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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

VHF SoOp (Signal of Opportunity) Technology Demonstration for Soil Moisture Measurement Using Microwave Hydraulic Boom Truck Platform

A goal of this research is to test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a global direct surface soil moisture (SM) and RZSM measurement system over a variety of land covers. Knowledge of RZSM up to a depth of 1 meter and surface SM up to a depth of 0.05 meter on a global scale, at a spatial resolution of 1-10 km through moderate-to-heavy vegetation, is critical to understanding global water resources and the vertical moisture gradient in the Earths surface layer which controls moisture interactions between the soil, vegetation, and atmosphere. Current observations of surface SM from space by L-band radiometers (1.4 GHz) and radars (1.26 GHz) are limited to measurements of surface SM up to a depth of 0.05 meter through moderate amounts of vegetation. This limitation is mainly due to the inability of L-band signals to penetrate through dense vegetation and deep into the soil column. Satellite observations of the surface moisture conditions are coupled to sophisticated models which extrapolate the surface SM into the root zone, thus providing an indirect estimate rather than a direct measurement of RZSM. To overcome this limitation, low-frequency airborne radars operating at 435 MHz and 118 MHz have been investigated, since these lower frequencies should penetrate denser vegetation and respond to conditions deeper in the soil.

SoOp↗
DOE OSTI2014

Locally-smeared operator product expansions

We propose a "locally-smeared Operator Product Expansion" (sOPE) to decompose non-local operators in terms of a basis of locally-smeared operators. The sOPE formally connects nonperturbative matrix elements of smeared degrees of freedom, determined numerically using the gradient flow, to non-local operators in the continuum. The nonperturbative matrix elements do not suffer from power-divergent mixing on the lattice, provided the smearing scale is kept fixed in the continuum limit. The presence of this smearing scale prevents a simple connection to the standard operator product expansion and therefore requires the construction of a two-scale formalism. We demonstrate the feasibility of our approach using the example of real scalar field theory.

Monahan, Christopher↗
NASA NTRS2000

Evolution of thermotolerance in hot spring cyanobacteria of the genus Synechococcus

The extension of ecological tolerance limits may be an important mechanism by which microorganisms adapt to novel environments, but it may come at the evolutionary cost of reduced performance under ancestral conditions. We combined a comparative physiological approach with phylogenetic analyses to study the evolution of thermotolerance in hot spring cyanobacteria of the genus Synechococcus. Among the 20 laboratory clones of Synechococcus isolated from collections made along an Oregon hot spring thermal gradient, four different 16S rRNA gene sequences were identified. Phylogenies constructed by using the sequence data indicated that the clones were polyphyletic but that three of the four sequence groups formed a clade. Differences in thermotolerance were observed for clones with different 16S rRNA gene sequences, and comparison of these physiological differences within a phylogenetic framework provided evidence that more thermotolerant lineages of Synechococcus evolved from less thermotolerant ancestors. The extension of the thermal limit in these bacteria was correlated with a reduction in the breadth of the temperature range for growth, which provides evidence that enhanced thermotolerance has come at the evolutionary cost of increased thermal specialization. This study illustrates the utility of using phylogenetic comparative methods to investigate how evolutionary processes have shaped historical patterns of ecological diversification in microorganisms.

Synechococcus Group/classification/growth & develo↗
DOE OSTI2024

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2021

Modeling household online shopping demand in the U.S.: a machine learning approach and comparative investigation between 2009 and 2017

Despite the rapid growth of online shopping and research interest in the relationship between online and in-store shopping, national-level modeling and investigation of the demand for online shopping with a prediction focus remain limited in the literature. Here, this paper differs from prior work and leverages two recent releases of the U.S. National Household Travel Survey (NHTS) data for 2009 and 2017 to develop machine learning (ML) models, specifically gradient boosting machine (GBM), for predicting household-level online shopping purchases. The NHTS data allow for not only conducting nationwide investigation but also at the level of households, which is more appropriate than at the individual level given the connected consumption and shopping needs of members in a household. We follow a systematic procedure for model development including employing Recursive Feature Elimination algorithm to select input variables (features) in order to reduce the risk of model overfitting and increase model explainability. Among several ML models, GBM is found to yield the best prediction accuracy. Extensive post-modeling investigation is conducted in a comparative manner between 2009 and 2017, including quantifying the importance of each input variable in predicting online shopping demand, and characterizing value-dependent relationships between demand and the input variables. In doing so, two latest advances in machine learning techniques, namely Shapley value-based feature importance and Accumulated Local Effects plots, are adopted to overcome inherent drawbacks of the popular techniques in current ML modeling. The modeling and investigation are performed at the national level, with a number of findings obtained. The models developed and insights gained can be used for online shopping-related freight demand generation and may also be considered for evaluating the potential impact of relevant policies on online shopping demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

