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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗
NASA NTRS2000

A Radiative Transfer Model for Climate Calculations

This paper describes a radiative transfer model developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. We use a newly developed k-distribution model for both the thermal and solar parts of the spectrum. We employ a generalized two-stream approximation for the scattering by aerosol and clouds. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. We perform several calculations focussing primarily on the question of absorption of solar radiation by gases and aerosols. We estimate the accuracy of the k-distribution to be approx. 1 W/sq m for the gaseous absorption in the solar spectrum. We estimate the accuracy of the two-stream method to be 3-12 W/sq m for the downward solar flux and 1-5 W/sq m for the upward solar flux at the top of atmosphere depending on the optical depth of the aerosol layer. We also show that the effect of ignoring aerosol absorption on the downward solar flux at the surface is 50 W/sq m for the TARFOX aerosol for an optical depth of 0.5 and 150 W/sq m for a highly absorbing mineral aerosol. Thus, we conclude that the uncertainty introduced by the aerosol solar radiative properties (and merely assuming some "representative" model) can be considerably larger than the error introduced by the use of a two-stream method.

Bergstrom, Robert W.↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Versatile and Accurate Method for Halo Mass Determination from Phase-space Distribution of Satellite Galaxies

We propose a versatile and accurate method to estimate the halo mass and concentration from the kinematics of satellite galaxies. We construct the 6D phase-space distribution function of satellites from a cosmological simulation based on the similarity of internal dynamics for different halos. Within the Bayesian statistical framework, not only can we efficiently infer the halo mass and concentration, we can also treat various observational effects, including the selection function, incomplete data, and measurement errors, in a rigorous and straightforward manner. Through tests with mock samples, we show that our method is valid and accurate, as well as more precise than pure steady-state methods. It can constrain the halo mass to within ~20% using only 20 tracers and has a small intrinsic uncertainty of ~10%. In addition to the clear application to the Milky Way and similar galaxies, our method can be extended to galaxy groups or clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Understanding Aitken Mode Aerosol Variability over the Southern Ocean and Antarctica: Insights from Cloud Condensation Nuclei Data

Aitken mode aerosol particles play an important role influencing cloud properties and sustenance, acting as a reservoir of potential cloud condensation nuclei against precipitation scavenging. However, there is limited data on Aitken mode aerosols. In this study, we develop a method to estimate Aitken mode aerosol concentrations and size distribution using cloud condensation nuclei measurements (CCN) and κ-Köhler theory. The performance of this method is evaluated using scanning mobility particle sizer (SMPS) data from recent field campaigns to demonstrate its skills and applicability. The method reasonably estimates Aitken- and accumulation-mode aerosol concentrations, achieving correlations of 0.7–0.9 with only modest biases (mean fractional bias within ±23% for Aitken mode and ±34% for accumulation-mode). This method is further applied to measurements collected over the Southern Ocean and Antarctica in recent years from multiple platforms, including ground sites, aircraft, and ships, to derive Aitken and accumulation-mode aerosol concentrations. Using the derived data, we examine the seasonal cycle, latitudinal variations, and vertical distribution of aerosols. Aitken mode aerosol concentrations are elevated over the Southern Ocean and Antarctica during the austral summer similar to the accumulation mode. In the austral summer, the free troposphere has more Aitken mode aerosols and fewer accumulation mode aerosols than the boundary layer, and thus likely serves as an important source of cloud-forming aerosol while also diluting the accumulation mode.

Kang, Litai [University of Washington] (ORCID:0000↗
NASA NTRS1961

Two Instruments for Measuring Distributions of Low-Energy Charged Particles in Space

Current estimates indicate that the bulk of interplanetary gas consists of protons with energies between 0 and 20 kev and concentrations of 1 to 105 particles/cu cm. Methods and instrumentation for measuring the energy and density distribution of such a gas are considered from the standpoint of suitability for space vehicle payloads. It is concluded that electrostatic analysis of the energy distribution can provide sufficient information in initial experiments. Both magnetic and electrostatic analyzers should eventually be used. Several instruments designed and constructed at the Ames Research Center for space plasma measurements, and the methods of calibration and data reduction are described. In particular, the instrument designed for operation on solar cell power has the following characteristics: weight, 1.1 pounds; size, 2 by 3 by 4 inches; and power consumption, 145 mw. The instrument is designed to yield information on the concentration, energy distribution, and the anisotropy of ion trajectories in the 0.2 to 20 kev range.

