Search NASA⌕ Search

SEARCH · Search NASA

Results for “sample consumption”

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.

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

At least 523 records · Page 29

Quantile-dependent expressivity of serum C-reactive protein concentrations in family sets

“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., C-reactive protein, CRP) is high or low relative to its distribution. We have previously shown that the heritabilities ( h 2 ) of coffee and alcohol consumption, postprandial lipemia, lipoproteins, leptin, adiponectin, adiposity, and pulmonary function are quantile-specific. Whether CRP heritability is quantile-specific is currently unknown. Methods Serum CRP concentrations from 2,036 sibships and 6,144 offspring-parent pairs were analyzed from the Framingham Heart Study. Quantile-specific heritability from full-sib (β FS , h 2 ={(1 + 8r spouse β FS ) 0.5 - 1}/(2r spouse )) and offspring-parent regression slopes (β OP , h 2 = 2β OP /(1 + r spouse )) were estimated robustly by quantile regression with nonparametric significance determined from 1,000 bootstrap samples. Results Quantile-specific h 2 (±SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted CRP distribution when estimated from β OP ( P trend = 0.0004): 0.02 ± 0.01 at the 10th, 0.04 ± 0.01 at the 25th, 0.10 ± 0.02 at the 50th, 0.20 ± 0.05 at the 75th, and 0.33 ± 0.10 at the 90th percentile, and when estimated from β FS ( P trend = 0.0008): 0.03±0.01 at the 10th, 0.06 ± 0.02 at the 25th, 0.14 ± 0.03 at the 50th, 0.24 ± 0.05 at the 75th, and 0.53 ± 0.21 at the 90th percentile. Conclusion Heritability of serum CRP concentration is quantile-specific, which may explain or contribute to the inflated CRP differences between CRP (rs1130864, rs1205, rs1800947, rs2794521, rs3091244), FGB (rs1800787), IL-6 (rs1800795, rs1800796), IL6R (rs8192284), TNF- α (rs1800629) and APOE genotypes following CABG surgery, stroke, TIA, curative esophagectomy, intensive periodontal therapy, or acute exercise; during acute coronary syndrome or Staphylococcus aureus bacteremia; or in patients with chronic rheumatoid arthritis, diabetes, peripheral arterial disease, ankylosing spondylitis, obesity or inflammatory bowel disease or who smoke.

59 BASIC BIOLOGICAL SCIENCES↗

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗

Geochemical and Microbial Dynamics of Hydrogen in a Methane Storage Reservoir

Hydrogen has been identified as a flexible energy carrier with zero or negative emission across multiple energy systems, and existing natural gas infrastructure could be leveraged if hydrogen gas (H2) was blended with methane (CH4). For example, subsurface methane storage reservoirs could be slightly modified to also store hydrogen if a methane/hydrogen blend were injected. However, the compatibility of methane storage reservoirs to include H2 injection has not been fully demonstrated, and this could lead to geochemical and microbiological reactions that alter the reservoir and stored gas content. It is essential that we understand the impact of H2 gas on the biogeochemistry of subsurface storage reservoirs before deploying large-scale H2-CH4 storage, We collected produced fluid from two separate methane storage reservoirs in the Southwestern US. First, we completed a baseline analysis of the biogeochemistry through qPCR, 16S rRNA sequencing, metagenomic sequencing, and geochemical analysis. Each reservoir was found to have unique geochemical conditions and a unique microbial community structure, with Site 1 having a higher TDS and an abundance of Shewanella and Site 2 having a lower TDS and high abundance of Eubacterium and Acetobacterium. Next, we ran a series of high pressure, high temperature reactors under hydrogen storage conditions with the biological sample from one of the storage reservoirs and a 20% H2-80% CH4 gas blend for up to 7 days. Our results show a decrease of hydrogen by 5% in reactors as early as 1-3 days. Previous hydrogen storage work has linked subsurface microorganisms with methanogenesis hydrogen sulfide production, acid production, and microbial corrosion. Our results show minimal change in the fluid chemistry, with the exception of a decrease in dissolved sulfate concentrations. Taxonomic sequencing demonstrated the presence of microorganisms capable of iron redox, acid generation, and hydrogen sulfide production throughout the reactors, suggesting microbial hydrogen consumption may occur through various metabolic pathways. This work demonstrates that site-specific geochemistry and microbiology may impact the efficiency of hydrogen storage in methane storage reservoirs.