A volumetric approach to path-length measurements is essential when treating radiotherapy with modulated beams

The established dosimetric benefits of intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy have lead to their increased use in prostate radiotherapy. Complimenting these techniques, volumetric image guidance has supported increased positional accuracy. In addition, 3-dimensional image guidance has also allowed for assessment of potential dosimetric variation that can be attributed to a deformation of either internal or external structures, such as rectal distension or body contour. Compounding these issues is the variation of tissue density through which the new field position passes and also the variation of dose across a modulated beam. Despite the growing level of interest in this area, there are only a limited number of articles that examine the effect of a variation in beam path length, particularly across a modulated field. IMRT and volumetric-modulated radiation therapy (VMAT) fields are dynamic in nature, and the dose gradient within these fields is variable. Assessment of variation of path length away from the beam's central axis and across the entire field is vital where there is considerable variation of dose within the field, such as IMRT and VMAT. In these cases, reliance on the traditional central axis to focus skin distances is no longer appropriate. This article discusses these more subtle challenges that may have a significant clinical effect if left unrecognized and undervalued.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Advances in Kriging-Based Autonomous X-Ray Scattering Experiments

Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest. We have recently demonstrated a generalized approach to autonomous experimental control, based on generating a surrogate model to interpolate experimental data, and a corresponding uncertainty model, which are computed using a Gaussian process regression known as ordinary Kriging (OK). We demonstrated the successful application of this method to exploring materials science problems using x-ray scattering measurements at a synchrotron beamline. Here, we report several improvements to this methodology that overcome limitations of traditional Kriging methods. The variogram underlying OK is global and thus insensitive to local data variation. We augment the Kriging variance with model-based measures, for instance providing local sensitivity by including the gradient of the surrogate model. As with most statistical regression methods, OK minimizes the number of measurements required to achieve a particular model quality. However, in practice this may not be the most stringent experimental constraint; e.g. the goal may instead be to minimize experiment duration or material usage. We define an adaptive cost function, allowing the autonomous method to balance information gain against measured experimental cost. We provide synthetic and experimental demonstrations, validating that this improved algorithm yields more efficient autonomous data collection.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Modeling quantum yield, emittance, and surface roughness effects from metallic photocathodes

Here, detailed measurements of momentum distributions of emitted electrons have allowed the investigation of the thermal limit of the transverse emittance from metal photocathodes. Furthermore, recent developments in material design and growth have resulted in photocathodes that can deliver high quantum efficiency and are sufficiently robust to use in high electric field gradient photoinjectors and free electron lasers. The growth process usually produces photoemissive material layers with rough surface profiles that lead to transverse accelerating fields and possible work function variations, resulting in emittance growth. To better understand the effects of temperature, density of states, and surface roughness on the properties of emitted electrons, we have developed realistic three-dimensional models for photocathode materials with grated surface structures. They include general modeling of electron excitation due to photon absorption, charge transport, and emission from flat and rough metallic surfaces. The models also include image charge and field enhancement effects. We report results from simulations with flat and rough surfaces to investigate how electron scattering, controlled roughness, work function variation, and field enhancement affect emission properties. Comparison of simulation results with measurements of the quantum yield and transverse emittance from flat Sb emission surfaces shows the importance of including efficient modeling of photon absorption, temperature effects, and the material density of states to achieve agreement with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Discovering Active Subspaces for High-Dimensional Computer Models