Bader, Michel↗
DOE OSTI2020

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

Estimation of discontinuous coefficients in parabolic systems - Applications to reservoir simulation

Spline-based techniques for estimating spatially varying parameters that appear in parabolic distributed systems (typical of those found in reservoir simulation problems) are presented. In particular, the problem of determining discontinuous coefficients is discussed, estimating both the functional shape and points of discontinuity for such parameters. In addition, the ideas may also be applied to problems with unknown initial conditions and unknown parameters appearing in terms representing external forces. Convergence results and a summary of numerical performance of the resulting algorithms are given.

Lamm, Patricia K.↗
NASA NTRS2000

Case Studies of the Vertical Structure of the Direct Shortwave Aerosol Radiative Forcing During TARFOX

The vertical structure of aerosol-induced radiative flux changes in the Earth's troposphere affects local heating rates and thereby convective processes, the formation and lifetime of clouds, and hence the distribution of chemical constituents. We present observationally based estimates of the vertical structure of direct shortwave aerosol radiative forcing for two case studies from the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) which took place on the U.S. east coast in July 1996. The aerosol radiative forcings are computed using the Fu-Liou broadband radiative transfer model. The aerosol optical properties used in the radiative transfer simulations are calculated from independent vertically resolved estimates of the complex aerosol indices of refraction in two to three distinct vertical layers, using profiles of in situ particle size distributions measured aboard the University of Washington research aircraft. Aerosol single-scattering albedos at 450 nm thus determined range from 0.9 to 0.985, while the asymmetry factor varies from 0.6 to 0.8. The instantaneous shortwave aerosol radiative forcings derived from the optical properties of the aerosols are of the order of -36 Wm(exp -2) at the top of the atmosphere and about -56 Wm(exp -2) at the surface for both case studies.

Redemann, J.↗
NASA NTRS2016

The Near-Earth Meteoroid Flux, Speed Distribution, and Uncertainty

Meteoroids are known to pose a threat to spacecraft; they can puncture components, disturb spacecraft attitude, and possibly create secondary electrical effects. Accurate environment models are therefore critical for mitigating meteoroid-related risks. While there are several meteoroid environment models available for assessing spacecraft risk, the uncertainties associated with these models are not well understood. Because meteoroid properties are derived from indirect observations such as meteors and impact craters, the uncertainty in the meteoroid flux is potentially quite large. We combine existing meteoroid flux measurements with new radar and optical meteor data to improve our characterization of the meteoroid flux onto the Earth and its velocity distribution. We use data extracted from the NASA all-sky network, the Canadian Automated Meteor Observatory, and the Canadian Meteor Orbit Radar. We improve our characterization of the observed meteoroid speed distribution by incorporating modern descriptions of the ionization efficiency (e.g., Thomas et al., 2016). We also present estimates of the uncertainties associated with our meteoroid flux distribution. Finally, we discuss the implications for spacecraft. Our model is constrained by the cratering rate on the space-facing surface of LDEF, and thus the risk posed to spacecraft by meteoroid-induced physical damage is the least uncertain component of our model. Other sources of risk, however, may vary. For instance, a lower average meteoroid speed would require a higher meteoroid mass flux in order to match the LDEF crater counts, leading to higher predicted rates of attitude disturbances.

Moorhead, Althea↗
NASA NTRS1990

Estimation of area-averaged rainfall over tropical oceans from microwave radiometry - A single channel approach

This paper presents a new simple retrieval algorithm for estimating area-time averaged rain rates over tropical oceans by using single channel microwave measurements from satellites. The algorithm was tested by using the Nimbus-5 Electrically Scanning Microwave Radiometer and a simple microwave radiative transfer model to retrieve seasonal 5-deg x 5-deg area averaged rainrate over the tropical Atlantic and Pacific from December 1973 to November 1974. The brightness temperatures were collected and analyzed into histograms for each season and in each grid box from December 1973 to November 1974. The histograms suggest a normal distribution of background noise plus a skewed rain distribution at the higher brightness temperatures. By using a statistical estimation procedure based upon normally distributed background noise, the rain distribution was separated from the raw histogram. The radiative transfer model was applied to the rain-only distribution to retrieve area-time averaged rainrates throughout the tropics. Despite limitations of single channel information, the retrieved seasonal rain rates agree well in the open ocean with expectations based upon previous estimates of tropical rainfall over the oceans.

