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DOE OSTI2024

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

NASA NTRS2005

Near-Earth Object Astrometric Interferometry

Using astrometric interferometry on near-Earth objects (NEOs) poses many interesting and difficult challenges. Poor reflectance properties and potentially no significant active emissions lead to NEOs having intrinsically low visual magnitudes. Using worst case estimates for signal reflection properties leads to NEOs having visual magnitudes of 27 and higher. Today the most sensitive interferometers in operation have limiting magnitudes of 20 or less. The main reason for this limit is due to the atmosphere, where turbulence affects the light coming from the target, limiting the sensitivity of the interferometer. In this analysis, the interferometer designs assume no atmosphere, meaning they would be placed at a location somewhere in space. Interferometer configurations and operational uncertainties are looked at in order to parameterize the requirements necessary to achieve measurements of low visual magnitude NEOs. This analysis provides a preliminary estimate of what will be required in order to take high resolution measurements of these objects using interferometry techniques.

Werner, Martin R.↗

NASA NTRS2005

Mission Functionality for Deflecting Earth-Crossing Asteroids/Comets

Park, Sang-Young↗

NASA NTRS2013

Biological Effects of Particles with Very High Energy Deposition on Mammalian Cells Utilizing the Brookhaven Tandem Van de Graaff Accelerator

High LET radiation from GCR (Galactic Cosmic Rays) consisting mainly of high charge and energy (HZE) nuclei and secondary protons and neutrons, and secondaries from protons in SPE (Solar Particle Event) pose a major health risk to astronauts due to induction of DNA damage and oxidative stress. Experiments with high energy particles mimicking the space environment for estimation of radiation risk are being performed at NASA Space Radiation Laboratory at BNL. Experiments with low energy particles comparing to high energy particles of similar LET are of interest for investigation of the role of track structure on biological effects. For this purpose, we report results utilizing the Tandem Van de Graaff accelerator at BNL. The primary objective of our studies is to elucidate the influence of high vs low energy deposition on track structure, delta ray contribution and resulting biological responses. These low energy ions are of special relevance as these energies may occur following absorption through the spacecraft and shielding materials in human tissues and nuclear fragments produced in tissues by high energy protons and neutrons. This study will help to verify the efficiency of these low energy particles and better understand how various cell types respond to them.

Saha, Janapriya↗

NASA NTRS2017

Determination of the Risk of Radiation-Associated Circulatory and Cancer Disease Mortality in a NASA Early Astronaut Cohort

Of the many possible health challenges posed during extended exploratory missions to space, the effects of space radiation on cardiovascular disease and cancer are of particular concern. There are unique challenges to estimating those radiation risks; care and appropriate and rigorous methodology should be applied when considering small cohorts such as the NASA astronaut population. The objective of this work was to determine if there was sufficient evidence for excess risk of cardiovascular disease and cancer in early NASA astronaut cohorts. NASA astronauts in selection groups 1-7 were chosen; this relatively homogeneous cohort consists of 73 white males, who unlike today's astronauts, maintained similar smoking and drinking habits to the general US population, and have published radiation doses. The participants flew in space on missions Mercury through Shuttle and received space radiation doses between 0-74.1 milligrays. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health (LSAH) program at NASA Johnson Space Center. Mortality was compared with the US male population. Trends of mortality with dose were assessed using a logistic model, fitted by maximum likelihood. Only 32 (43.84 percent) of the 73 early astronauts have died. Standard mortality ratios (SMRs) for cancer (n=7, SMR=43.4, 95 percent CI 17.8, 84.9), all circulatory disease (n=7, SMR=33.2, 95 percent CI 13.7, 65.0), and ischemic heart disease (IHD) (n=5, SMR=40.1, 95 percent CI 13.2, 89.4) were significantly lower than for the US white male population. For cerebrovascular disease, the upper confidence interval for SMR included 100, indicating it was not significantly different from the US population (n=2, SMR = 77.0, 95 percent CI 9.4, 268.2). The power of the study is low and remains below 10 percent even when risks 10 times those reported in the literature are assumed. Due to small sample size, there is currently insufficient statistical power to evaluate space radiation exposure effects on mortality in NASA astronauts. In addition to a comprehensive longitudinal study of NASA astronauts, a research strategy of low dose epidemiology data integration with cell and animal studies should be utilized for space radiation risk assessment in the astronauts.

