SEARCH · Search NASA

Results for “Model serving”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,441 records · Page 80

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Implementation of a Transition Model in a NASA Code and Validation Using Heat Transfer Data on a Turbine Blade

The purpose of this report is to summarize and document the work done to enable a NASA CFD code to model laminar-turbulent transition process on an isolated turbine blade. The ultimate purpose of the present work is to down-select a transition model that would allow the flow simulation of a variable speed power turbine to be accurately performed. The flow modeling in its final form will account for the blade row interactions and their effects on transition which would lead to accurate accounting for losses. The present work only concerns itself with steady flows of variable inlet turbulence. The low Reynolds number k- model of Wilcox and a modified version of the same model will be used for modeling of transition on experimentally measured blade pressure and heat transfer. It will be shown that the k- model and its modified variant fail to simulate the transition with any degree of accuracy. A case is thus made for the adoption of more accurate transition models. Three-equation models based on the work of Mayle on Laminar Kinetic Energy were explored. The three-equation model of Walters and Leylek was thought to be in a relatively mature state of development and was implemented in the Glenn-HT code. Two-dimensional heat transfer predictions of flat plate flow and two-dimensional and three-dimensional heat transfer predictions on a turbine blade were performed and reported herein. Surface heat transfer rate serves as sensitive indicator of transition. With the newly implemented model, it was shown that the simulation of transition process is much improved over the baseline k- model for the single Reynolds number and pressure ratio attempted; while agreement with heat transfer data became more satisfactory. Armed with the new transition model, total-pressure losses of computed three-dimensional flow of E3 tip section cascade were compared to the experimental data for a range of incidence angles. The results obtained, form a partial loss bucket for the chosen blade. In time the loss bucket will be populated with losses at additional incidences. Results obtained thus far will be discussed herein.

Ameri, Ali A.↗

NASA NTRS1988

A flight-test methodology for identification of an aerodynamic model for a V/STOL aircraft

Described is a flight test methodology for developing a data base to be used to identify an aerodynamic model of a vertical and short takeoff and landing (V/STOL) fighter aircraft. The aircraft serves as a test bed at Ames for ongoing research in advanced V/STOL control and display concepts. The flight envelope to be modeled includes hover, transition to conventional flight, and back to hover, STOL operation, and normaL cruise. Although the aerodynamic model is highly nonlinear, it has been formulated to be linear in the parameters to be identified. Motivation for the flight test methodology advocated in this paper is based on the choice of a linear least-squares method for model identification. The paper covers elements of the methodology from maneuver design to the completed data base. Major emphasis is placed on the use of state estimation with tracking data to ensure consistency among maneuver variables prior to their entry into the data base. The design and processing of a typical maneuver is illustrated.

Bach, Ralph E., Jr.↗

DOE OSTI2018

Intermolecular structural correlations in model globular and unconcatenated ring polymer liquids

We employ the field theoretic polymer integral equation theory to construct a segment-level theory for the thermodynamics and pair structure of dense liquids of interpenetrating ring polymers and a simple globule model. The latter is defined by a fractal mass distribution on all internal length scales with an exponent equal to the spatial dimension (d F = d s = 3). In an isochoric ensemble the dimensionless compressibility and pressure is predicted to vary exponentially with macromolecular volume fraction. An intermolecular correlation hole exists down to small length scales. This model appears to be useful for a recently studied experimental soft nanoparticle suspension, and also serves as a reference system for our analysis of ring liquids. Motivated by simulations, a two-fractal exponent ring model is adopted for the intramolecular structure factor. At smaller lengths it describes chain-like macromolecules, while on larger scales it corresponds to a space-filling object in the sense that d F = d s = 3. The crossover between these two regimes is of order the entanglement length of the linear chain analog. Based on a constant compressibility ensemble, the effective volume fraction grows at intermediate values of degree of polymerization (N), and crosses over to a very slow logarithmic growth at large N. A weaker intermolecular correlation hole is predicted. The number of nearest neighbor rings increases dramatically at small N, akin to linear chain melts, but then tends to saturate at large N, in accord with simulations. We determine that the tools developed may be relevant for other partially interpenetrating soft objects such as core–shell nanogels or microgels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Coupling an External Plant Code

