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NASA NTRS2019

Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC/yr). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

Sajeev Philip↗

DOE OSTI2014

Impact of Different Oseltamivir Regimens on Treating Influenza A Virus Infection and Resistance Emergence: Insights from a Modelling Study

Several studies have proven oseltamivir to be efficient in reducing influenza viral titer and symptom intensity. However, the usefulness of oseltamivir can be compromised by the emergence and spread of drug-resistant virus. The selective pressure exerted by different oseltamivir therapy regimens have received little attention. Combining models of drug pharmacokinetics, pharmacodynamics, viral kinetics and symptom dynamics, we explored the efficacy of oseltamivir in reducing both symptoms (symptom efficacy) and viral load (virological efficacy). We simulated samples of 1000 subjects using previously estimated between-subject variability in viral and symptom dynamic parameters to describe the observed heterogeneity in a patient population. We simulated random mutations conferring resistance to oseltamivir. We explored the effect of therapy initiation time, dose, intake frequency and therapy duration on influenza infection, illness dynamics, and emergence of viral resistance. Symptom and virological efficacies were strongly associated with therapy initiation time. The proportion of subjects shedding resistant virus was 27-fold higher when prophylaxis was initiated during the incubation period compared with no treatment. It fell to below 1% when treatment was initiated after symptom onset for twice-a-day intakes. Lower doses and prophylaxis regimens led to lower efficacies and increased risk of resistance emergence. We conclude that prophylaxis initiated during the incubation period is the main factor leading to resistance emergence.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2012

Parametric Explosion Spectral Model

Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

The Role of Early Giant-planet Instability in Terrestrial Planet Formation

The terrestrial planets are believed to have formed by violent collisions of tens of lunar- to Mars-size protoplanets at time t < 200 Myr after the protoplanetary gas disk dispersal (t {sub 0}). The solar system giant planets rapidly formed during the protoplanetary disk stage and, after t {sub 0}, radially migrated by interacting with outer disk planetesimals. An early (t < 100 Myr) dynamical instability is thought to have occurred with Jupiter having gravitational encounters with a planetary-size body, jumping inward by ∼0.2–0.5 au, and landing on its current, mildly eccentric orbit. Here we investigate how the giant-planet instability affected the formation of the terrestrial planets. We study several instability cases that were previously shown to match many solar system constraints. We find that resonances with giant planets help to remove solids available for accretion near ∼1.5 au, thus stalling the growth of Mars. It does not matter, however, whether the giant planets are placed on their current orbits at t {sub 0} or whether they realistically evolve in one of our instability models; the results are practically the same. The tight orbital spacing of Venus and Earth is difficult to reproduce in our simulations, including cases where bodies grow from a narrow annulus at 0.7–1 au, because protoplanets tend to spread radially during accretion. The best results are obtained in the narrow-annulus model when protoplanets emerging from the dispersing gas nebula are assumed to have (at least) the mass of Mars. This suggests efficient accretion of the terrestrial protoplanets during the first ∼10 Myr of the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRSDate not supplied

Rocket Propulsion Test Design and Analysis

As the small satellite launch vehicle (SSLV) market grows and NASA continues to prepare for upcoming missions in the Artemis program, John C. Stennis Space Center’s (SSC) testing facilities must adapt to the increasing demand in liquid rocket engine testing. The Rocket Propulsion Test Design and Analysis Project for this rotation focused in both of this areas through two separate subprojects, the creation of a Private Rocket Engine Database and the automatization of the A1-Set Point Prediction Model. To identify the testing requirements of future Stennis Space Center (SSC) costumers, an excel spread sheet was commissioned as a database to collect technical and non-technical features of over one hundred privately developed liquid and hybrid rocket engine. Similarly, The A-1 Set Point Sheet Model is used to satisfy Aerojet Rocketdyne’s testing requirements of Net Positive Suction Pressure (NPSP) for the RS-25 staged combustion cycle engine. To expand the capabilities of this prediction model, a feed back loop was programmed to automate the search of setpoints using Excel Visual Basic for Applications (VBA).

