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All sources NASA NTRS DOE OSTI

DOE OSTI2014

Multiple indicators, multiple causes measurement error models

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methods for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Radiative transfer modelling of discontinuous tree canopies at microwave frequencies

Development of a first-order radiative transfer model for predicting backscatter from tree canopies has been underway at the University of Michigan Radiation Laboratory for some time. This model is known as the Michigan Microwave Canopy Scattering (MIMICS) model. This article presents the second-generation MIMICS model (MIMICS II) which accounts for canopies with discontinuous (open) crown layer geometries. MIMICS II models open crown layers by treating the location, size, and shape of the individual tree crowns as random variables. The backscattering coefficients for the canopy are then determined by introducing statistics derived from these parameters into the radiative transfer solution. Application of the radiative transfer equations to the discontinuous canopy geometry is presented. The resulting model is a robust fully polarimetric solution that is applicable over a wide variety of canopy architectures. Model simulations are compared to results generated with the continuous canopy model. The effect of the open crown geometry is found to be most significant at shallow incidence angles and at high frequencies for trees with well-developed crowns. Under these conditions, the gaps in the crown layer give rise to a notable increase in crown layer transmissivity which allows the radar to see through to the lower layers of the canopy more easily, thereby directly affecting the backscatter contribution of the trunks and ground.

Mcdonald, K. C.↗

NASA NTRS1991

Modeling multi-frequency diurnal backscatter from a walnut orchard

The Michigan Microwave Canopy Scattering Model (MIMICS) is used to model scatterometer data that were obtained during the August 1987 EOS (Earth Observing System) synergism study. During this experiment, truck-based scatterometers were used to measure radar backscatter from a walnut orchard in Fresno County, California. Multipolarized L- and X-band data were recorded for orchard plots for which dielectric and evapotranspiration characteristics were monitored. MIMICS is used to model a multiangle data set in which a single orchard plot was observed at varying impedance angles and a series of diurnal measurements in which backscatter from this same plot was measured continuously over several 24-h periods. MIMICS accounts for variations in canopy backscatter driven by changes in canopy state that occur diurnally as well as on longer time scales. L-band backscatter is dependent not only on properties of the vegetation but also on properties of the underlying soil surface. The behavior of the X-band backscatter is dominated by properties of the tree crowns.

Mcdonald, Kyle C.↗

NASA NTRS1984

Cardiovascular and hormonal (aldosterone) responses in a rat model which mimics responses to weightlessness

Cardiovascular responses and fluid/electrolyte shifts seen during spaceflight have been attributed to cephalad redistribution of vascular fluid. The antiorthostatic (AO) rat (suspended, head-down tilt of 15-20 deg) is used to model these responses. This study documents that elevated blood pressures in AO rats are sustained for periods of up to seven days, compared with presuspension values. Increased blood pressures in AO rats suggests a specific response to AO positioning, potentially relatable to a cephalad fluid shift. To assess a role for hormonal regulation of sodium excretion, serum aldosterone levels were measured. Circulating aldosterone concentrations were seen to increase approximately 100 percent during seven days of AO suspension, concurrently with a pronounced natriuresis. These results suggest that aldosterone may not be involved in the long term regulation of increased Na(+) excretion in AO animals. These studies continue to show the usefulness of models for the development of animal protocols for space flight.

Musacchia, X. J.↗

NASA NTRS1999

A liposomal model that mimics the cutaneous production of vitamin D3. Studies of the mechanism of the membrane-enhanced thermal isomerization of previtamin D3 to vitamin D3

We reported previously that the rate of previtamin D3 (preD3) <==> vitamin D3 isomerization was enhanced by about 10 times in the skin compared with that in organic solvents. To elucidate the mechanism by which the rate of this reaction is enhanced in the skin, we developed a liposomal model that mimicked the enhanced isomerization of preD3 to vitamin D3 that was described in human skin. Using this model we studied the effect of changing the polarity of preD3 as well as changing the chain length and the degree of saturation of liposomal phospholipids on the kinetics of preD3 <==> vitamin D3 isomerization. We found that a decrease in the hydrophilic interaction of the preD3 with liposomal phospholipids by an esterification of the 3beta-hydroxy of preD3 (previtamin D3-3beta-acetate) reduced the rate of the isomerization by 67%. The addition of a hydroxyl on C-25 of the hydrophobic side chain (25-hydroxyprevitamin D3), which decreased the hydrophobic interaction of preD3 with the phospholipids, reduced the rate by 87%. In contrast, in an isotropic n-hexane solution, there was little difference among the rates of the conversion of preD3, its 3beta-acetate, and 25-hydroxy derivatives to their corresponding vitamin D3 compounds. We also determined rate constants (k) of preD3 <==> vitamin D3 isomerization in liposomes containing phosphatidylcholines with different carbon chain lengths. The rates of the reaction were found to be enhanced as the number of carbons (Cn) in the hydrocarbon chain of the phospholipids increased from 10 to 18. In conclusion, these results support our hypothesis that amphipathic interactions between preD3 and membrane phospholipids stabilize preD3 in its "cholesterol like" cZc-conformer, the only conformer of preD3 that can convert to vitamin D3. The stronger these interactions were, the more preD3 was likely in its cZc conformation at any moment and the faster was the rate of its conversion to vitamin D3.