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) with the aim to develop standalone software to perform the dynamic HRA calculations. Within the HRA, human actions in nuclear power plants (NPPs) are predicated by plant states, and human actions influence the plant. In other words, plant operations are necessarily recursive, and it becomes challenging to model complex human-plant interactions. Consequently, we have linked two software simulations that complement those shortcomings. RELAP5-3D—the Reactor Excursion and Leak Analysis Program (RELAP; Aumiller, Tomlinson, and Bauer 2001) is the foundational thermal-hydraulic software used to model nuclear systems. Using RELAP5-3D, we have simulated the plant operations proceeding according to procedures developed to address emergent situations in NPPs. Plant operations include various actions such as the operator checking plant parameters, as well as actions that are continuously performed over time until a specific parameter reaches certain criteria. That means that HUNTER and RELAP5-3D exchange information with each other and should be carried out simultaneously over time. To simulate plant operations, which represent the actual operator checks of plant parameters and corresponding manual control actions, changes in plant status are identified through simulation and performed according to the criteria and order of the procedure. Thus, the goal of coupling HUNTER with RELAP5-3D is to facilitate synchronous coupling, where human and plant models provide iterative feedback loops that drive the course of actions. The advantage of coupling with RELAP5-3D to serve as the external environment module in HUNTER is the ability to customize the plant model and streamline for particular model applications. In this paper, we will address the key features of the coupling and the coupling structure built to perform the feedback loops.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Fourth order expressions for the electronic absorption lineshape of molecular excitons

The line shape of electronic absorption spectroscopy reflects the information on quantum dynamical processes accompanying the electronic excitation, and its accurate description is an important component for validating theoretical models and assumptions. The present work provides detailed expressions for the absorption line shape of molecular excitons that are valid up to the fourth order of exciton-bath interactions within the quantum master equation approach. These expressions can serve as the basis for developing general and systematic methods to model the line shape for a broad class of molecular exciton systems and environments. For the bath model of linearly coupled harmonic oscillators, more detailed expressions employing the spectral densities of the bath are presented. These expressions are then tested for a linear aggregate of identical chromophores each coupled to the harmonic oscillator bath. Finally, calculation results for a super-Ohmic spectral density with exponential cutoff demonstrate the feasibility of calculations and also offer insights into the utility and difficulty of going beyond the second order approximation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Residential Battery Modeling for Control-Oriented Techno-Economic Studies: Preprint

Electrochemical batteries, which serve as electric energy storage devices, are becoming increasingly popular among residential buildings that incorporate solar photovoltaic (PV) systems to help meet their energy needs. Battery economics are affected by performance degradation over time, and managing this degradation can help extend the battery's lifespan. The tradeoff between operational costs/benefits and managing battery degradation is of significant research interest. One of the key factors for assessing battery degradation is the dispatch strategy used to control the charging and discharging of the battery. Conventional dispatch strategies typically use simple rule-based methods, and these overly aggressive charging/discharging cycles can significantly reduce a battery’s life span. Our research seeks to develop optimized dispatch strategies for grid-connected PV homes with a goal of extending battery life while simultaneously taking into consideration utility costs and occupant comfort. To achieve this goal, we adapted lithium-ion battery life- and cyclic-degradation models for use in high-fidelity building simulations, so whole-building and grid-interactive controllers can dispatch the batteries along with other flexible loads. With the help of a co-simulation platform, we performed a simulation study to compute the optimized dispatch strategies for relevant operating conditions brought about by changing geographical locations, weather conditions, and utility pricing. Comparing the optimized strategies with the conventional strategies resulted in a >50% decrease in capacity degradation and >10% average reduction in operational costs during the months of January and July in Fort Collins, Colorado; Phoenix, Arizona; and Portland, Oregon.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2016

The trends high-contrast imaging survey. VI. Discovery of a mass, age, and metallicity benchmark brown dwarf

The mass and age of substellar objects are degenerate parameters leaving the evolutionary state of brown dwarfs ambiguous without additional information. Theoretical models are normally used to help distinguish between old, massive brown dwarfs and young, low-mass brown dwarfs but these models have yet to be properly calibrated. We have carried out an infrared high-contrast imaging program with the goal of detecting substellar objects as companions to nearby stars to help break degeneracies in inferred physical properties such as mass, age, and composition. Rather than using imaging observations alone, our targets are pre-selected based on the existence of dynamical accelerations informed from years of stellar radial velocity (RV) measurements. In this paper, we present the discovery of a rare benchmark brown dwarf orbiting the nearby (d = 18.69 ± 0.19 pc), solar-type (G9V) star HD 4747 ([Fe/H] = −0.22 ± 0.04) with a projected separation of only ρ = 11.3 ± 0.2 au (θ = 0.″6). Precise Doppler measurements taken over 18 years reveal the companion’s orbit and allow us to place strong constraints on its mass using dynamics (msin i=55.3±1.9M{sub Jup}). Relative photometry (ΔK {sub s} = 9.05 ± 0.14, M{sub K{sub s}}=13.00±0.14, K{sub s}−L{sup ′}=1.34±0.46) indicates that HD 4747 B is most likely a late-type L-dwarf and, if near the L/T transition, an intriguing source for studying cloud physics, variability, and polarization. We estimate a model-dependent mass of m=72{sub −13}{sup +3} M{sub Jup} for an age of 3.3{sub −1.9}{sup +2.3} Gyr based on gyrochronology. Combining astrometric measurements with RV data, we calculate the companion dynamical mass (m=60.2±3.3M{sub Jup}) and orbit (e = 0.740 ± 0.002) directly. As a new mass, age, and metallicity benchmark, HD 4747 B will serve as a laboratory for precision astrophysics to test theoretical models that describe the emergent radiation of brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2017

