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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Framework for idealized climate simulations with spatiotemporal stochastic clouds and planetary-scale circulations

In climate predictions, clouds are the leading source of uncertainty. This is partly because, to simulate the fluid dynamics of climate over the entire globe, a large grid spacing must be used, so clouds are a subgrid-scale parametrization rather than a resolved feature. Here, a framework is investigated with finer grid spacing of O(1) or O(10)km so that some clouds are not subgrid-scale; instead, clouds evolve on the numerical grid. This cloud evolution is achieved using stochastic modeling. Hence, the framework is idealized in the sense that the full fluid dynamics of cloud circulations is still not resolved, and simplified vertical structures are used. Nevertheless, the fluid dynamics model includes evolving clouds that interactively adjust in size, shape, lifetime, and regional coverage. In addition, different cloud types are included with different roles in the climate system, including deep convective clouds and also boundary-layer clouds such as shallow cumulus and stratocumulus clouds. Other basic aspects of the idealized climate system are planetary-scale circulations (e.g., Walker circulation) and radiation. With these ingredients (evolving clouds, planetary-scale circulations, and radiation), the framework has the potential for idealized investigations of climate change with interactive cloud–radiative feedback of individual clouds. Here, the formulation of the model equations is presented, and numerical simulations are shown to illustrate the model dynamics and climate change.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2005

Simulation and Analyses of Stage Separation Two-Stage Reusable Launch Vehicles

NASA has initiated the development of methodologies, techniques and tools needed for analysis and simulation of stage separation of next generation reusable launch vehicles. As a part of this activity, ConSep simulation tool is being developed which is a MATLAB-based front-and-back-end to the commercially available ADAMS(registered Trademark) solver, an industry standard package for solving multi-body dynamic problems. This paper discusses the application of ConSep to the simulation and analysis of staging maneuvers of two-stage-to-orbit (TSTO) Bimese reusable launch vehicles, one staging at Mach 3 and the other at Mach 6. The proximity and isolated aerodynamic database were assembled using the data from wind tunnel tests conducted at NASA Langley Research Center. The effects of parametric variations in mass, inertia, flight path angle, altitude from their nominal values at staging were evaluated. Monte Carlo runs were performed for Mach 3 staging to evaluate the sensitivity to uncertainties in aerodynamic coefficients.

Pamadi, Bandu N.↗
NASA NTRS2007

Simulation and Analyses of Stage Separation of Two-Stage Reusable Launch Vehicles

NASA has initiated the development of methodologies, techniques and tools needed for analysis and simulation of stage separation of next generation reusable launch vehicles. As a part of this activity, ConSep simulation tool is being developed which is a MATLAB-based front-and-back-end to the commercially available ADAMS(Registerd TradeMark) solver, an industry standard package for solving multi-body dynamic problems. This paper discusses the application of ConSep to the simulation and analysis of staging maneuvers of two-stage-to-orbit (TSTO) Bimese reusable launch vehicles, one staging at Mach 3 and the other at Mach 6. The proximity and isolated aerodynamic database were assembled using the data from wind tunnel tests conducted at NASA Langley Research Center. The effects of parametric variations in mass, inertia, flight path angle, altitude from their nominal values at staging were evaluated. Monte Carlo runs were performed for Mach 3 staging to evaluate the sensitivity to uncertainties in aerodynamic coefficients.

Pamadi, Bandu N.↗
NASA NTRS1995

EWB: The Environment WorkBench Version 4.0

The Environment WorkBench EWB is a desktop integrated analysis tool for studying a spacecraft's interactions with its environment. Over 100 environment and analysis models are integrated into the menu-based tool. EWB, which was developed for and under the guidance of the NASA Lewis Research Center, is built atop the Module Integrator and Rule-based Intelligent Analytic Database (MIRIAD) architecture. This allows every module in EWB to communicate information to other modules in a transparent manner from the user's point of view. It removes the tedious and error-prone steps of entering data by hand from one model to another. EWB runs under UNIX operating systems (SGI and SUN workstations) and under MS Windows (3.x, 95, and NT) operating systems. MIRIAD, the unique software that makes up the core of EWB, provides the flexibility to easily modify old models and incorporate new ones as user needs change. The MIRIAD approach separates the computer assisted engineering (CAE) tool into three distinct units: 1) A modern graphical user interface to present information; 2) A data dictionary interpreter to coordinate analysis; and 3) A database for storing system designs and analysis results. The user interface is externally programmable through ASCII data files, which contain the location and type of information to be displayed on the screen. This approach provides great flexibility in tailoring the look and feel of the code to individual user needs. MIRIADbased applications, such as EWB, have utilities for viewing tabulated parametric study data, XY line plots, contour plots, and three-dimensional plots of contour data and system geometries. In addition, a Monte Carlo facility is provided to allow statistical assessments (including uncertainties) in models or data.