John Paul Ortiz↗

DOE OSTI2020

An energy model of droplet impingement on an inclined wall under isothermal and non-isothermal environments

The observation of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of different droplet-wall impingement conditions is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process. These conditions are grouped as: a single diesel droplet impinging on the wall with different inclined angles (α); cold wall - heated droplet and heated wall - cold droplet impingement when inclined angle of the wall is 0°, respectively. The analytical model is built up based on the energy conservation that considers kinetic energy, gravitation energy, and surface energy before impingement, as well as viscous dissipation, gravitation energy, adhesion energy, deformation energy, and heat energy after impingement. The experimental work of diesel droplet impinging on an inclined wall is performed at a certain range of the Weber number (We of 33 to 420) with various inclined angles (α of 0° to 45°), while for inclined angle is 0°, droplet and wall temperature are varied from 25°C to 150°C to study the effects of the inclined angle and temperature on the temporal evolution of the post-impingement characteristics (i.e. droplet spreading length, dynamic contact angle). The analytical model is validated and evaluated at the aforementioned experimental operating points. The validated model can be employed to predict maximum spreading length of the droplet impinged on the wall. It is further utilized to determine the transition from capillary regime to kinetic regime, then to viscous regime at different inclined angle of the wall.

42 ENGINEERING↗

DOE OSTI2022

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI techniques that uncover the relationships between discernible data signatures and model predictions. In this context, counterfactual explanations that synthesize small, interpretable changes to a given query while producing desired changes in model predictions have become popular. This under-constrained, inverse problem is vulnerable to introducing irrelevant feature manipulations, particularly when the model’s predictions are not well-calibrated. Hence, in this paper, we propose the TraCE (training calibration-based explainers) technique, which utilizes a novel uncertainty-based interval calibration strategy for reliably synthesizing counterfactuals. Given the wide-spread adoption of machine-learned solutions in radiology, our study focuses on deep models used for identifying anomalies in chest X-ray images. Using rigorous empirical studies, we demonstrate the superiority of TraCE explanations over several state-of-the-art baseline approaches, in terms of several widely adopted evaluation metrics. Our findings show that TraCE can be used to obtain a holistic understanding of deep models by enabling progressive exploration of decision boundaries, to detect shortcuts, and to infer relationships between patient attributes and disease severity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Generation of realistic input parameters for simulating atmospheric point-spread functions at astronomical observatories

High-fidelity simulated astronomical images are an important tool in developing and measuring the performance of image-processing algorithms, particularly for high precision measurements of cosmic shear – correlated distortions of images of distant galaxies due to weak gravitational lensing caused by the large-scale mass distribution in the Universe. For unbiased measurements of cosmic shear, all other sources of correlated image distortions must be modeled or removed. One such source is the correlated blurring of images due to optical turbulence in the atmosphere, which dominates the point-spread function (PSF) for ground-based instruments. In this work, we leverage data from weather forecasting models to produce wind speeds and directions, and turbulence parameters, that are realistically correlated with altitude. To study the resulting correlations in the size and shape of the PSF, we generate simulated images of the PSF across a ~10 square-degree field of view – the size of the camera focal plane for the Vera C. Rubin Observatory in Chile – using weather data and historical seeing for a geographic location near the Observatory. We make quantitative predictions for two-point correlation functions (2PCF) that are used in analyses of cosmic shear. We observe a strong anisotropy in the two-dimensional 2PCF, which is expected based on observations in real images, and study the dependence of the orientation of the anisotropy on dominant wind directions near the ground and at higher altitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

SU-E-T-572: Beam Characteristics and Treatment Planning Commissioning for a New Proton Therapy Unit