Predictive Modeling of Fast-Curing Thermosets in Nozzle-Based Extrusion

This work presents an approach to modeling the dynamic spreading and curing behavior of thermosets in nozzle-based extrusions. Thermosets cover a wide range of materials, some of which permit low-temperature processing with subsequent high-temperature and high-strength working properties. Extruding thermosets may overcome the limited working temperatures and strengths of conventional thermoplastic materials used in additive manufacturing. This project aims to produce technology for the fabrication of thermoset-based structures leveraging advances made in nozzle-based extrusion, such as fused deposition modeling (FDM), material jetting, and direct writing. Understanding the synergistic interactions between spreading and fast curing of extruded thermosetting materials will provide essential insights for applications that require accurate dimensional controls, such as additive manufacturing [1], [2] and centrifugal coating/forming [3]. Two types of thermally curing thermosets -- one being a soft silicone (Ecoflex 0050) and the other being a toughened epoxy (G/Flex) -- served as the test materials in this work to obtain models for cure kinetics and viscosity. The developed models align with extensive measurements made with differential scanning calorimetry (DSC) and rheology. DSC monitors the change in the heat of reaction, which reflects the rate and degree of cure at different crosslinking stages. Rheology measures the change in complex viscosity, shear moduli, yield stress, and other properties dictated by chemical composition. By combining DSC and rheological measurements, it is possible to establish a set of models profiling the cure kinetics and chemorheology without prior knowledge of chemical composition, which is usually necessary for sophisticated mechanistic modeling. In this work, we conducted both isothermal and dynamic measurements with both DSC and rheology. With the developed models, numerical simulations yielded predictions of diameter and height of droplets, along with width and height of extruded lines cured at varied temperatures. Experimental results carried out on a goniometric platform and a nozzle-based 3D printer showed agreement with the numerical simulations. Finally, this presentation will show how the models are adaptable to the planning of tool paths and designs in additive manufacturing.

Xie, Jingjin↗

DOE OSTI2021

Kinetic modeling of anaerobic degradation of plant-derived aromatic mixtures by Rhodopseudomonas palustris

Abstract Rhodopseudomonas palustris is a model microorganism for studying the anaerobic metabolism of aromatic compounds. While it is well documented which aromatics can serve as sole organic carbon sources, co-metabolism of other aromatics is poorly understood. This study used kinetic modeling to analyze the simultaneous degradation of aromatic compounds present in corn stover hydrolysates and model the co-metabolism of aromatics not known to support growth of R. palustris as sole organic substrates. The simulation predicted that p -coumaroyl amide and feruloyl amide were hydrolyzed to p -coumaric acid and ferulic acid, respectively, and further transformed via p -coumaroyl-CoA and feruloyl-CoA. The modeling also suggested that metabolism of p -hydroxyphenyl aromatics was slowed by substrate inhibition, whereas the transformation of guaiacyl aromatics was inhibited by their p -hydroxyphenyl counterparts. It also predicted that substrate channeling may occur during degradation of p -coumaroyl-CoA and feruloyl-CoA, resulting in no detectable accumulation of p -hydroxybenzaldehyde and vanillin, during the transformation of these CoA ligated compounds to p- hydroxybenzoic acid and vanillic acid, respectively. While the simulation correctly represented the known transformation of p -hydroxybenzoic acid via the benzoyl-CoA pathway, it also suggested co-metabolism of vanillic acid and syringic acid, which are known not to serve as photoheterotrophic growth substrate for R. palustris .