Shin, Kyung-Sup↗
DOE OSTI2019

Assessment of the Geomechanical Risks Associated with CO 2 Injection at the FutureGen 2.0 Site: Application of the State of Stress Assessment Tool (SOSAT)

This report presents the results of the application of the State of Stress Assessment Tool (SOSAT) on the FutureGen 2.0 data set. SOSAT was developed as part of the National Risk Assessment Partnership (NRAP) project and provides a unique integrated framework for estimating the state of stress probability distribution at a given depth in the subsurface and evaluating the risk of induced shear and tensile failure resulting from the injection of carbon dioxide (CO 2 ). The approach implemented by SOSAT is based on two deterministic and widely used methods of determining the state of stress (i.e., stress polygon and one-dimensional tectonic-elastic approach). These methods have been modified using a probabilistic approach to account for uncertainties in the input parameters. The methodology proposed in SOSAT was demonstrated using the data obtained for the FutureGen 2.0 project located in the Illinois Basin. Although the FutureGen 2.0 project was suspended by the U.S. Department of Energy prior to the start of injection operations, the extensive characterization efforts undertaken at the storage site have yielded a considerable amount of valuable data about this part of the sedimentary basin. The FutureGen 2.0 storage site was designed to accommodate the injection of 1.1 million metric tons of CO 2 per year over a 20-year period. The injection of CO 2 and the associated pressure buildup in the reservoir is expected to alter the state of stress over the course of the injection. These changes in the initial stress state may affect fault stability and potentially lead to the unintentional creation of hydraulic fractures, which could pose a leakage risk if not contained within the reservoir. Assessing these risks is critical to making informed decisions about the characterization, management of the injection operation, and monitoring of the storage site. The data required by SOSAT for the geomechanical assessment of the FutureGen 2.0 site were identified, and the methodology proposed in SOSAT was followed to evaluate the probability of reactivating critically oriented faults or potentially creating hydraulic fractures in the reservoir. The results of the geomechanical analysis performed using the SOSAT led to the following conclusions. 1. The probability distribution of the state of stress indicates significant uncertainties in the magnitude of the maximum horizontal stress S Hmax , while the minimum horizontal stress S hmin is well constrained by the stress measurements conducted during the characterization efforts at the storage site. This uncertainty in the magnitude of S Hmax is a common challenge and has significant implications for geomechanical risk at sites like FutureGen 2.0 where a strike-slip tectonic regime exists. 2. The probability that the Mount Simon reservoir was initially critically stressed is relatively high—25%. When the pore pressure increases to the maximum allowable pressure permitted under the Underground Injection Control Class VI regulation of the FutureGen 2.0 project, the risk of shear failure approaches a probability of 43%. These relatively high probabilities reflect the current state of information about the geomechanical conditions in this part of the Illinois Basin. For future operations in this basin this should be a high characterization priority because it could significantly lower the risk of operations. 3. Based on the maximum injection pressure allowed in the UIC Class VI, the risk of unintentional hydraulic fracturing is limited. The risk of shear failure as determined by SOSAT is based on a very conservative approach assuming that critically oriented faults exist in the subsurface. While no faults have been formally identified at the FutureGen 2.0 site, the results obtained with SOSAT using the FutureGen 2.0 data set highlight the importance of integrating uncertainties in critical parameters to quantify geomechanical risks in a defensible way. Should SOSAT have been available at the time the characterization activities were being planned, more characterization efforts would have been implemented to reduce the uncertainties on the magnitude of the maximum horizontal stress, and to dismiss with confidence the potential existence of a critically-oriented fault in the reservoir (e.g., 3D seismic survey).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Accelerated Distributed Energy Management for Microgrids

This paper considers the optimal energy management for a microgrid. The goal of optimal energy management is to minimize the total generation cost while meeting total demand and satisfying individual generator output limits. To achieve this goal, we develop a distributed algorithm based on the consensus theory and gradient estimation technique. Compared to the existing algorithms with diminishing step-sizes, the proposed algorithm enjoys a faster convergence speed due to the fixed step-size, and thus increases the computation speed, and reduces the computation and communication burden. The proposed distributed algorithm is applicable to both fixed and time-varying directed communication networks. We show that the convergence of the proposed distributed algorithm is achieved if the fixed communication network is strongly connected, or if the time-varying communication network is uniformly jointly strongly connected. Numerical simulation results are used to illustrate and demonstrate the effectiveness of the proposed algorithm.