Source record↗
DOE OSTI2025

Analysis of the HAE activity in the TJ-II stellarator using a Landau closure model

The aim of this study is to analyze the stability of helical Alfvén eigenmodes (HAEs) in TJ-II discharges and the stabilizing effect of the energetic particles generated by the neutral beam injector (NBI) on pressure gradient-driven modes (PGDMs). HAE and PGDM stability is studied using the linear version of the gyro-fluid code FAR3d and the continuous structure by the STELLGAP code. First, Alfvén eigenmode (AE) and PGDM activity observed in the experiments is reproduced by the simulations, identifying unstable m/n = 4/7 − 2/3 and 7/12 − 5/8 HAEs triggered around ρ = 0.66 showing a frequency of 209 and 204 kHz, respectively, as well as 5/3 PGDM. Next, a parametric study is performed with respect to the thermal ion density and iota profile in the middle-outer plasma region to verify the robustness of the simulation results with respect to the uncertainty of experimental profiles. The analysis confirms that experimental uncertainty does not cause large deviations in the simulation results, showing the destabilization of the same HAEs for all the configurations tested. The simulations also indicate the decay of the 5/3 PGDM growth rate as the energetic particle (EP) population in the plasma increases, consistent with the experiment. Stability analysis of the n = 3, 7, 11, n = 5, 9, 13, n = 6, 10, 14, and n = 8, 12 helical families is performed with respect to the NBI operational regime for different EP energies, β as well as deposition profiles. The most unstable configuration is the radially localized on-axis NBI operation (stiff EP density profile gradients nearby the magnetic axis). Using the simulation model that reproduces the observed Alfvén activity, we extend the study to analyze NBI performance within a theoretical framework. It shows that increasing NBI voltage (which raises EP energy) leads to a degradation in NBI performance for a given power (related to EP β and their density). To achieve better NBI operation, higher voltage must be balanced with lower injection power, ensuring stable AEs while keeping the same EP β.

Plasma confinement↗
DOE OSTI2026

Pion and kaon PDFs from lattice QCD via large momentum effective theory and short-distance factorization

In this paper, we present a first-principles lattice-QCD calculation of the unpolarized quark PDF for the pion and the kaon. The lattice data rely on matrix elements calculated for boosted mesons coupled to non-local operators containing a Wilson line. The calculations on this lattice ensemble correspond to two degenerate light, a strange, and a charm quark (𝑁 𝑓 = 2 + 1 + 1), using maximally twisted mass fermions with a clover term. The lattice volume is 32 3 × 64, with a lattice spacing of 0.0934 fm, and a pion mass of 260 MeV. Matrix elements are calculated for hadron boosts of |𝑃 3 | = 0, 0.41, 0.83, 1.25, 1.66, and 2.07 GeV. To match lattice QCD results to their light-cone counterparts, we employ two complementary frameworks: the large-momentum effective theory (LaMET) and the short-distance factorization (SDF). Using these approaches in parallel, we also test the lattice data to identify methodology-driven systematics. Results are presented for the standard quark PDFs, as well as the valence sector. Beyond obtaining the PDFs, we also explore the possibility of extracting information on SU(3) flavor-symmetry-breaking effects. For LaMET, we also parametrize the momentum dependence to obtain the infinite-momentum PDFs. Since the present calculation is performed on a single ensemble at a pion mass of 260 MeV and fixed lattice spacing, the uncertainties reported are statistical only, and systematic uncertainties remain to be addressed in future multi-ensemble studies.

Miller, Joshua [Temple University, Philadelphia, P↗
NASA NTRS2019

Blind Validation Study of Parametric Cost Estimation Tool SEER-H for NASA Space Missions

One of the primary parametric cost modeling tools used by NASA and the aerospace industry to estimate the development and production cost of future spacecraft hardware is SEER-H by Galorath. To date, no independent validation of this tool for cost estimation of space missions has been reported in the literature. In the present validation study, cost estimators used SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. The point estimates of SEER-H had an average error of 23%, median error of -0.3%, and a standard deviation of 43%. Nine of the twelve mission's actual costs fell within the 80% confidence interval of SEER's probabilistic estimates. Several factors independent of SEER that may have affected the accuracy of the results have been identified and are discussed; these include: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

