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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Random Forests to Predict Rectal Toxicity Following Prostate Cancer Radiation Therapy

Purpose: To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models. Methods and Materials: Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression model was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC). Results: The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69. Conclusions: The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Impact of hydrate saturation on water permeability in hydrate-bearing sediments

Permeability of the hydrate-bearing sediments vitally affects the hydrate dissociation process as well as the rate and efficiency of gas production. Reported permeability values are observed to be widely are very scattered owing to the dependence on multiple factors such as experimental conditions and test procedures. It is critical that the permeability is measured accurately to enable prediction of long-term gas production using numerical simulation for an economic development of hydrate-bearing reservoirs. In this study, the tetrahydrofuran (THF) hydrates that exhibit pore habits of the pore-filling pattern are formed in sediments, and the water permeability is quantified as a function of hydrate saturation. The results reveal that a decrease in the permeability for an increase in the hydrate saturation. Based on the measured values that are bounded by Kozeny grain-coating and pore-filling models, the fitting parameters of the empirical permeability models are indicated for use in numerical simulation of long-term hydrate dissociation. Wave velocity measurements reveal pore habits of pore-filling pattern of THF hydrates in the sediments with S h < 0.5, and a gradual transition to patchy and load-bearing pore-habits when S h > 0.6. The numerical simulation results obtained using the complementary pore-network model suggest that the THF hydrates in the sediments may form in small clusters with an average patch size of ~4 pores.

58 GEOSCIENCES↗
DOE OSTI2024

Calibration and validation of the foundation for a multiphase strength model for tin

In this work, the Common Model of Multi-phase Strength and Equation of State (CMMP) model was applied to tin. Specifically, calibrations of the strength-specific elements of the CMMP foundation were developed with a combination of experiments and theory, and then the model was validated experimentally. The first element of the foundation is a multi-phase analytic treatment of the melt temperature and the shear modulus for the solid phases. These models were parameterized for each phase based on ab initio calculations using the software VASP (Vienna Ab initio Simulations Package) based on density functional theory. The shear modulus model for the ambient phase was validated with ultrasonic sound speed measurements as a function of pressure and temperature. The second element of the foundation is a viscoplastic strength model for the phase, upon which strength for inaccessible higher-pressure phases can be scaled as necessary. The stress–strain response of tin was measured at strain rates of 10 -3 to 3 x 10 3 s -1 and temperatures ranging from 87 to 373 K. The Preston–Tonks–Wallace (PTW) strength model was fit to that data using Bayesian model calibration. For validation, six forward and two reverse Taylor impact experiments were performed at different velocities to measure large plastic deformation of tin at strain rates up to ⁠10 5 s -1 . The PTW model accurately predicted the deformed shapes of the cylinders, with modest discrepancies attributed to the inability of PTW to capture the effects of twinning and dynamic recrystallization. Some material in the simulations of higher velocity Taylor cylinders reached the melting temperature, thus testing the multiphase model because of the presence of a second phase, the liquid. In simulations using a traditional modeling approach, the abrupt reduction of strength upon melt resulted in poor predictions of the deformed shape and non-physical temperatures. With CMMP, the most deformed material points evolved gradually to a mixed solid–liquid but never a fully liquid state, never fully lost strength, stayed at the melt temperature as the latent heat of fusion was absorbed, and predicted the deformed shape well.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Oxygen evolution from olivine Mn 1– x M x PO 4 ( M =Fe,Ni,Al,Mg) delithiated cathode materials