environmental microbiology↗

Review of thermal comfort infused with the latest big data and modeling progresses in public health

Thermal environment is important for both occupants’ comfort and health. Previously, the impacts of thermal environment were explored in the areas of thermal comfort and public health separately. This paper aims to bridge both disciplines by examining the correlation between comfort temperature and Minimum Mortality Temperature (MMT), which is a key index quantifying the association of health and weather temperature, through literature review and data-driven approach. It was found that the MMT data obtained from the public health area are generally in good agreement with the thermal neutral temperatures from the comfort perspective. The MMT data range from 17.2 °C to 30 °C, which are similar to the thermal neutral temperatures ranging from 19.5 °C to 30 °C based on the global field tests. Moreover, the MMT data demonstrate the potential to capture some complex distribution patterns of the field comfort data. The introduction of the health-temperature data could assist the intensive field experiments and modeling efforts and complement the thermal comfort dataset, which suffers from the problems of limited sample size. Some discrepancies between the two datasets were identified as well. The contextual factors other than the climate factor which may cause such discrepancies, such as socio-economics, population densities, etc. should be analyzed to enable the potential application of the health-temperature data and modeling to thermal comfort and health studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reducing ridesourcing empty vehicle travel with future travel demand prediction

Ridesourcing services provide alternative mobility options in several cities. Their market share has grown exponentially due to the convenience they provide. The use of such services may be associated with car-light or car-free lifestyles. However, there are growing concerns regarding their impact on urban transportation operations performance due to empty, unproductive miles driven without a passenger (commonly referred to as deadheading). This paper is motivated by the potential to reduce deadhead mileage of ridesourcing trips by providing drivers with information on future ridesourcing trip demand. Future demand information enables the driver to wait in place for the next rider’s request without cruising around and contributing to congestion. A machine learning model is employed to predict hourly and 10-minute future interval travel demand for ridesourcing at a given location. Using future demand information, we propose algorithms to (i) assign drivers to act on received demand information by waiting in place for the next rider, and (ii) match these drivers with riders to minimize deadheading distance. Real-world data from ridesourcing providers in Austin, TX (RideAustin) and Chengdu, China (DiDi Chuxing) are leveraged. Results show that this process achieves 68%–82% and 53%–60% reduction of trip-level deadheading miles for the RideAustin and DiDi Chuxing sample operations respectively, under the assumption of unconstrained availability of short-term parking. Deadheading savings increase slightly as the maximum tolerable waiting time for the driver increases. Further, it is observed that significant deadhead savings per trip are possible, even when a small percent of the ridesourcing driver pool is provided with future ridesourcing demand information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Microwave absorption through the martensitic and Curie transitions in Ni 45 Cr 5 Mn 37 In 13

We have investigated the electron spin resonance (ESR) of the Ni 45 Cr 5 Mn 37 In 13 Heusler alloy near the structural and magnetic phase transition temperatures. Ni 45 Cr 5 Mn 37 In 13 is characterized by a first order magnetostructural (martensitic) transition (MST) with magneto-responsive properties such as magnetoresistance, Hall and magnetocaloric effects, etc., in the vicinity of the MST. Since the details and origins of these behaviors are not well understood, we used a technique beyond magnetometry, i.e., “microwave absorption”, to reveal new information. ESR studies of Ni 45 Cr 5 Mn 37 In 13 shows that this compound is characterized by wide absorption spectra at temperatures greater than 250 K that depend on the angle of the magnetic field relative to the normal to the sample plate (α) and temperature (T). Two local maxima at about 5 and 6 kOe were detected for α close to zero degrees near the martensitic transition and Curie temperatures. In conclusion, the absorption spectra are discussed along with the results of the structural and magnetic studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Properties and reaction mechanism of phosphoric acid activated metakaolin geopolymer at varied curing temperatures