SEER-H↗
DOE OSTI2022

DUNE atmospheric neutrinos: Earth tomography

In this paper we show that the DUNE experiment can measure the Earth’s density profile by analyzing atmospheric neutrino oscillations. The crucial feature that enables such measurement is the detailed event reconstruction capability of liquid argon time projection chambers. This allows for studying the sub-GeV atmospheric neutrino component, which bears a rich oscillation phenomenology, strongly dependent on the matter potential sourced by the Earth. We provide a pedagogical discussion of the MSW and parametric resonances and their role in measuring the core and mantle densities. By performing a detailed simulation, accounting for particle reconstruction at DUNE, nuclear physics effects relevant to neutrino-argon interactions and several uncertainties on the atmospheric neutrino flux, we manage to obtain a robust estimate of DUNE’s sensitivity to the Earth matter profile. We find that DUNE can measure the total mass of the Earth at 9.3% precision with an exposure of 400 kton-year. By accounting for previous measurements of the total mass and moment of inertia of the Earth, the core, lower mantle and upper mantle densities can be determined with 9%, 14% and 22% precision, respectively, for the same exposure. Finally, for a low exposure run of 60 kton-year, which would correspond to two far detectors running for three years, we have found that the core density could be measured by DUNE at ∼ 30% precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1988

A gamma ray observatory ground attitude error analysis study using the generalized calibration system

The Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) will be responsible for performing ground attitude determination for Gamma Ray Observatory (GRO) support. The study reported in this paper provides the FDD and the GRO project with ground attitude determination error information and illustrates several uses of the Generalized Calibration System (GCS). GCS, an institutional software tool in the FDD, automates the computation of the expected attitude determination uncertainty that a spacecraft will encounter during its mission. The GRO project is particularly interested in the uncertainty in the attitude determination using Sun sensors and a magnetometer when both star trackers are inoperable. In order to examine the expected attitude errors for GRO, a systematic approach was developed including various parametric studies. The approach identifies pertinent parameters and combines them to form a matrix of test runs in GCS. This matrix formed the basis for this study.

Ketchum, E.↗
DOE OSTI2026

Quantifying uncertainty in physics-based predictions of rare-isotope production cross sections via Bayesian-inspired model averaging across nuclear mass tables

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction models and phenomenological cross-section parametrizations often exhibit significant deviations over broad regions of mass and charge. In this work, a Bayesian-inspired model-averaging framework is developed to combine abrasion-ablation (AA) calculations based on multiple nuclear mass tables into a single statistically weighted estimate. For the calibrated systems, the model weights are assigned empirically according to the relative quality of fit to measured cross sections, thereby reducing systematic model bias while preserving the underlying physics content of the AA description. The weights are constrained using proton-rich fragmentation data for the 78 Kr and 124 Xe projectiles. The resulting parameter trends are then propagated to the 92 Mo and 144 Sm systems through a controlled scaling procedure. In the present implementation, the excitation-energy prescription is fixed, while the averaging is performed across nuclear-mass inputs; the framework provides both weighted cross sections and associated uncertainty estimates. Applied to proton-rich fragmentation, the present approach provides a practical basis for interpolation and limited extrapolation in regions relevant to rare-isotope production. The resulting predictions are used to assess the production of very proton-rich nuclei, and candidate new isotopes are discussed.

Bayesian methods↗
NASA NTRS1992

Generalized probability model for calculation of interference to the Deep Space Network due to circularly Earth-orbiting satellites

The probability of exceeding interference power levels and the duration of interference at the Deep Space Network (DSN) antenna is calculated parametrically when the state vector of an Earth-orbiting satellite over the DSN station view area is not known. A conditional probability distribution function is derived, transformed, and then convolved with the interference signal uncertainties to yield the probability distribution of interference at any given instant during the orbiter's mission period. The analysis is applicable to orbiting satellites having circular orbits with known altitude and inclination angle.

Ruggier, C. J.↗
NASA NTRS2024

Tail-Cone Thruster Fan Rotor Flutter Analysis

The aeroelastic stability of a tail cone thruster fan was analyzed for three structural modes and various nodal diameter patterns. Computational fluid dynamics modeling with blade vibrations was used in the analyses performed at design (peak-efficiency) and two near-stall conditions at the design rotational speed. Aerodynamic damping was used to assess flutter since this integrally bladed rotor design will have minimal structural damping. Aerodynamic damping was found to be low at the design condition. For the first mode, aerodynamic damping was seen to decrease towards stall, vanishing for a zero nodal diameter pattern. Further decrease in mass flow led to negative aerodynamic damping (flutter) for the first and second nodal diameters in the near stall condition. The flowfield at this lowest mass flow rate exhibited some additional unsteadiness at higher frequency. The sensitivity of results to time step and amplitudes of vibration was examined and found to be very satisfactory. The largest uncertainty in the results comes from the observed sensitivity of the aerodynamic damping to details of the variation of grid deformations in the blade passage mesh from the blade passage to the boundaries. For the parametric variations analyzed, the calculated aerodynamic damping is lower if the grid deformations near the blade surface are higher. Further work is needed to understand the cause of this sensitivity and find possible solutions to reduce the effects on flutter predictions.