Purpose: A single-room proton system, the Mevion S250, was introduced into the arena of proton radiotherapy by Mevion Medical Systems. The first unit was installed and operates at the S. Lee Kling Proton Therapy Center at Barnes-Jewish Hospital. The objective of this abstract is to report the system's beam characteristics and Eclipse commissioning. Methods: Commissioning data were acquired for modelling longitudinal fluence, virtual source position, effective source position, source size and Bragg peaks in Eclipse. Stoichiometric CT calibration was generated via ICRU44 human. Spread-out Bragg peaks (SOBP) were measured with Parallel Plate Chamber and profiles with solid state detector for model validation. Heterogeneity effects were measured with bone and lung inserts in the beam line. RT dose was computed in a virtual water phantom, and exported from Eclipse to compare with measurements at various depths and axis. SOBPs were fine-tuned with partial shining correction and entry correction to match measurements. Output factor was measured for each individual field with an ADCL ion chamber in a water tank and fitted to a polynomial function to cross-check the monitor unit verification. Results: Ranges of all 24 options were measured within ±1mm tolerance. Modulations met a ±1mm or ±2% tolerance. SOBP flatness met a ±3% tolerance. Distal fall off (80%-20%) were measured between 6mm and 7mm for all options. Virtual source positions varied between 177cm and 195cm, decreasing with field size and range. SOBP generated by Eclipse agreed with measurements within ±3% in the entry region, and ±1%/±1mm in other regions. Sanity check for output achieved 5% accuracy in 98% of cases. Conclusion: The commissioning of the first Mevions S250 proton therapy system met specifications. The unit has been put in clinical operation since 12/17/2013.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Modeling the one-dimensional imager of neutrons (ODIN) for neutron response functions at the Sandia Z facility

The one-dimensional imager of neutrons (ODIN) at the Sandia Z facility consists of a 10-cm block of tungsten with rolled edges, creating a slit imager with slit widths of either 250, 500, or 750 μm. Designed with a 1-m neutron imaging line of sight, we achieve about 4:1 magnification and 500-μm axial spatial resolution. The baseline inertial confinement fusion concept at Sandia is magnetized liner inertial fusion, which nominally creates a 1-cm line source of neutrons. ODIN was designed to determine the size, shape, and location of the neutron producing region, furthering the understanding of compression quality along the cylindrical axis of magnetized liner implosions. Challenges include discriminating neutrons from hard x-rays and gammas with adequate signal-to-noise in the 2 × 10 12 deuterium-deuterium (DD) neutron yield range, as well as understanding the point spread function of the imager to various imaging detectors (namely, CR-39). Modeling efforts were conducted with MCNP6.1 to determine neutron response functions for varying configurations in a clean DD neutron environment (without x-rays or gammas). Configuration alterations that will be shown include rolled-edge slit orientation and slit width, affecting the resolution and response function. The experiment to determine CR-39 neutron sensitivity, with and without a high density polyethylene (n, p) converter, an edge spread function, and resolution will be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Monte Carlo Control Loops for Cosmic Shear Cosmology with DES Year 1

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. The Monte Carlo Control Loops (MCCL) is a forward modelling method designed to tackle this problem. It relies on the Ultra Fast Image Generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. We present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_{\ell}$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, Point Spread Function (PSF), an Approximate Bayesian Computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and the fast estimation of the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a non-tomographic setting, we derive a set of $C_\ell$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $\Omega_m$, $\sigma_8$, and intrinsic alignment amplitude $A_{\rm{IA}}$, defined as $S_8D_{\rm{IA}} = \sigma_8(\Omega_m/0.3)^{0.5}D_{\rm{IA}}$, where $D_{\rm{IA}}=1-0.11(A_{\rm{IA}}-1)$. We find $S_8D_{\rm{IA}}=0.895^{+0.054}_{-0.039}$, where systematics are at the level of roughly 60\% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Monte Carlo control loops for cosmic shear cosmology with DES Year 1 data

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. Monte Carlo control loops (MCCL) is a forward modeling method designed to tackle this problem. It relies on the ultra fast image generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. Here, we present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_ℓ$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, point spread function (PSF), an approximate Bayesian computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and a fast method to estimate the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a nontomographic setting, we derive a set of $C_ℓ$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $Ω_m$, $σ_8$, and intrinsic alignment amplitude $A_{IA}$, defined as $S_8D_{IA}=σ_8(Ω_m/0.3)^{0.5}D_{IA}$, where $D_{IA}=1-0.11(A_{IA}-1)$. We find $S_8D_{IA}=0.8954_{-0.039}^{+0.054}$, where systematics are at the level of roughly 60% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2019

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling

The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

Southern Great Plains↗

DOE OSTI2015

Hydrodynamical evolution of merging carbon–OXYGEN white dwarfs: Their pre-supernova structure and observational counterparts