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. While sensible in some settings, this approach has obvious drawbacks. Recent research has demonstrated that active subspace calculations can be obtained in closed form, conditional on a Gaussian process (GP) surrogate, which can be limiting in high-dimensional settings for computational reasons. In this paper, we produce the relevant calculations for a more general case when the model of interest is a linear combination of tensor products. These general equations can be applied to the GP, recovering previous results as a special case, or applied to the models constructed by other regression techniques including multivariate adaptive regression splines (MARS). Furthermore, using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. In one real-world example, we obtain the active subspace of a radiation-transport code with 240 inputs and 9,372 model runs in under half an hour.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Molecular cloud-scale star formation in NGC 300

We present the results of a galaxy-wide study of molecular gas and star formation in a sample of 76 H II regions in the nearby spiral galaxy NGC 300. We have measured the molecular gas at 250 pc scales using pointed CO(J = 2-1) observations with the Atacama Pathfinder Experiment telescope. We detect CO in 42 of our targets, deriving molecular gas masses ranging from our sensitivity limit of ∼10{sup 5} M {sub ☉} to 7 × 10{sup 5} M {sub ☉}. We find a clear decline in the CO detection rate with galactocentric distance, which we attribute primarily to the decreasing radial metallicity gradient in NGC 300. We combine Galaxy Evolution Explorer far-ultraviolet, Spitzer 24 μm, and Hα narrowband imaging to measure the star formation activity in our sample. We have developed a new direct modeling approach for computing star formation rates (SFRs) that utilizes these data and population synthesis models to derive the masses and ages of the young stellar clusters associated with each of our H II region targets. We find a characteristic gas depletion time of 230 Myr at 250 pc scales in NGC 300, more similar to the results obtained for Milky Way giant molecular clouds than the longer (>2 Gyr) global depletion times derived for entire galaxies and kiloparsec-sized regions within them. This difference is partially due to the fact that our study accounts for only the gas and stars within the youngest star-forming regions. We also note a large scatter in the NGC 300 SFR-molecular gas mass scaling relation that is furthermore consistent with the Milky Way cloud results. This scatter likely represents real differences in giant molecular cloud physical properties such as the dense gas fraction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

CONSTRAINED EVOLUTION OF A RADIALLY MAGNETIZED PROTOPLANETARY DISK: IMPLICATIONS FOR PLANETARY MIGRATION

We consider the inner ∼1 AU of a protoplanetary disk (PPD) at a stage where angular momentum transport is driven by the mixing of a radial magnetic field into the disk from a T Tauri wind. Because the radial profile of the imposed magnetic field is well constrained, a constrained calculation of the disk mass flow becomes possible. The vertical disk profiles obtained in Paper I imply a stronger magnetization in the inner disk, faster accretion, and a secular depletion of the disk material. Inward transport of solids allows the disk to maintain a broad optical absorption layer even when the grain abundance becomes too small to suppress its ionization. Thus, a PPD may show a strong mid- to near-infrared spectral excess even while its mass profile departs radically from the minimum-mass solar nebula. The disk surface density is buffered at ∼30 g cm{sup −2}; below this, X-rays trigger magnetorotational turbulence at the midplane strong enough to loft millimeter- to centimeter-sized particles high in the disk, followed by catastrophic fragmentation. A sharp density gradient bounds the inner depleted disk and propagates outward to ∼1–2 AU over a few megayears. Earth-mass planets migrate through the inner disk over a similar timescale, whereas the migration of Jupiters is limited by the supply of gas. Gas-mediated migration must stall outside 0.04 AU, where silicates are sublimated and the disk shifts to a much lower column. A transition disk emerges when the dust/gas ratio in the MRI-active layer falls below X{sub d} ∼ 10{sup −6} (a{sub d}/μm), where a{sub d} is the grain size.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Cohort organized learning: clustering through agreement

In this article we describe cohort organized learning (CoOL), a method for clustering data without explicit distance or similarity computations. Herein, we will describe CoOL, derive the gradients determined by expectation maximization to train the networks, show how to monitor convergence during training and evaluate the clusters after training, and discuss a series of examples and use cases. We also discuss CoOL’s limitations and future prospects on related tasks. Because CoOL uses neural networks to estimate the clusters, it can be used to cluster any data that can be made compatible and we illustrate this on vector data and images.

clustering↗
DOE OSTI2017

Diazotroph Community Characterization via a High-Throughput nifH Amplicon Sequencing and Analysis Pipeline