Fan↗
DOE OSTI2022

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗
DOE OSTI2023

Decoding Zeolite Crystallization and Stage III in Nuclear Waste Glasses by Coupled Modeling and Experiments

Under specific conditions of pH and temperature, nuclear waste immobilization borosilicate glasses may exhibit a sudden acceleration in their corrosion kinetics (stage III)—a behavior that has been associated with the formation of zeolite crystals. Such accelerated dissolution may compromise the integrity of nuclear wasteforms placed in geological depositories. However, thus far, none of the available models is able to predict the thermodynamic propensity and kinetics of zeolite precipitation as a function of the solution conditions due to (i) a lack of fundamental knowledge regarding the nucleation & growth mechanisms of zeolitic phases, (ii) uncertainty regarding the compositions (types) of zeolites that may form and the rate-limiting step in their precipitation as a function of the solution conditions, and (iii) the complexities that arise due to the vast parametric space (i.e., solution chemistry, temperature, number of secondary phases, etc.) that encompass these systems under conditions of environmental exposure. To resolve these challenges, this project aimed to unambiguously identify the thermodynamic propensity for zeolite precipitation and the kinetics thereof as a function of the solution conditions (composition, pH, and temperature). To achieve this goal: 1) We identified the solution conditions and zeolite phases relevant to nuclear glass dissolution. 2) We performed a series of ab initio molecular dynamics (AIMD) simulations to compute the thermodynamic properties of a group of characteristic zeolites that features a large range of compositions, various hydration levels, a wide range of framework structures, and partial atomic site occupancies. 3) We released a first-of-a-kind self-consistent thermodynamic database that can be used to assess the kinetics and the stability fields of zeolitic phases within a Gibbs energy minimization (GEM) framework. 4) We developed a robust geochemical modeling method allowing us to predict the stability of secondary phases (including zeolites, calcium–silicate–hydrate gels, and clays) upon the dissolution of nuclear waste immobilization glasses. 5) We introduced a model that predicts the dissolution kinetics of a series of borosilicate nuclear waste immobilization glasses in terms of the topology of their atomic network. 6) We investigated the roles of the solution composition on the crystallization kinetics of phillipsite zeolites and tobermorite silicate hydrates. Via PNNL’s collaboration and engagement, this project directly supports DOE’s nuclear waste immobilization activities by offering a technical, science-based foundation that will (i) facilitate predictions of the long-term corrosion rates and extents of existing nuclear waste immobilization glasses to help ensure safe and successful vitrification operations, (ii) inform the development of advanced glass formulations with enhanced durability, and, (iii) enable cost-savings that result from making more decisive and hence less conservative predictions while offering higher levels of nuclear waste embedment in smaller, more compact glass volumes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2014

Supersonic Retropropulsion Test 1853 in NASA LaRC Unitary Plan Wind Tunnel Test Section 2

A supersonic retropropulsion experiment was conducted in the Langley Research Center Unitary Plan Wind Tunnel Test Section 2 at Mach numbers of 2.4, 3.5, and 4.6. Intended as a code validation effort, this study used pretest computations to size and refine the model such that tunnel blockage and internal flow separations were minimized. A 5-in diameter 70 degree sphere-cone forebody, which can accommodate up to four 4:1 area ratio nozzles, followed by a 9.55 inches long cylindrical aft body was selected for this test after computational maturation. The primary measurements for this experiment were high spatial-density surface pressures. In addition, high speed schlieren video and internal pressures and temperatures were acquired. The test included parametric variations in the number of nozzles utilized, thrust coefficients (roughly 0 to 4), and angles of attack (-8 to 20 degrees). The run matrix was developed to also allow quantification of various sources of experimental uncertainty, such as random errors due to run-to-run variations and systematic errors due to flowfield or model misalignments. To accommodate the uncertainty assessment, many runs and replicates were conducted with the model at various locations within the tunnel and with model roll angles of 0, 60, 120, and 180 degrees. This test report provides operational details of the experiment, contains a review of trends, and provides all schlieren and pressure results within appendices.