NASA Discipline Regulatory Physiology↗

DOE OSTI2019

MCNP TREAT Core Model with MIMIC-N

This MCNP model contains the MIMIC-N materials and instrumentation test and the BUSTER containment system within the TREAT core in a full slot configuration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1990

Multiband radar characterization of forest biomes

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

Dobson, M. Craig↗

DOE OSTI2020

Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics

We develop physics-constrained and control-oriented predictive deep learning models for the thermal dynamics of a real-world commercial office building. The proposed method is based on the systematic encoding of physics-based prior knowledge into a structured recurrent neural architecture. Specifically, our model mimics the structure of the building thermal dynamics model and leverages penalty methods to model inequality constraints. Additionally, we use constrained matrix parameterization based on the Perron-Frobenius theorem to bound the eigenvalues of the learned network weights. We interpret the stable eigenvalues as dissipativeness of the learned building thermal model. We demonstrate the effectiveness of the proposed approach on a dataset obtained from an office building with $20$ thermal zones.

Building Energy, structured neural networks↗

DOE OSTI2022

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Here, subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a – 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

The 1991 AVIRIS/POLDER experiment in Camargue, France

Airborne campaigns during the eighties provided high spectral resolution data, collected with imaging instruments such as AIS, AVIRIS, FLI, CAESI, and ISM, in order to investigate the relationship with canopy biophysical characteristics. The statistical approaches used to analyze these data do not allow investigation of the causality and the applicability of the observed correlations. Further, statistical studies demonstrated the high degree of redundancy of the spectral information amongst many others. And for retrieving vegetation biophysical characteristics, few results demonstrate the real information gain attributable to the high spectral resolution capability as compared to the use of a few wide wavelength bands. With several new imaging spectrophotometers scheduled for launch during the next 10 years (MERIS, MODIS, HIRIS), progress in the description and understanding of the mechanisms that drive the spectral variation of canopy reflectance is required. Most of these new sensor systems will also have the capability to observe the target under differing view directions. The problem of the combination and the use of the synergy between both the spectral and the directional sources of canopy reflectance variations has to be addressed. Apart from the atmospheric effects, the spectral variation of the light reflected by canopies originates from the leaves, the soil or the other vegetation elements such as branches and fruits. At leaf level, both diffuse reflectance and transmittance may be simulated by simple models, although no accurate information exists on the absorption features of the biochemicals (except water) in the 900-2500nm wavelength range. Many models mimic the directional variability of canopy reflectance at a given wavelength. Combining a leaf spectral model with a canopy directional model provides a powerful tool to analyze this problem. Some of us have initiated such a study, but our approach and theory remain to be tested using canopy data with their complexity, associated experimental error, and atmospheric effects. The main objective of the 1990 POLDER/AVIRIS experiment in Camargue was to provide a consistent data set over various canopies in order to test the applicability of the theory. The experiment, part of the 1991 MAC Europe experiment, involved simultaneous data collection using two sensors: AVIRIS and POLDER which measures the bidirectional and polarization properties of the targets at 670 and 880nm wavebands.

Baret, F.↗

NASA NTRS2002

Molecular modeling of interactions in electronic nose sensors for environmental monitoring

We report a study aimed at understanding analyte interactions with sensors made from polymer-carbon black composite films. The sensors are used in an Electronic Nose (ENose) which is used for monitoring the breathing air quality in human habitats. The model mimics the experimental conditions of the composite film deposition and formation and was developed using molecular modeling and simulation tools. The Dreiding 2.21 Force Field was used for the polymer and analyte molecules while graphite parameters were assigned to the carbon black atoms. The polymer considered for this work is methyl vinyl ether / maleic acid copolymer. The target analytes include both inorganic (NH3) and organic (methanol) types of compound. Results indicate different composite-analyte interaction behavior.

electronic noise polymer-carbon composite molecula↗

DOE OSTI2017

Semilocal exchange hole with an application to range-separated density functionals

The exchange-correlation hole is a central concept in density functional theory. It not only provides justification for an exchange-correlation energy functional but also serves as a local ingredient for nonlocal range-separated density functionals. However, due to the nonlocal nature, modeling the conventional exact exchange hole presents a great challenge to density functional theory. In this work, we propose a semilocal exchange hole underlying the Tao-Perdew-Staroverov-Scuseria (TPSS) meta-generalized gradient approximation functional. Our model is distinct from previous ones not only at small separation between an electron and the hole around the electron but also in the way it interpolates between rapidly varying and slowly varying densities. Here the interpolation is determined by the wave-vector analysis on the infinite-barrier model for a jellium surface. Numerical tests show that our exchange-hole model mimics the conventional exact one quite well for atoms. As a simple application, we apply the hole model to construct a TPSS-based range-separated functional. We find that this range-separated functional can substantially improve the band gaps and barrier heights of TPSS, without losing much accuracy for atomization energies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Vector interaction enhanced bag model for astrophysical applications