Du, Wen↗
NASA NTRS2006

On the Quality of the Nimbus 7 LIMS Version 6 Ozone for Studies of the Middle Atmosphere

The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) radiance profile dataset of 1978/79 was reconditioned and reprocessed to Version 6 (V6) profiles of temperature and species that are improved significantly over those from Version 5 (V5). The LIMS V6 dataset was archived for public use in 2002. Improvements for its ozone include: (1) a more accurate accounting for instrument and spacecraft motion effects in the radiances, (2) the use of better spectroscopic line parameters for its ozone forward model, (3) retrievals of all its scans, (4) more accurate and compatible temperature versus pressure profiles (or T(p)), which are needed for the registration of the ozone radiances and for the removal of temperature effects from them, and (5) a better accounting for interfering species in the lower stratosphere. The retrieved V6 ozone profiles extend from near cloud top altitudes to about 80 km and from 64S to 84N latitude with better sampling along the orbit than for the V5 dataset. Calculated estimates of the single-profile precision and accuracy are provided for the V6 ozone from this study. Precision estimates based on the data themselves are of order 3% or better from 1 to 30 hPa. Estimates of total systematic error for a single profile are hard to generalize because the separate sources of error may not all be of the same sign and they depend somewhat on the atmospheric state. It is estimated that the V6 zonal mean ozone distributions are accurate to within 9% to 7% from 50 hPa to 3 hPa, respectively. Effects of a temperature bias can be significant and may be present at 1 to 2 hPa though. There may be ozone biases of order 10% at those levels due to possible biases of up to +2 K, but there is no indication of a similar problem elsewhere in the stratosphere. Simulation studies show that the LIMS retrievals are also underestimating slightly the small amplitudes of the atmospheric temperature tides, which affect its retrieved day/night ozone differences. There are small biases in the middle to lower stratosphere for the ascending versus descending node LIMS ozone, due principally to not accounting for the asymmetric weighting of its radiances across the tangent layer. The estimates of total accuracy were assessed by comparing the daily zonal mean LIMS ozone distributions against those from the Nimbus 7 SBUV Version 8 (V8) dataset for the same period. Generally, the LIMS V6 ozone agrees well with SBUV, except perhaps in the tropical lower stratosphere where the LIMS ozone is less. Still, the accuracy for LIMS V6 ozone in the lower stratosphere is improved over that found for LIMS V5, as indicated by several LIMS comparisons with ECC ozonesonde profiles. The LIMS V6 ozone is considered especially suitable for detailed studies of large-scale stratospheric processes above the 100-hPa level. Comparison of diurnal, photochemical model calculations with the monthly-averaged, upper stratospheric ozone observed from LIMS V6 indicates only a slight ozone deficit for the model at about 2 hPa. However, that deficit exhibits little to no seasonal variation and is in good agreement with similar model comparisons for a seasonal time series of ozone obtained with ground-based microwave instruments. Because the LIMS V6 ozone in the lower stratosphere has improved accuracy and sampling versus that of V5, it should now be possible to conduct quantitative studies of ozone transport and chemistry for the northern hemisphere, polar stratospheric winter of 1978/79 a time period when the catalytic loss of ozone due to reactive chlorine should not have been a major factor for the Arctic region.