Reaction mechanism of phosphoric activated metakaolin is studied by techniques of calorimetry, ICP-OES, FTIR and NMR taking curing temperature and [H{sub 3}PO{sub 4}] as variables. A two-stage curing method including pre-curing at 40 °C for 24 h and second curing at 60/80 °C for another 24 h effectively mitigates thermal-cracking of the obtained silico-aluminate phosphate (SAP) samples, whose maximum compressive strength reaches 120 MPa. Dealumination of metakaolin in H{sub 3}PO{sub 4} solution produces low aluminate-containing silicate units and subsequently condensation of silicate tetrahedrons occurs. Higher temperature and H{sub 3}PO{sub 4} concentration accelerate the two processes. After complete reaction, A{sub VI} structure from metakaolin disappears and the dissolved Al preferably forms Al{sub VI}-O-P units. During reaction, metastable P-O-P intermediate appears in SAPs with higher P/Al ratio and finally transforms into Al-O-P structure upon PO{sub 4}{sup 3−} consumption. Phosphate units as P(OAl){sub x}(H{sub 2}O){sub 4-x} are connected with Si or Al structure units. Major structural units of the SAPs include Al-O-P, Si-O-P, Si-O-Si, and Si-O-Al.

36 MATERIALS SCIENCE↗

Evaluating performance of different generative adversarial networks for large-scale building power demand prediction

We report as an unsupervised-learning data-driven model, Generative Adversarial Networks (GANs) have recently attracted a lot of attention for various applications. There is potential to apply GANs for large-scale building power demand prediction, which is needed for power grid operation. However, there are many GAN variations and it is unclear which GAN is suitable for this application. To answer this question, this paper identifies five promising GANs (Original GAN, cGAN, SGAN, InfoGAN, and ACGAN) and evaluates their performance for predicting building power demand at a large scale. Physics-based building energy models are developed to generate training and reference data. A new evaluation indicator that combines accuracy and reproducibility is proposed to evaluate the performance of different GANs in predicting building power demand. The results show that SGAN and InfoGAN are not suitable because they cannot control the number of generated building samples for different building types. The prediction performance among the Original GAN, cGAN, and ACGAN can vary depending on training sample sizes and number of building types. If the training sample size is sufficiently large, Original GAN and cGAN can predict building power demand more accurately than ACGAN with the same number of samples. If training samples are limited, Original GAN provides better accuracy than cGAN and ACGAN. When the number of building types increase, the prediction accuracy increases for cGAN, decreases for ACGAN, and remains the same for Original GAN. As a result, cGAN and Original GAN are recommended for large-scale building power demand prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A compendium of bacterial and archaeal single-cell amplified genomes from oxygen deficient marine waters

Oxygen-deficient marine waters referred to as oxygen minimum zones (OMZs) or anoxic marine zones (AMZs) are common oceanographic features. They host both cosmopolitan and endemic microorganisms adapted to low oxygen conditions. Microbial metabolic interactions within OMZs and AMZs drive coupled biogeochemical cycles resulting in nitrogen loss and climate active trace gas production and consumption. Global warming is causing oxygen-deficient waters to expand and intensify. Therefore, studies focused on microbial communities inhabiting oxygen-deficient regions are necessary to both monitor and model the impacts of climate change on marine ecosystem functions and services. Here we present a compendium of 5,129 single-cell amplified genomes (SAGs) from marine environments encompassing representative OMZ and AMZ geochemical profiles. Of these, 3,570 SAGs have been sequenced to different levels of completion, providing a strain-resolved perspective on the genomic content and potential metabolic interactions within OMZ and AMZ microbiomes. Hierarchical clustering confirmed that samples from similar oxygen concentrations and geographic regions also had analogous taxonomic compositions, providing a coherent framework for comparative community analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Microstructure characterization of electric field assisted sintering (EFAS) sintered metallic and ceramic materials using local thermal diffusivity measurement

Electric Field Assisted Sintering (EFAS, also referred to as spark plasma sintering) is a powerful technology for the consolidation of powder materials. The high heating rate during the sintering process is critical for minimizing energy consumption, but it can also cause microstructure heterogeneities in sintered parts, such as spatially varied porosity. The examination of localized porosity usually requires the use of a scanning electron microscope with a carefully prepared surface. In this paper, photothermal radiometry is used to measure local thermal diffusivity and extract localized porosity of EFAS-sintered parts by using a percolation-threshold model. Applying this approach, we identified the radial position-dependent porosity variation in EFAS parts, which is likely formed due to the large temperature gradient during the sintering process. This approach has a unique advantage because it can measure samples with minimal or no surface preparation, enabling the possibility of in situ characterization in EFAS with proper system modification. Necessary modifications on the measurement approach for EFAS deployment and in situ characterization are also discussed.