Berry, Scott A.↗
NASA NTRSDate not supplied

Delta Method Application for the Correlation of IR Detector Thermal Parasitic Loads with Statistically Accurate Results

The Linear Etalon Imaging Spectral Array (LEISA) is a cryogenic IR detector that is passively cooled below 110K. LEISA is part of the L’Ralph instrument, which is going on the Lucy mission, with planned flyby’s of the Trojan asteroids around 5.5 AU. One of the primary thermal challenges is to successfully quantify each significant parasitic heat flow value with statistical certainty.Simulation of flight-like thermal environments and correlation of thermal models is an important part of this challenge, which can be critical for thermally sensitive systems such as cryogenic detectors that are passively cooled. It is common practice during TVAC to achieve several thermal balance points and then to correlate several design variables in order to achieve the closest match to all balance points tested. This approach lends itself to high levels of uncertainty in the correlated values due to the cumulative effect of absolute temperature uncertainty and differences between the sensors used for the measurement. Accuracy can be improved with the use of more accurate sensors, by calibrating all sensors with respect to each other, and by using Zero-Q methodologies, all of which add cost and complexity to the test.The Delta Method uses the difference in temperature caused by the changes in the boundary conditions to calculate heat flows and/or thermal resistances across temperature differentials. This eliminates the problem of high uncertainties with absolute temperature measurements, and yields statistically accurate results down to the sensor resolution of 1mK at < 100K, by taking the sensor’s calibration errors out of the equation. During testing, this method relies on parametric variations around an initial balance point, by varying the boundary conditions of the different parasitic heat sources. The Delta Method, as well as its application on the LEISA thermal test, will be discussed in detail.

Daniel G. Bae↗
DOE OSTI2021

Flow-driven spectral chaos (FSC) method for simulating long-time dynamics of arbitrary-order non-linear stochastic dynamical systems

Uncertainty quantification techniques such as the time-dependent generalized polynomial chaos (TD-gPC) use an adaptive orthogonal basis to better represent the stochastic part of the solution space (aka random function space) in time. However, because the random function space is constructed using tensor products, TD-gPC-based methods are known to suffer from the curse of dimensionality. Here, we introduce a new numerical method called the flow-driven spectral chaos (FSC) which overcomes this curse of dimensionality at the random-function-space level. The proposed method is not only computationally more efficient than existing TD-gPC-based methods but is also far more accurate. The FSC method uses the concept of enriched stochastic flow maps to track the evolution of a finite-dimensional random function space efficiently in time. To transfer the probability information from one random function space to another, two approaches are developed and studied herein. In the first approach, the probability information is transferred in the mean-square sense, whereas in the second approach the transfer is done exactly using a new theorem that was developed for this purpose. The FSC method can quantify uncertainties with high fidelity, especially for the long-time response of stochastic dynamical systems governed by ODEs of arbitrary order. Six representative numerical examples, including a nonlinear problem (the Van-der-Pol oscillator), are presented to demonstrate the performance of the FSC method and corroborate the claims of its superior numerical properties. Finally, a parametric, high-dimensional stochastic problem is used to demonstrate that when the FSC method is used in conjunction with Monte Carlo integration, the curse of dimensionality can be overcome altogether.

(nonlinear) stochastic dynamical systems↗
DOE OSTI2021

Joint Bayesian Inference for Near-Surface Explosion Yield and Height-of-Burst

Forensic capabilities to understand chemical and nuclear explosions are greatly aided by an accurate estimate of explosive yield with uncertainty. The relationship between explosive size and geophysical observations of seismic, acoustic, and optical waves can be exploited to provide an estimate of yield. Any near-surface yield estimate is complicated by the surface interaction, so an estimate for the explosion height-of-burst is necessarily included in the relationship. Additionally, the relationship dictates a trade-off between estimates of yield and height-of-burst. Fortunately, the surface interaction for each type of observation is different, which breaks the trade-off, and the inclusion of height-of-burst with multiple data types improves yield estimation. We define simple parametric forward models to relate seismoäcoustoöptic observations from a data set of known explosive yields and height-of-bursts. The parameters of the models and a prediction for the yield and height-of-burst of a new event can then be estimated given new observations via Bayesian inference. We report posterior distribution estimates of the parametric models using a Markov chain Monte Carlo sampling technique. These models are then used to predict the yield and height-of-burst of SUGAR, a historical near-surface nuclear explosion, using its reported historical observations. The reported yield of 1.2 ktonne Trinitrotoluene (TNT)-equivalent (Department of Energy, 2015) is within the estimated posterior. Yield uncertainty can be estimated from the spread of the posterior, which is between 0.9 and 2.1 ktonne TNT-equivalent. The posterior for height-of-burst has a wider range between 10 m below and 8 m above ground that includes the true height-of-burst of 1 m.

58 GEOSCIENCES↗