Olivine LiMnPO 4 is a promising cathode material for Li-ion batteries. One drawback of this material is the propensity of its delithiated phase, MnPO 4 , to evolve oxygen gas above approximately 200 °C. During thermal runaway of cells, this oxygen gas can burn the electrolyte and other cell components and thereby jeopardize safety. Partial substitution of Mn with M = Fe, Ni, Al, or Mg has been used to improve the lithium intercalation kinetics of Li x MnPO 4 ; however, the effect of these substitutions on oxygen evolution is not fully documented. In this paper, we calculate phase diagrams and oxygen evolution diagrams for these Mn 1–x M x PO 4 delithiated cathode materials. To generate the phase diagrams, we use subregular solid-solution models and fit the energetic parameters of these models to density functional theory calculations of special quasirandom structures. The resulting thermodynamic models describe the effect of mixing on the initial temperature of oxygen evolution and on the cumulative amount of oxygen evolution at elevated temperatures. We find that addition of Fe increases the initial temperature and decreases the cumulative amount of oxygen evolution. Mn 0.5 Fe 0.5 PO 4 exhibits an initial temperature 50 °C higher than MnPO 4 and releases 70% less oxygen gas at 300 °C. Al is insoluble in MnPO 4 , so addition of Al has no affect on the initial temperature. However, Al addition does slightly decrease the amount of oxygen evolution due to an inactive AlPO 4 component. Mg and Ni both decrease the initial temperature of oxygen evolution, and therefore may worsen the safety of MnPO 4 .

25 ENERGY STORAGE↗
DOE OSTI2014

HERMES impact for the access of Compton form factors

We utilize the DVCS asymmetry measurements of the HERMES collaboration for access to Compton form factors in the deeply virtual regime and to generalized parton distributions. In particular, the (almost) complete measurement of DVCS observables allows us to map various asymmetries into the space of Compton form factors, where we still rely in this analysis on dominance of twist-two associated Compton form factors. We compare this one-to-one map with local Compton form factor fits and a model dependent global fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

FuelsGen

This toolset generates heterogeneous spatial layouts, aimed at representing forest fuels applicable to wildland fire modeling. Methods are included for calibrating (fitting) this model to data extracted from plot survey information.

Gattiker, James↗
DOE OSTI2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Calibration and validation of the foundation for a multiphase strength model for tin

In this work, the Common Model of Multi-phase Strength and Equation of State (CMMP) model was applied to tin. Specifically, calibrations of the strength-specific elements of the CMMP foundation were developed with a combination of experiments and theory, and then the model was validated experimentally. The first element of the foundation is a 10 multi-phase analytic treatment of the melt temperature and the shear modulus for the solid phases. These models were parameterized for each phase based on ab initio calculations using the software VASP (Vienna Ab initio Simulations Package) based on density functional theory (DFT). The shear modulus model for the ambient β phase was validated with ultrasonic sound speed measurements as a function of pressure and temperature. The second element of the foundation is a viscoplastic strength model for the β phase, upon which strength for inaccessible higher-pressure phases can be scaled as necessary. The stress-strain response of tin was measured at strain rates of 10 -3 to 3 x 10 3 s -1 and temperatures ranging from 87 to 373 K. The Preston-Tonks-Wallace (PTW) strength model was fit to that data using Bayesian model calibration. For validation, six forward and two reverse Taylor impact experiments were performed at different velocities to measure large plastic deformation of tin at strain rates up to 10 5 s -1 . The PTW model accurately predicted the deformed shapes of the cylinders, with modest discrepancies attributed to the inability 20 of PTW to capture the effects of twinning and dynamic recrystallization. Some material in the simulations of higher velocity Taylor cylinders reached the melting temperature, thus testing the multiphase model because of the presence of a second phase, the liquid. In simulations using a traditional modeling approach, the abrupt reduction of strength upon melt resulted in poor predictions of the deformed shape and non-physical temperatures. With CMMP, the most deformed material points evolved gradually to a mixed solid-liquid but never fully liquid state, never fully lost strength, 25 stayed at the melt temperature as the latent heat of fusion was absorbed, and predicted the deformed shape well.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

A major goal in pre-detonation nuclear forensics is to infer the processing conditions and/or facility type that produced radiological material. This review paper focuses on analyses of particle size, shape, texture (“morphology”) signatures that could provide information on the provenance of interdicted materials. For example, uranium ore concentrates (UOC or yellowcake) include ammonium diuranate (ADU), ammonium uranyl carbonate (AUC), sodium diuranate (SDU), magnesium diuranate (MDU), and others, each prepared using different salts to precipitate U from solution. Once precipitated, UOCs are often dried and calcined to remove adsorbed water. The products can be allowed to react further, forming uranium oxides UO3, U3O8, or UO2 powders, whose surface morphology can be indicative of precipitation and/or calcination conditions used in their production. This review paper describes statistical issues and approaches in using quantitative analyses of measurements such as particle size and shape to infer production conditions. Statistical topics include multivariate t tests (Hotelling’s T 2 ), design of experiments, and several machine learning (ML) options including decision trees, learning vector quantization neural networks, mixture discriminant analysis, and approximate Bayesian computation (ABC). ABC is emphasized as an attractive option to include the effects of model uncertainty in the selected and fitted forward model used for inferring processing conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1983