36 MATERIALS SCIENCE↗

Diverse and unconventional methanogens, methanotrophs, and methylotrophs in metagenome-assembled genomes from subsurface sediments of the Slate River floodplain, Crested Butte, CO, USA

We use metagenome-assembled genomes (MAGs) to understand single-carbon (C1) compound-cycling—particularly methane-cycling—microorganisms in montane riparian floodplain sediments. We generated 1,233 MAGs (>50% completeness and <10% contamination) from 50- to 150-cm depth below the sediment surface capturing the transition between oxic, unsaturated sediments and anoxic, saturated sediments in the Slate River (SR) floodplain (Crested Butte, CO, USA). We recovered genomes of putative methanogens, methanotrophs, and methylotrophs (n = 57). Methanogens, found only in deep, anoxic depths at SR, originate from three different clades (Methanoregulaceae, Methanotrichaceae, and Methanomassiliicoccales), each with a different methanogenesis pathway; putative methanotrophic MAGs originate from within the Archaea (Candidatus Methanoperedens) in anoxic depths and uncultured bacteria (Ca. Binatia) in oxic depths. Genomes for canonical aerobic methanotrophs were not recovered. Ca. Methanoperedens were exceptionally abundant (~1,400× coverage, >50% abundance in the MAG library) in one sample that also contained aceticlastic methanogens, indicating a potential C1/methane-cycling hotspot. Ca. Methylomirabilis MAGs from SR encode pathways for methylotrophy but do not harbor methane monooxygenase or nitrogen reduction genes. Comparative genomic analysis supports that one clade within the Ca. Methylomirabilis genus is not methanotrophic. The genetic potential for methylotrophy was widespread, with over 10% and 19% of SR MAGs encoding a methanol dehydrogenase or substrate-specific methyltransferase, respectively. MAGs from uncultured Thermoplasmata archaea in the Ca. Gimiplasmatales (UBA10834) contain pathways that may allow for anaerobic methylotrophic acetogenesis. Overall, MAGs from SR floodplain sediments reveal a potential for methane production and consumption in the system and a robust potential for methylotrophy.

58 GEOSCIENCES↗

Low-Cost Bio-Based Carbon Fibers for High Temperature Processing

GrafTech International Holdings Inc. (GTI), under Award No. DE-EE0005779, worked with Oak Ridge National Laboratory (ORNL) under CRADA No. NFE-15-05807 to develop lignin-based carbon fiber (LBCF) technology and to demonstrate LBCF performance in high-temperature products and applications. This work was unique and different from other reported LBCF work in that this study was application-focused and scalability-focused. Accordingly, the executed work was based on meeting criteria based on technology development, cost, and application suitability. High-temperature carbon fiber based insulation is used in energy intensive industries, such as metal heat treating and ceramic and semiconductor material production. Insulation plays a critical role in achieving high thermal and process efficiency, which is directly related to energy usage, cost, and product competitiveness. Current high temperature insulation is made with petroleum based carbon fibers, and one goal of this protect was to develop and demonstrate an alternative lignin (biomass) based carbon fiber that would achieve lower cost, CO2 emissions, and energy consumption and result in insulation that met or exceeded the thermal efficiency of current commercial insulation. In addition, other products were targeted to be evaluated with LBCF. As the project was designed to proceed in stages, the initial focus of this work was to demonstrate lab-scale LBCF from at least 4 different lignin precursor feedstock sources that could meet the estimated production cost of $5.00/pound and have ash level of less than 500 ppm in the carbonized insulation-grade fiber. Accordingly, a preliminary cost model was developed based on publicly available information. The team demonstrated that 4 lignin samples met the cost criteria. In addition, the ash level for the 4 carbonized lignin samples was below 500 ppm. Processing as-received lignin to produce a high purity lignin fiber was a significant accomplishment in that most industrial lignin, prior to purification, had greater than 4X the ash level needed for this project, and prior to this work there was not a clear path of how to achieve the purity target. The lab scale development of LBCF was performed with a specific functional application in mind, specifically for high temperature rigid insulation. GTI is a consumer of foreign-sourced pitch and rayon based carbon fibers for use in its high temperature insulation products, and the motivation was that LBCF had potential to decrease costs and increase product competitiveness in the marketplace through lowered raw material costs, lowered energy costs, and decreased environmental footprint. At the end of this project, the Technology Readiness Level (TRL) remained at 5 for LBCF in high temperature insulation.