For quark matter studies in astrophysics the thermodynamic bag model (tdBAG) has been widely used. Despite its success it fails to account for various phenomena expected from QCD. We suggest a straightforward extension of tdBAG in order to take the dynamical breaking of chiral symmetry and the influence of vector interactions explicitly into account. As for tdBAG the model mimics confinement in a phenomenological approach. It is based on an analysis of the Nambu–Jona-Lasinio (NJL) model at finite density. Furthermore, we demonstrate how NJL and bag models in this regime follow from the more general and QCD-based framework of the Dyson–Schwinger equations in a medium by assuming simple gluon contact interaction. Based on our simple and novel model, we construct quark hadron hybrid equations of state and systematically study chiral and deconfinement phase transitions, the appearance of s-quarks, and the role of vector interaction. We further study these aspects for matter in β-equilibrium at zero temperature, with particular focus on the current ∼2 M{sub ⊙} maximum mass constraint for neutron stars. Our approach indicates that the currently only theoretical evidence for the hypothesis of stable strange matter is an artifact of tdBAG and results from neglecting the dynamical breaking of chiral symmetry.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Implementation of a realistic artificial data generator for crash data generation

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. In conclusion, the crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

42 ENGINEERING↗

NASA NTRS1991

System monitoring and diagnosis with qualitative models

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Kuipers, Benjamin↗

NASA NTRS2007

Development of an Efficient CFD Model for Nuclear Thermal Thrust Chamber Assembly Design

The objective of this effort is to develop an efficient and accurate computational methodology to predict both detailed thermo-fluid environments and global characteristics of the internal ballistics for a hypothetical solid-core nuclear thermal thrust chamber assembly (NTTCA). Several numerical and multi-physics thermo-fluid models, such as real fluid, chemically reacting, turbulence, conjugate heat transfer, porosity, and power generation, were incorporated into an unstructured-grid, pressure-based computational fluid dynamics solver as the underlying computational methodology. The numerical simulations of detailed thermo-fluid environment of a single flow element provide a mechanism to estimate the thermal stress and possible occurrence of the mid-section corrosion of the solid core. In addition, the numerical results of the detailed simulation were employed to fine tune the porosity model mimic the pressure drop and thermal load of the coolant flow through a single flow element. The use of the tuned porosity model enables an efficient simulation of the entire NTTCA system, and evaluating its performance during the design cycle.

Cheng, Gary↗

DOE OSTI2020

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗

NASA NTRS1998

Hindlimb unloading of growing rats: a model for predicting skeletal changes during space flight

A model that uses hindlimb unloading of rats was developed to study the consequences of skeletal unloading and reloading as occurs during and following space flight. Studies using the model were initiated two decades ago and further developed at National Aeronautics and Space Administration (NASA)-Ames Research Center. The model mimics some aspects of exposure to microgravity by removing weightbearing loads from the hindquarters and producing a cephalic fluid shift. Unlike space flight, the forelimbs remain loaded in the model, providing a useful internal control to distinguish between the local and systemic effects of hindlimb unloading. Rats that are hindlimb unloaded by tail traction gain weight at the same rate as pairfed controls, and glucocorticoid levels are not different from controls, suggesting that systemic stress is minimal. Unloaded bones display reductions in cancellous osteoblast number, cancellous mineral apposition rate, trabecular bone volume, cortical periosteal mineralization rate, total bone mass, calcium content, and maturation of bone mineral relative to controls. Subsequent studies reveal that these changes also occur in rats exposed to space flight. In hindlimb unloaded rats, bone formation rates and masses of unloaded bones decline relative to controls, while loaded bones do not change despite a transient reduction in serum 1,25-dihydroxyvitamin D (1,25D) concentrations. Studies using the model to evaluate potential countermeasures show that 1,25D, growth hormone, dietary calcium, alendronate, and muscle stimulation modify, but do not completely correct, the suppression of bone growth caused by unloading, whereas continuous infusion of transforming growth factor-beta2 or insulin-like growth factor-1 appears to protect against some of the bone changes caused by unloading. These results emphasize the importance of local as opposed to systemic factors in the skeletal response to unloading, and reveal the pivotal role that osteoblasts play in the response to gravitational loading. The hindlimb unloading model provides a unique opportunity to evaluate in detail the physiological and cellular mechanisms of the skeletal response to weightbearing loads, and has proven to be an effective model for space flight.

Non-NASA Center↗