Remsberg, Ellis↗
DOE OSTI2024

Simulation-based inference for parameter estimation of complex watershed simulators

High-resolution, spatially distributed process-based (PB) simulators are widely employed in the study of complex catchment processes and their responses to a changing climate. However, calibrating these PB simulators using observed data remains a significant challenge due to several persistent issues, including the following: (1) intractability stemming from the computational demands and complex responses of simulators, which renders infeasible calculation of the conditional probability of parameters and data, and (2) uncertainty stemming from the choice of simplified representations of complex natural hydrologic processes. Here, we demonstrate how simulation-based inference (SBI) can help address both of these challenges with respect to parameter estimation. SBI uses a learned mapping between the parameter space and observed data to estimate parameters for the generation of calibrated simulations. To demonstrate the potential of SBI in hydrologic modeling, we conduct a set of synthetic experiments to infer two common physical parameters – Manning's coefficient and hydraulic conductivity – using a representation of a snowmelt-dominated catchment in Colorado, USA. We introduce novel deep-learning (DL) components to the SBI approach, including an “emulator” as a surrogate for the PB simulator to rapidly explore parameter responses. We also employ a density-based neural network to represent the joint probability of parameters and data without strong assumptions about its functional form. While addressing intractability, we also show that, if the simulator does not represent the system under study well enough, SBI can yield unreliable parameter estimates. Approaches to adopting the SBI framework for cases in which multiple simulator(s) may be adequate are introduced using a performance-weighting approach. The synthetic experiments presented here test the performance of SBI, using the relationship between the surrogate and PB simulators as a proxy for the real case.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Far-infrared and submillimeter-wavelength observations of star-forming dense cores. I - Spectra

Far-infrared and submillimeter photometry of 10 low-mass star formation regions containing embedded IRAS sources is presented. These new observations define the peak of the spectral energy distributions of these objects and provide more precise estimates of their bolometric luminosities. Two new sources, L1527 and L483, are among the reddest known low-mass objects, with spectral energy distribution peaks at 100-200 microns and extremely steep IRAS slopes. These cold sources have spectra which are similar to blackbodies of 30-40 K but have significant excess emission on the Wien side. Models of the spectral energy distributions using a spherically symmetric core structure indicate that these sources have visual extinctions greater than 1000 mag. However, models with these large extinctions predict too little near-infrared emission. A nonspherically symmetric distribution of circumstellar material may play a role in the generation of the extra near-infrared emission.

Ladd, E. F.↗
DOE OSTI2022

Quantile-specific heritability of plasma fibrinogen concentrations

Fibrinogen is a moderately heritable blood protein showing different genetic effects by sex, race, smoking status, pollution exposure, and disease status. These interactions may be explained in part by “quantile-dependent expressivity”, where the effect size of a genetic variant depends upon whether the phenotype (e.g. plasma fibrinogen concentration) is high or low relative to its distribution. Determine whether fibrinogen heritability (h 2 ) is quantile-specific, and whether quantile-specific h 2 could account for fibrinogen gene-environment interactions. Plasma fibrinogen concentrations from 5689 offspring-parent pairs and 1932 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β OP , h 2 = 2β OP /(1+r spouse )) and full-sib regression slopes (β FS , h 2 = {(1+8r spouse β FS ) 0.05 –1}/(2r spouse )) were robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples. Quantile-specific h 2 (±SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted fibrinogen distribution when estimated from β OP (P trend = 5.5x10 -6 ): 0.30±0.05 at the 10 th , 0.37±0.04 at the 25 th , 0.48±0.05 at the 50 th , 0.61±0.06 at the 75 th , and 0.65±0.08 at the 90 th percentile, and when estimated from β FS (P trend = 0.008): 0.28±0.04 at the 10 th , 0.31±0.04 at the 25 th , 0.36±0.03 at the 50 th , 0.41±0.05 at the 75 th , and 0.50±0.06 at the 90 th percentile. The larger genetic effect at higher average fibrinogen concentrations may contribute to fibrinogen’s greater heritability in women than men and in Blacks than Whites, and greater increase from smoking and air pollution for the FGB -455G>A A-allele. It may also explain greater fibrinogen differences between: 1) FGB -455G>A genotypes during acute phase reactions than usual conditions, 2) GTSM1 and IL-6 -572C>G genotypes in smokers than nonsmokers, 3) FGB -148C>T genotypes in untreated than treated diabetics, and LPL PvuII genotypes in macroalbuminuric than normoalbuminuric patients. Fibrinogen heritability is quantile specific, which may explain or contribute to its gene-environment interactions. The analyses do not disprove the traditional gene-environment interpretations of these examples, rather quantile-dependent expressivity provides an alternative explanation that warrants consideration.

59 BASIC BIOLOGICAL SCIENCES↗