Elgart, S. R.↗

NASA NTRS2018

Radiation Exposure and Mortality from Cardiovascular Disease and Cancer in Early NASA Astronauts: Space for Exploration

Elgart, S. R.↗

NASA NTRS2006

Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal components and the brightness temperature principal components of the classes. Because the classes are stratified by the sea surface temperature and the echo-top-height estimator, the number of classes that are considered for retrieval is significantly smaller than the total number of classes, making the algorithm computationally efficient. The radiometer-only algorithm is applied to TMI observations, and precipitation estimates are compared with combined TRMM precipitation radar (PR) TMI reference estimates. The TMI-only algorithm, supported by the empirically derived database, produces estimates that are more consistent with the reference values than the precipitation estimates from the version-6 TRMM facility TMI algorithm. Cloud-resolving model simulations are used to assign a latent heating profile to each precipitation profile in the empirically derived database, making it possible to estimate latent heating using the radiometer-only algorithm. Although the evaluation of latent heating estimates in this study is preliminary, because realistic conditional probability distribution functions are attached to latent heating structures in the algorithm s database, a generally positive impact on latent heating estimation from passive microwave observations is expected.

Grecu, Mircea↗

NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗

DOE OSTI2021

An approach to characterizing spatial aspects of image system blur

Quantitative X-ray radiographic imaging systems that utilize a charged couple device (CCD) camera connected to a thick, monolithic scintillator can exhibit blur that varies spatially across the field of view, especially for thick scintillators used in pulse-power radiography of dynamically compressed objects. Here, a three-point approach to estimating and accounting for this effect is demonstrated by (a) using a local estimation technique to measure the effect of blurring a calibration object at key locations across the field of view, (b) combining each of the local estimates into a spatially varying blurring function via partitions of unity interpolation, and (c) resolving the effects of that blur on the image by solving an ill-posed inverse problem using a spatially varying regularization term. The technique is demonstrated on synthetic examples and actual radiographs collected at the Naval Research Laboratory’s (NRL)Mercury pulsed power facility.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Photogrammetry: Develop methods for detecting deviations from expected geometry of components in a glovebox environment (Lawrence Livermore National Laboratory Aging and Lifetimes Program FY23, Milestone 8651, Grading Criterion #4)

Measurements in glovebox environments are challenging to conduct. Currently deployed techniques are time consuming and provide limited information. These limitations make current disposition and future assessments of products challenging. In FY23 we developed methods for detecting deviations of components in a glovebox environment that address these shortcomings by rapidly collecting information-dense measurements. Conducted tests demonstrate that camera pose (position and orientation) can be derived for images utilized in the photogrammetry process. This information, in conjunction with common image processing techniques, enables automated detection and size estimation of surface features. First, image processing is used to identify marks, or localized regions, that standout from the surrounding area. Then, the physical size of the region can be estimated because scale can be determined for photogrammetry images. Development of this methods shows that photogrammetry can identify measurable deviations from expected geometries. Although measurement error when using this technique through a glovebox window still needs to be reduced, this capability shows promise for eliminating or reducing the use of tedious manual measurements.

42 ENGINEERING↗

NASA NTRS2019

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

NASA NTRSDate not supplied

Convective precipitation retrievals from space-borne dual frequency (Ka- and W-band) radar observations

The 2017 Decadal Survey highlighted Earth System Science themes, science and application questions that led to the inclusion aerosols (A), clouds, convection, and precipitation (CCP) in the list of designated observables (DOs) to be pursued within the decade following the survey. Multiple observing system architectures were considered during the NASA A-CCP study, and dual frequency Ka-W band radars have been identified as components of the most likely architectures due to their ability to significantly contribute to the achievement of the science objectives and their synergy with other essential instruments. We present an algorithm to estimate convective precipitation from dual frequency, Ka- and W-band, observations applicable to the observing system architectures considered in the A-CCP study. The algorithm is based on the radar profiling algorithm used within the operational NASA GPM combined algorithm but features an additional module that makes the retrieval problem well-posed in cases of severe attenuation and potential loss of signal below the freezing level. The additional module is developed from GPM combined retrievals and consists of a procedure that generates an ensemble of potential retrievals consistent with the portions of the Ka-band and W-band observation profiles above the noise level. The ensemble solution is refined based on estimates of Path Integrated Attenuation (PIA) from the Surface Reference Technique (SRT) and radiometric observations.