The dinitrogenase reductase gene ( nifH ) is the most widely established molecular marker for the study of nitrogen-fixing prokaryotes in nature. A large number of PCR primer sets have been developed for nifH amplification, and the effective deployment of these approaches should be guided by a rapid, easy-to-use analysis protocol. Bioinformatic analysis of marker gene sequences also requires considerable expertise. In this study, we advance the state of the art for nifH analysis by evaluating nifH primer set performance, developing an improved amplicon sequencing workflow, and implementing a user-friendly bioinformatics pipeline. Furthermore, the developed amplicon sequencing workflow is a three-stage PCR-based approach that uses established technologies for incorporating sample-specific barcode sequences and sequencing adapters. Based on our primer evaluation, we recommend the Ando primer set be used with a modified annealing temperature of 58°C, as this approach captured the largest diversity of nifH templates, including paralog cluster IV/V sequences. To improve nifH sequence analysis, we developed a computational pipeline which infers taxonomy and optionally filters out paralog sequences. In addition, we employed an empirical model to derive optimal operational taxonomic unit (OTU) cutoffs for the nifH gene at the species, genus, and family levels. A comprehensive workflow script named TaxADivA (TAXonomy Assignment and DIVersity Assessment) is provided to ease processing and analysis of nifH amplicons. Our approach is then validated through characterization of diazotroph communities across environmental gradients in beach sands impacted by the Deepwater Horizon oil spill in the Gulf of Mexico, in a peat moss-dominated wetland, and in various plant compartments of a sugarcane field. IMPORTANCE: Nitrogen availability often limits ecosystem productivity, and nitrogen fixation, exclusive to prokaryotes, comprises a major source of nitrogen input that sustains food webs. The nifH gene, which codes for the iron protein of the nitrogenase enzyme, is the most widely established molecular marker for the study of nitrogen-fixing microorganisms (diazotrophs) in nature. In this study, a flexible sequencing/analysis pipeline, named TaxADivA, was developed for nifH amplicons produced by Illumina paired-end sequencing, and it enables an inference of taxonomy, performs clustering, and produces output in formats that may be used by programs that facilitate data exploration and analysis. Diazotroph diversity and community composition are linked to ecosystem functioning, and our results advance the phylogenetic characterization of diazotroph communities by providing empirically derived nifH similarity cutoffs for species, genus, and family levels. Thus, the utility of our pipeline is validated for diazotroph communities in a variety of ecosystems, including contaminated beach sands, peatland ecosystems, living plant tissues, and rhizosphere soil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Giant Virus Infection Signatures Are Modulated by Euphotic Zone Depth Strata and Iron Regimes of the Subantarctic Southern Ocean

Viruses can alter the abundance, evolution, and metabolism of microorganisms in the ocean, playing a key role in water column biogeochemistry and global carbon cycles. Large efforts to measure the contribution of eukaryotic microorganisms (e.g., protists) to the marine food web have been made, yet the in situ activities of the ecologically relevant viruses that infect these organisms are not well characterized. Viruses within the phylum Nucleocytoviricota (“giant viruses”) are known to infect a diverse range of ecologically relevant marine protists, yet how these viruses are influenced by environmental conditions remains under-characterized. By employing metatranscriptomic analyses of in situ microbial communities along a temporal and depthresolved gradient, we describe the diversity of giant viruses at the Southern Ocean Time Series (SOTS), a site within the subpolar Southern Ocean. Using a phylogeny-guided taxonomic assessment of detected giant virus genomes and metagenome-assembled genomes, we observed depth-dependent structuring of divergent giant virus families mirroring dynamic physicochemical gradients in the stratified euphotic zone. Analyses of transcribed metabolic genes from giant viruses suggest viral metabolic reprogramming of hosts from the surface to a 200-m depth. Lastly, using on-deck incubations reflecting a gradient of iron availability, we show that modulating iron regimes influences the activity of giant viruses in the field. Specifically, we show enhanced infection signatures of giant viruses under both iron-replete and iron-limited conditions. Collectively, these results expand our understanding of how the water column’s vertical biogeography and chemical surroundings affect an important group of viruses within the Southern Ocean

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AADL: Anderson Accelerated Deep Learning