Laboratory studies at high resolution of the infrared absorption spectra of a number of gases found in planetary atmospheres

The infrared absorption spectra of a number of gases found in planetary atmospheres were studied at high resolution. Absorption line measurements which can be of value for the interpretation of planetary spectra in terms of molecular abundances and conditions in the planetary atmospheres were provided. The high resolution spectra have yielded measurements of individual vibration rotation line parameters including positions, strengths, pressure broadened widths and, where assignments were unknown, the temperature sensitivity of the strengths. Such information allows the determinations of the absorption of a given molecular gas under planetary conditions of temperature and pressure and at the same time it provides the data necessary if the spectra are to be understood in terms of basic molecular theory. Thus this work has included spectral analysis in the form of line assignments as well as fitting of the data to Hamiltonian models. Such fitting is very useful in that it helps to confirm and extend the assignments.

Hunt, R. H.↗
NASA NTRS1984

The structure of clusters of galaxies observed with Einstein

Imaging observations from the Einstein Observatory are used to determine properties of galactic clusters and the intracluster gas. The hydrostatic-isothermal gas model is applied to obtain the cluster core radius, the limiting slope of the X-ray surface brightness distribution, and the presence and magnitude of a central luminosity excess above that predicted from the model when fit to the outer regions of the cluster. It is concluded that clusters can be divided into two basic families, one with small core radii and X-ray emission centered on a central dominant galaxy, and one with larger core radii and generally no central, stationary bright galaxy. The former type probably begins to form in the early stages of a cluster's dynamical evolution. The intracluster gas has a larger scale height than that of the galaxies based on the fit of the hydrostatic-isothermal model to the X-ray surface brightness profiles.

Jones, C.↗
NASA NTRS1992

Extended atmospheres of comets and outer planet-satellite systems

For the hydrogen coma of comet P/Halley, both a Lyman-alpha image and extensive Lyman-alpha scan data obtained by the Pioneer Venus Orbiter Ultraviolet spectrometer as well as H-alpha ground-based spectral observations obtained by the University of Wisconsin Space Physics Group were successfully interpreted and analyzed with our Monte Carlo particle trajectory model. The excellent fit of the model and the Halley data and the water production rate determined near perihelion (9 Feb. 1986) from 13 Dec. 1985 to 13 Jan. 1986 and from 1 Feb. to 7 Mar. 1986 are discussed. Studies for the circumplanetary distribution of atomic hydrogen in the Saturn and Neptune systems were undertaken for escape of H atoms from Titan and Triton, respectively. The discovery of a new mechanism which can dramatically change the normal cylindrically symmetric distribution of hydrogen about the planet is discussed. The implications for the Titan-Saturn and Triton-Neptune are summarized.

Smyth, William H.↗
NASA NTRS2023

First VLTI/GRAVITY Observations of HIP 65426 b: Evidence for a Low or Moderate Orbital Eccentricity

Giant exoplanets have been directly imaged over orders of magnitude of orbital separations, prompting theoretical and observational investigations of their formation pathways. In this paper, we present new VLTI/GRAVITY astrometric data of HIP 65426 b, a cold, giant exoplanet which is a particular challenge for most formation theories at a projected separation of 92 au from its primary. Leveraging GRAVITY's astrometric precision, we present an updated eccentricity posterior that disfavors large eccentricities. The eccentricity posterior is still prior dependent, and we extensively interpret and discuss the limits of the posterior constraints presented here. We also perform updated spectral comparisons with self-consistent forward-modeled spectra, finding a best-fit ExoREM model with solar metallicity and C/O = 0.6. An important caveat is that it is difficult to estimate robust errors on these values, which are subject to interpolation errors as well as potentially missing model physics. Taken together, the orbital and atmospheric constraints paint a preliminary picture of formation inconsistent with scattering after disk dispersal. Further work is needed to validate this interpretation. Analysis code used to perform this work is available on GitHub: https://github.com/sblunt/hip65426.