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2010

Simplified Vicarious Radiometric Calibration

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

Stanley, Thomas↗

DOE OSTI2024

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives.

access↗

DOE OSTI2020

An ab initio exciton model for singlet fission

Here we present an ab initio exciton model that extends the Frenkel exciton model and includes valence, charge-transfer, and multiexcitonic excited states. It serves as a general, parameter-free, yet computationally efficient and scalable approach for simulation of singlet fission processes in multichromophoric systems. A comparison with multiconfigurational methods confirms that our exciton model predicts consistent energies and couplings for the pentacene dimer and captures the correct physics. Calculations of larger pentacene clusters demonstrate the computational scalability of the exciton model and suggest that the mixing between local and charge-transfer excitations narrows the gap between singlet and multiexcitonic states. Local vibrations of pentacene molecules are found to facilitate singlet–multiexcitonic state-crossing and hence are important for understanding singlet fission. The exciton model developed in this work also sets the stage for further implementation of the nuclear gradients and nonadiabatic couplings needed for first principles nonadiabatic quantum molecular dynamics simulations of singlet fission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Effect of sample size on the maximum value distribution of fatigue driving forces in metals and alloys

An analytical framework is presented to predict the effects of sample size on the maximum value distribution (MVD) of the driving forces for fatigue crack formation in metals and alloys. The distribution of the maximum driving force for fatigue crack formation over the domain follows the generalized extreme value theory in the limit as the domain size increases to infinity. Here, a simulation-based analysis of microstructure influences on fatigue resistance for polycrystalline metals and alloys is very costly, and reaching those limits is intractable. This work models the MVD of Fatigue Indicator Parameters (FIPs), which serve as surrogate measures for the driving force for fatigue crack formation, at finite sample sizes prior to their convergence to a limiting extreme value distribution. Large-scale crystal plasticity finite element (CPFE) simulations of FCC Al 7075-T6 with microstructure realizations of various sizes are incorporated to calibrate and evaluate the developed framework, and a total of ∼6.5 million grains of Al 7075-T6 are examined. The calibrated analytical solution agrees well with the brute force Monte Carlo simulation results extracted from the CPFE simulations. Furthermore, the developed formulation can predict the MVD of FIPs for different sample sizes using a size-dependent parameter, and it is capable of accurately extrapolating the MVD of FIPs for much larger microstructure sample sizes than the size used for its calibration.

Crystal plasticity↗

DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗

DOE OSTI2020

Progress on Understanding Rayleigh–Taylor Flow and Mixing Using Synergy Between Simulation, Modeling, and Experiment

Simultaneous advances in numerical methods and computing, theoretical techniques, and experimental diagnostics have all led independently to better understanding of Rayleigh–Taylor (RT) instability, turbulence, and mixing. In particular, experiments have provided significant motivation for many simulation and modeling studies, as well as validation data. Numerical simulations have also provided data that is not currently measurable or very difficult to measure accurately in RT unstable flows. Thus, simulations have also motivated new measurements in this class of buoyancy-driven flows. This overview discusses simulation and modeling studies synergistic with experiments and examples of how experiments have motivated simulations and models of RT instability, flow, and mixing. First, a brief summary of measured experimental and calculated simulation quantities, of experimental approaches, and of issues and challenges in the simulation and modeling of RT experiments is presented. Implicit large-eddy, direct numerical, and large-eddy simulations validated using RT experimental data are then discussed. This is followed by a discussion of modeling using analytical, modal, buoyancy–drag, and turbulent transport models of RT mixing experiments. The discussion will focus on three-dimensional RT mixing arising from multimode perturbations. Finally, this focused review concludes with a perspective on future simulation, modeling, and experimental directions for further research. Research in simulation and modeling of RT unstable flows, coupled with experiments, has made significant progress over the past several decades. This overview serves as an opportunity to both discuss progress and to stimulate future research on simulation and modeling of this unique class of hydrodynamically unstable turbulent flows.

42 ENGINEERING↗

DOE OSTI2019

Physical and Thermodynamic Properties of Secondary Organic Materials for Modeling (Final Technical Report)