Mircea Grecu↗

DOE OSTI2022

Predicting tungsten erosion and leakage properties for the new V-shaped small angle slot divertor in DIII-D

Impurity transport modeling of the new tungsten (W)-coated, V-shaped small angle slot (SAS) divertor in the DIII-D tokamak was conducted using the SOLPS-ITER plasma edge code package and the DIVIMP impurity tracking code. The inboard baffle of the current SAS divertor will be shifted closer to the outboard baffle, creating a V-corner at the slot vertex. In addition, the outboard baffle will be coated with 10–15 μm of W for experiments studying high-Z sourcing and leakage in a closed divertor. Modeling of the 'SAS-VW' divertor predicts that these changes to the inner baffle will reduce W gross erosion by 40× relative to the existing SAS divertor when the outer strike point (OSP) is at the V-corner and the ion B × ∇B drift is towards the divertor, driven primarily by significant cooling near the slot vertex. Most W erosion in SAS-VW is expected to occur near the slot entrance, which may pose a higher risk to core contamination than W eroded deeper in the slot. Furthermore, adding a new sheath-based prompt redeposition model increases the sensitivity of redeposition estimates to near-target plasma conditions and may provide more accurate predictions of net erosion. Moving the OSP outboard from the slot vertex ~4 cm onto the W-coated region yields a 40× increase in the gross erosion rate and a 50% decrease in the core leakage fraction. Thus slight variations in strike point location may counteract the potential benefits of the tightly-baffled V slot on minimizing erosion. This impurity transport modeling provides useful guidance for future experiments on the SAS-VW divertor focused on high-Z erosion/redeposition, scrape-off layer transport, and core leakage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2015

Predicting Space Weather Effects on Close Approach Events

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Space Weather↗

DOE OSTI2023

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗

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↗

DOE OSTI2023

An adaptive synchronous extraction (ASE) method for estimating intensity and footprint of surface urban heat islands: A case study of 254 North American cities

The urban heat island (UHI) effect has attracted great attention due to its potential impacts on rapidly growing urban areas. Using remotely sensed estimates of land surface temperature (LST), a large number of studies have focused on the surface UHI (SUHI) effect, which can be characterized by its two fundamental properties: intensity and footprint. The SUHI intensity reflects the LST difference between the urban area and the background reference area (BRA), and the SUHI footprint indicates the spatial extent influenced by the heat island. Currently, numerous methods have been developed to estimate the SUHI intensity and footprint, but are still greatly challenged by three main issues. Namely, the discrepancy in BRA selection criterion brings great uncertainty to the estimated SUHI intensity, the estimation of SUHI footprint is largely constrained by the predefined models, and the quantification of SUHI effect is potentially influenced by several confounding factors. Here, we proposed an adaptive synchronous extraction (ASE) method, which is capable of adaptively selecting the most optimal BRA while removing the influence of confounding factors, and achieving synchronous estimation of SUHI intensity and footprint. We applied the ASE method to 254 North American cities and conducted an in-depth comparative analysis to discuss its applicability and benefits. The main results include: (1) The ASE method avoids the limitations of existing methods in BRA selection and model presetting, and shows resilience to parameter variations. This makes the ASE method highly applicable to quantify the SUHI intensity and footprint in cities with various thermal characteristics. (2) The ASE method can better highlight the spatial, seasonal and day-night contrasts in the estimated SUHI intensity. This superiority is particularly evident when comparing it to methods based on the equal-area buffer or the simplified urban-extent algorithm. (3) Confounding factors pose non-negligible impacts on the quantification of the SUHI effect. Typically, ignoring the influence of topographic relief or missing LST data can lead to an overall overestimation of the SUHI intensity, while not removing surrounding urban areas will cause some underestimation of the SUHI intensity. In conclusion, overall, the proposed ASE method provides a new generalizable tool for quantifying the SUHI effect, which has great potentials for future studies and urban climate assessments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1988

Shielding against debris

The damage to spacecraft caused by debris and design of the Space Station to minimize damage from debris are discussed. Although current estimates of the debris environment show that fragments bigger than 2 cm are not likely to hit the Space Station, orbital debris from about 0.5 mm to 2 cm will pose a hazard, especially on brittle surfaces, such as glass. Spacesuits are being designed to reduce debris caused dangers to astronauts during EVA. About 5 cm of high-strength aluminum are needed to prevent penetration by a 1 cm piece of aluminum with a mass near 1.5 g colliding at 10 km/sec. Because aluminum bumpers have the drawback of metallic debris ejected outward after a hypervelocity collision, the use of nonmetallic materials for bumpers is being studied. Methods of reducing the weight and volume of the shield for the Space Station are also being researched. A space station habitation module using bumpers has a 99.6 percent chance of avoiding penetration during its lifetime.

Cour-Palais, Burton G.↗