We perform smoothed particle hydrodynamics simulations for merging binary carbon–oxygen (CO) WDs with masses of 1.1 and 1.0 M{sub ⊙}, until the merger remnant reaches a dynamically steady state. Using these results, we assess whether the binary could induce a thermonuclear explosion, and whether the explosion could be observed as a type Ia supernova (SN Ia). We investigate three explosion mechanisms: a helium-ignition following the dynamical merger (“helium-ignited violent merger model”), a carbon-ignition (“carbon-ignited violent merger model”), and an explosion following the formation of the Chandrasekhar mass WD (“Chandrasekhar mass model”). An explosion of the helium-ignited violent merger model is possible, while we predict that the resulting SN ejecta are highly asymmetric since its companion star is fully intact at the time of the explosion. The carbon-ignited violent merger model can also lead to an explosion. However, the envelope of the exploding WD spreads out to ∼0.1 R{sub ⊙}; it is much larger than that inferred for SN 2011fe (<0.1 R{sub ⊙}) while much smaller than that for SN 2014J (∼1 R{sub ⊙}). For the particular combination of the WD masses studied in this work, the Chandrasekhar mass model does not successfully lead to an SN Ia explosion. Besides these assessments, we investigate the evolution of unbound materials ejected through the merging process (“merger ejecta”), assuming a case where the SN Ia explosion is not triggered by the helium- or carbon-ignition during the merger. The merger ejecta interact with the surrounding interstellar medium and form a shell. The shell has a bolometric luminosity of more than 2×10{sup 35} erg s{sup −1}, lasting for ∼2×10{sup 4} years. If this is the case, the Milky Way should harbor about 10 such shells at any given time. The detection of the shell(s) can therefore rule out the helium-ignited and carbon-ignited violent merger models as major paths to SN Ia explosions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Integrated Process Testing of MSR Salt Spill Accidents

Part of the licensing process for new nuclear reactors requires vendors to assess the potential consequences of identified accident scenarios using accident progression modeling. The accident scenario that will likely be evaluated by all molten salt reactor (MSR) developers is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). The development of accident progression models requires experimental data to inform which processes to incorporate, to enable the calculation of parameters to model these processes, and to validate the model predictions. The data should quantify the sensitivities of key processes (e.g., molten salt spreading, heat transfer, containment structure corrosion, radionuclide vaporization, and aerosol generation) towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, results from integrated process tests that quantify coupled processes are required to validate systems-level models. This report documents results from integrated process tests conducted on simulated molten salt spill accidents. The generated experimental data simultaneously quantify the heat transfer behavior of the spilled salt, compositional changes to the bulk salt, and the release of surrogate fission products from the spilled salt as aerosol particles. All tests that were conducted used FLiNaK doped with surrogate fission products, and the variables that were evaluated included the initial salt temperature and the concentration of surrogate fission products present in the salt. The major accomplishments of this work include identifying surrogate fuel salt compositions that provide insight into the dispersal behavior of radionuclides of potential significance to the source term, employing previously developed methods and measurement techniques to simultaneously measure key processes, generating data on the coupled processes of molten salt heat transfer and surrogate fission product release as aerosol particles, demonstrating new test methods for real-time monitoring of the flow rate of the spill and aerosol size quantification in an argon atmosphere, and developing a mass transfer model for cesium and iodine release from molten FLiNaK to provide insight into aerosol formation by vapor condensation. The same methodology applied herein can be employed to study different salt compositions of interest to MSR developers, different environmental conditions, and other variables that are relevant to postulated accident scenarios. The insights gained from these integrated process tests conducted at a laboratory scale will be incorporated into future integral effects tests conducted at an engineering scale.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2012

