isotropic. Three different normalized forces are defined: $Φ^L$ is the Lagrangian normalized force on an individual particle suitable for application in a microscale-informed Euler-Lagrange simulation, $Φ^E$ is the Eulerian normalized average force suitable for application in an Euler-Euler simulation, and $Φ^{LE}$ is the Lagrangian normalized force on an individual particle suitable for application in the standard Euler-Lagrange simulation. In this work, we establish precise relations between these different definitions. The drag laws developed based on particle-resolved direct numerical simulation results and experiments are appropriate for application only as the Eulerian normalized average force. We introduce the force consistency relation and use it to obtain an expression for $Φ^L$, which when applied to each particle and averaged over all the particles equals $Φ^E$. The results are first obtained in the limit of stationary particles and then extended to the general case of nonstationary particles.

42 ENGINEERING↗
NASA NTRS2010

Parachute Drag Model

DTV-SIM is a computer program that implements a mathematical model of the flight dynamics of a missile-shaped drop test vehicle (DTV) equipped with a multistage parachute system that includes two simultaneously deployed drogue parachutes and three main parachutes deployed subsequently and simultaneously by use of pilot parachutes. DTV-SIM was written to support air-drop tests of the DTV/parachute system, which serves a simplified prototype of a proposed crew capsule/parachute landing system.

Cuthbert, Peter↗