Sarah Blunt↗
DOE OSTI2018

The impact of alternative land and yield assumptions in herbaceous biomass supply modeling: one-size-fits-all resource assessment?: One-size-fits-all resource assessment?

The Billion-ton Reports series has addressed the technical economic potential of supplying additional biomass from farmland and forests.Underlying each of the reports and supporting scenarios is a series of assumptions that drive the modeled output. The assumptions have developed over time with the support of technical experts from industry, academia, and government. Energy crops have not yet reached commodity scale, and only exist in commercial production in a limited number of regions, so many of the key assumptions of biomass potential are not supported by commercial demonstrations across multiple regions. This report examines the biomass potential of herbaceous energy crops from US farmland when alternative assumptions concerning production are modeled. In particular, the assumption of energy grasses, both perennial and annual, is modified with respect to land eligibility, annual rotations, and yield growth. The results of these changes are presented in six scenarios – three of which are modifications to the base-case scenario and three to the high-yield scenario. Finally, the impact on land enrolled and biomass supply are discussed with respect to the most recent 2016 Billion-ton Report results.

09 BIOMASS FUELS↗
NASA NTRS1982

Surface fitting with biharmonic and harmonic models

The physical and geometric interpretation of a surface fitting technique, multiquadric equations (MQ), is discussed. The relation of this method and its reciprocal form to biharmonic and harmonic techniques respectively, is pointed out. In both forms the solutions may be viewed as being numerical approximations of an integral equation in which an unknown density function is the physical source for disturbing potential (reciprocal-MQ) or elastic displacement (MQ).

Hardy, R. L.↗
DOE OSTI2023

Use of Sobol’ Variance-Based Global Sensitivity Analysis and Multidimensional Legendre Polynomial Fitting for Reduced Order Modeling

Sandia National Laboratories (SNL) has developed a novel reduced order modeling approach. Prioritization of inputs is accomplished using Sobo' indices obtained through a more efficient variance-based global sensitivity analysis. To determine the Sobo' functions, simulated input values are aligned to collocation points to permit the use of Gauss-Lobatto integration, thereby reducing the number of simulation trials needed by more than an order of magnitude compared to standard Monte Carlo approaches. Furthermore, by leveraging the orthogonality of Legendre polynomials in conjunction with those same simulations at the collocation nodes, an efficient fitting method is developed to represent the Sobo' functions from which a reduced order model (ROM) is constructed. The developed method is both more efficient computationally, and the resulting ROM is more accurate. The efficacy of this technique is demonstrated on a nonlinear polynomial test function as well as the nonlinear Ishigami and Sobo' g functions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗
DOE OSTI2023

Numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

For this work, we numerically evaluated photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively) on stream corridor transport. Correctly separating HSZ and SSZ effects is critical to estimating the hydro-biogeochemical function of a stream because HSZs and SSZs expose solutes to significantly different biogeochemical conditions, like sunlight exposure, microbial processes, and oxygen availability. Our numerical experiments used a multiscale river-corridor transport model implemented in the ATS code, which accommodates multiple storage zones with distinct travel time distributions and biogeochemical reactions. For parameter inferences, we used Bayesian inverse modeling. We found that breakthrough curves for photo-decaying tracers from day and night injection can delineate surface and hyporheic transient storage contributions, but only when interpreted jointly through a two-storage zone model. Numerical experiments that used only daytime injection or interpreted breakthrough curves with a single storage zone model yielded good fit to breakthrough curves, but parameter estimates were biased and controlling processes misattributed, examples of good model fits for the wrong reasons. Using those biased parameter estimates in reactive transport simulations resulted in significantly different projections of denitrification, which underscores the potential for stream function to be mischaracterized if tracer tests are interpreted through an inappropriately simplified model for transient storage. More generally, this study highlights the role of modeling in evaluating the experimental design and identifying the potential of system mischaracterization and its implications.

54 ENVIRONMENTAL SCIENCES↗