Secondary organic material constitutes more than 50% of the submicron component of atmospheric aerosol particles. This organic material is produced by oxidation of biogenic and anthropogenic volatile organic compounds. The physicochemical properties of these aerosol particles and their variability with atmospheric conditions influence many climate-relevant endpoints, such as rates of chemical reactions, production of secondary organic material, number-diameter distributions, direct radiative forcing, and cloud condensation nuclei. The results of the project research highlight a nonlabile-to-labile transition for material representative of anthropogenic secondary organic particulate matter at a threshold humidity range. This behavior differs markedly from materials representing biogenic aerosol sources, which lack such a transition. More specifically, the mass lability of atmospheric organic particulate matter, meaning its tendency to evaporate, is an important property in the mechanisms governing the climate effects. This property is affected by both the volatility and the molecular diffusivity of the constituent organic species. Via a series of laboratory experiments, the project directly determined the mass labilities of films of secondary organic material representative of anthropogenic and biogenic organic particulate matter (PM). The evaporation rates for anthropogenic organic PM increased above a threshold relative humidity (RH) between 20% and 30%, indicating rapid partitioning above a transition RH. Below the threshold, the characteristic time for equilibration was estimated at up to 1 week for a typically sized particle. In contrast, for films representing biogenic PM, no RH threshold was observed, suggesting equilibrium partitioning is rapidly obtained for all RHs. The effective molecular diffusivity for the biogenic case was at least 1000 times greater than that of the anthropogenic case. The results allow for an improved representation of anthropogenic and biogenic secondary organic aerosol formation in climate models. The results of the project also provide new measurements on how organic aerosol particles take up water and serve as cloud condensation nuclei, thus explaining the observed complex thermodynamic behaviors using a simple thermodynamic model. The project results reconciled the discrepancy between sub-saturation hygroscopicity and super-saturation cloud condensation nuclei activity for organic aerosol particles. The key to the explanation is the phase separation between hydrophobic and hydrophilic organics and the induced surface tension lowering. The results are essential for the assessment of the aerosol indirect effect on climate. In more detail, hygroscopic growth and cloud condensation nuclei activation are key processes for accurately modeling the climate impacts of organic particulate matter. Nevertheless, the microphysical mechanisms of these processes remain unresolved. The project results focus on complex thermodynamic behaviors, including humidity-dependent hygroscopicity, diameter-dependent cloud condensation nuclei activity, and liquid-liquid phase separation in the laboratory for biogenically derived secondary organic material representative of similar atmospheric organic particulate matter. These behaviors can be explained by the non-ideal mixing of water with hydrophobic and hydrophilic organic components. The non-ideality-driven liquid-liquid phase separation further enhances water uptake and induces lowered surface tension at high relative humidity, which results in a lower barrier to cloud condensation nuclei activation. By comparison, secondary organic material representing anthropogenic sources does not exhibit complex thermodynamic behavior. The combined results highlight the importance of detailed thermodynamic representations of the hygroscopicity and cloud condensation nuclei activity in models of the Earth’s climate system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

Abstract Identification of a heterogeneous conductivity field and reconstruction of a contaminant release history are key aspects of subsurface remediation. These two goals are achieved by combining model predictions with sparse and noisy hydraulic head and concentration measurements. Solution of this inverse problem is notoriously difficult due to, in part, high dimensionality of the parameter space and high computational cost of repeated forward solves. We use a convolutional adversarial autoencoder (CAAE) to parameterize a heterogeneous non‐Gaussian conductivity field via a low‐dimensional latent representation. A three‐dimensional dense convolutional encoder‐decoder (DenseED) network serves as a forward surrogate of the flow and transport model. The CAAE‐DenseED surrogate is fed into the ensemble smoother with multiple data assimilation (ESMDA) algorithm to sample from the Bayesian posterior distribution of the unknown parameters, forming a CAAE‐DenseED‐ESMDA inversion framework. The resulting CAAE‐DenseED‐ESMDA inversion strategy is used to identify a three‐dimensional contaminant source and conductivity field. A comparison of the inversion results from CAAE‐ESMDA with physical flow and transport simulator and from CAAE‐DenseED‐ESMDA shows that the latter yields accurate reconstruction results at the fraction of the computational cost of the former.

Zhou, Zitong↗

NASA NTRSDate not supplied

RadLab Platform: Investigating Space Radiation

The RadLab Project, initiated by the Open Science Data Repository (OSDR) for Space Biology at NASA Ames Research Center (osdr.nasa.gov), aims to be an ongoing compilation of radiation data relevant to human space flight. Sponsored by the NASA Human Research Program, RadLab serves as the latest database in this domain. RadLab is intended to serve the needs of both the space radiation detector and space radiation biology communities. The RadLab architecture is being designed to accommodate data both from low Earth orbit (LEO) and beyond low Earth orbit (BLEO). Our long-term vision entails the establishment of a sustainable database receiving continuous updates through APIs connecting to other databases, as well as individual investigator contributions via a RadLab submission portal, modeled on the OSDR (https://osdr.nasa.gov/bio/submission-sso-login.html). In addition to serving as a resource for space biologists and space radiation physicists, such a database would facilitate the deployment of AI algorithms to study the impact of location in space and within spacecraft on the ambient space radiation field. The ultimate goal is to develop predictive dosimetry algorithms for future BLEO missions.

Sylvain V Costes↗