We propose a stable, distributed approach to perform AA that accelerates the convergence rate of stochastic first-order optimizers to train neural networks. Differently from previous works, we do not alter neither the scheme to perform AA nor the loss function minimized during the training. To improve robustness against stagnation, we customize general guidelines that suggest to relax the frequency of AA corrections by performing AA only at the end of an entire training epoch. To improve robustness of AA against the stochastic oscillations of first-order optimizers, we average the gradients computed on consecutive stochastic optimization updates. The improved regularity of the converging sequence and the reduced amplitude of stochastic oscillations across consecutive optimization steps allows AA to efficiently extrapolate an improved converging sequence, thereby overcoming limitations of existing approaches to perform AA on stochastic optimization.

Lupo Pasini, Massimiliano [Oak Ridge National Lab.↗
DOE OSTI2026

Thermal Studies of CMS High-Granularity Calorimeter (HGCAL) Cassettes for the HL-LHC Upgrade

The CMS High Granularity Calorimeter (HGCAL) is a key endcap upgrade for the High-Luminosity LHC, designed to operate in an environment of extreme radiation and high particle rates. Each HGCAL cassette integrates silicon and scintillator modules, front-end ASICs, and a copper cooling plate that provides both mechanical integrity and thermal coupling using two-phase CO₂ cooling. Stable and uniform temperature control is essential to ensure reliable performance of the front-end electronics and to limit radiation-induced leakage currents in the silicon sensors. We present results from thermal characterization studies of pre-series HGCAL cassettes assembled and tested at Fermilab. Embedded RTD/PT1000 temperature sensors were used to measure gradients across copper cooling plates, module layers, and cassette edges under powering conditions representative of operation. The measured thermal behavior demonstrates effective heat transport through the cassette stack and highlights small but systematic variations correlated with geometry and assembly tolerances. These results validate the cooling performance of HGCAL cassettes.

Wang, Jinglu [Northwestern U.]↗
NASA NTRS1991

Distributed-Computer System Optimizes SRB Joints

Initial calculations of redesign of joint on solid rocket booster (SRB) that failed during Space Shuttle tragedy showed redesign increased weight. Optimization techniques applied to determine whether weight could be reduced while keeping joint closed and limiting stresses. Analysis system developed by use of existing software coupling structural analysis with optimization computations. Software designed executable on network of computer workstations. Took advantage of parallelism offered by finite-difference technique of computing gradients to enable several workstations to contribute simultaneously to solution of problem. Key features, effective use of redundancies in hardware and flexible software, enabling optimization to proceed with minimal delay and decreased overall time to completion.

Rogers, James L., Jr.↗
NASA NTRS1991

Pulmonary function in microgravity: KC-135 experience

We have commenced a KC-135 program that parallels and proceeds our Spacelab (SLS-1) pulmonary function experiment. Our first task was to elucidate the affect of normal gravitation on the shape of the maximum expiratory flow volume (MEFV) curve. Nine normal subjects performed multiple MEFV maneuvers at 0-G, 1-G, and approximately 1.7-G. The MEFV curves for each subject were filtered, aligned at RV, and ensemble-averaged to produce an average MEFV curve for each state, allowing differences to be studied. Most subjects showed a decrease in the FVC at 0-G, which we attribute to an increased intrathoracic blood volume. In most of these subjects, the mean lung volume associated with a given flow was lower at 0-G, over about the upper half of the vital capacity. This is similar to the change previously reported during heat out immersion and is consistent with the known affect of engorgement of the lung with blood, on elastic recoil. There were also consistent but highly individual changes in the position and magnitude of detailed features of the curve, the individual patterns being similar to those previously reported on transition from the erect to the supine position. This supports the idea that the location and motion of choke points which determine the detailed individual configuration of MEFV curves, can be significantly influenced by gravitational forces, presumably via the effects of change in longitudinal tension on local airway pressure-diameter behavior and wave speed. We have developed a flight mass spectrometer and have commenced a study of single breath gradients in gas exchange, inert gas washouts, and rebreathing cardiac outputs and lung volumes at 0-G, 1-G, and 1.7-G. Comparison of our results with those from SLS-1 should identify the opportunities and limitations of the KC-135 as an accessible microgravity resource.

Guy, Harold J.↗