Saltstone SDU6 Modeling Study

A new disposal unit, designated as Saltstone Disposal Unit 6 (SDU6), is being designed for support of site accelerated closure goals and salt waste projections identified in the new Liquid Waste System Plan. The unit is a cylindrical disposal cell of 375 ft in diameter and 43 ft in height, and it has a minimum 30 million gallons of capacity. SRNL was requested to evaluate the impact of an increased grout placement height on the flow patterns radially spread on the floor and to determine whether grout quality is impacted by the height. The primary goals of the work are to develop the baseline Computational Fluid Dynamics (CFD) model and to perform the evaluations for the flow patterns of grout material in SDU6 as a function of elevation of grout discharge port and grout rheology. Two transient grout models have been developed by taking a three-dimensional multiphase CFD approach to estimate the domain size of the grout materials radially spread on the facility floor and to perform the sensitivity analysis with respect to the baseline design and operating conditions such as elevation height of the discharge port and fresh grout properties. For the CFD modeling calculations, air-grout Volume of Fluid (VOF) method combined with Bingham plastic and time-dependent grout models were used for examining the impact of fluid spread performance for the initial baseline configurations and to evaluate the impact of grout pouring height on grout quality. The grout quality was estimated in terms of the air volume fraction for the grout layer formed on the SDU6 floor, resulting in the change of grout density. The study results should be considered as preliminary scoping analyses since benchmarking analysis is not included in this task scope. Transient analyses with the Bingham plastic model were performed with the FLUENT TM code on the high performance parallel computing platform in SRNL. The analysis coupled with a transient grout aging model was performed by using ANSYS-CFX code in the parallel computing platform in Mercer University. Recommended operational guidance was developed assuming that local shear rates and flow patterns related to radial spread along the SDU floor can be used as a measure of grout performance and spatial dispersion affected by the grout height and viscosity. The main conclusions drawn from the grout modeling and calculations are as follows: • The 5 ft height baseline results show that when the 150 gpm grout flow with a 5 Pa yield stress and a 60 cp viscosity is poured down through a 3 inch discharge port, the grout is spread radially up to about 64 ft distance from the pouring center after 2 hours’ pouring time. The air volume fraction of the grout layer is about 29% at 5 minutes’ transient time, and it is reduced by about 9% in 2 hours’ pouring time, resulting in the grout density consisting of about 80% grout and 20% air volume fractions. • The sensitivity results show that when the discharge port is located at a higher position, a larger amount of air is trapped inside the layer formed below the discharge port at the early transient time of less than 30 minutes because of the higher impinging momentum of the grout flow on the floor, resulting in the formation of less smooth layer. • The results clearly indicate that the radial spread for the 43 ft discharge port is about 10% faster than that of the 5 ft discharge port for the early transient period of 5 minutes. However, for the pouring time longer than half an hour, the discharge port height does not affect the radial distance spread on the disposal floor. • When grout quality is related to grout volume fraction, the grout volume fraction for the 43 ft discharge port has lower volume fraction than the 5 ft discharge port for the transient period of the first 5 minutes. However, for the pouring time longer than half an hour, the discharge port height does not affect the grout volume fraction for the layer accumulated on the disposal floor. • A modified Bingham plastic model coupled with time-dependent viscosity behavior was developed for conducting the initial scoping calculations to assess the impact of fluid residence time on radial spreading and basic flow patterns. • The results for the transient viscosity model show that when grout material becomes more viscous, the thickness of the grout layer accumulated on the floor becomes higher, but the radial distance spread on the horizontal floor becomes smaller. The early transient results for the grout density with about 32% air volume fractions are in reasonable agreement with those of the idealized Bingham plastic model. • It is recommended that the current models developed here be benchmarked against the experimental results for critical applications of the modeling results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2021

Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning

Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.

DEVELOP Tech Paper↗

DOE OSTI2025

Neural Posterior Estimation for Cataloging Astronomical Images with Spatially Varying Backgrounds and Point Spread Functions

Neural posterior estimation (NPE), a type of amortized variational inference, is a computationally efficient means of constructing probabilistic catalogs of light sources from astronomical images. To date, NPE has not been used to perform inference in models with spatially varying covariates. However, ground-based astronomical images exhibit spatially varying sky backgrounds and point spread functions (PSFs), and accounting for this variation is essential for constructing accurate catalogs of imaged light sources. In this work, we introduce a novel NPE-based cataloging method that trains an inference network with semisynthetic astronomical images generated using PSFs and backgrounds sampled from the Sloan Digital Sky Survey. In experiments with semisynthetic images, we evaluate the method on key cataloging tasks: light source detection, star/galaxy separation, and flux measurement. A “generalist” inference network—trained with diverse PSFs and backgrounds—performs as well as a “specialist” network even when both are evaluated on the specialist’s particular PSF/background combination. This result suggests that a single NPE network can generalize across spatial variations, eliminating the need for retraining on each observational condition.

astronomy image processing↗