09 BIOMASS FUELS↗

Automotive Gas Turbine Power System-Performance Analysis Code

An open cycle gas turbine numerical modelling code suitable for thermodynamic performance analysis (i.e. thermal efficiency, specific fuel consumption, cycle state points, working fluid flowrates etc.) of automotive and aircraft powerplant applications has been generated at the NASA Lewis Research Center's Power Technology Division. The use this code can be made available to automotive gas turbine preliminary design efforts, either in its present version, or, assuming that resources can be obtained to incorporate empirical models for component weight and packaging volume, in later version that includes the weight-volume estimator feature. The paper contains a brief discussion of the capabilities of the presently operational version of the code, including a listing of input and output parameters and actual sample output listings.

Juhasz, Albert J.↗

Assessment of Model Outcomes Between the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT)

The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.

Matthew T Prelich↗

Process-based approach for the detection of deep gas invading the surface

The present invention includes a method for determining the level of deep gas in a near surface formation that includes: measuring CO.sub.2, O.sub.2, CH.sub.4, and N.sub.2 levels in percent by volume from one or more surface or near surface geological samples; adding the water vapor content to the measured CO.sub.2, O.sub.2, CH.sub.4, and N.sub.2 levels in percent by volume; normalizing the gas mixture to 100% by volume or 1 atmospheric total pressure; and determining the ratios of: O.sub.2 versus CO.sub.2 to distinguish in-situ vadose zone CO.sub.2 from exogenous deep leakage CO.sub.2; CO.sub.2 versus N.sub.2 to distinguish whether CO.sub.2 is being removed from the near surface formation or CO.sub.2 is added from an exogenous deep leakage input; or CO.sub.2 versus N.sub.2/O.sub.2 to determine the degree of oxygen influx, consumption, or both; wherein the ratios are indicative of natural in situ CO.sub.2 or CO.sub.2 from the exogenous deep leakage input.

47 OTHER INSTRUMENTATION↗

On-the-Fly Treatment of Temperature Dependent Cross Sections in the Unresolved Resonance Regions in RMC Code

Monte Carlo method can provide high fidelity neutronics analysis of different nuclear reactors, owing to its advantages of the flexible geometry modeling and the use of continuous-energy nuclear cross sections. It can also be coupled with thermal-hydraulics codes to consider the feedback. For thermal reactors such as PWR and HTGR, two main temperature effects should be considered. The first is the effect of thermal motion of target nuclei in resolved resonance energy regions, which is known as Doppler effect. The second is the thermal scattering and bound effect in thermal energy regions. The traditional approach of pre-generated cross sections has difficulty in memory footprint for detailed temperature modelling in multi-physics calculations. Recently, on-the-fly (OTF) technique has been proposed in order to reduce the memory consumption for both resolved resonance energy and thermal energy. For fast reactors calculations, the temperature dependence of cross sections in the unresolved resonance energy regions is also important. However, less attention was paid to the unresolved resonance regions compared with resolved resonance energy and thermal energy. In this paper, the on-the-fly temperature treatment of cross sections in unresolved resonance regions was proposed and developed in RMC codes. The results show that the on-the-fly treatment has high efficiency and satisfactory fidelity. The on-the-fly treatment of unresolved resonance region was also combined with the target motion sampling (TMS) method for resolved resonance energy. The formats of libraries were changed, in which the probability tables were separated from the cross sections. Then the interpolation of probability table was performed on-the-fly during the transport routine. The results show that the on-the-fly treatment has high efficiency and satisfactory fidelity. The on-the-fly treatment of unresolved resonance region was also combined with the target motion sampling (TMS) method for resolved resonance energy, showing that TMS method is effective and accurate for cross sections treatment in resolved resonance energy regions. The memory saving of the on-the-fly treatment is also considerable. For the high-fidelity 'transport-burnup-thermal-hydraulics' coupling calculation, the memory requirement is 60 Mb. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Non-Contact Thermal Properties Measurement with Low-Power Laser and IR Camera System

As shown by the Phoenix Mars Lander's Thermal and Electrical Conductivity Probe (TECP), contact measurements of thermal conductivity and diffusivity (using a modified flux-plate or line-source heat-pulse method) are constrained by a number of factors. Robotic resources must be used to place the probe, making them unavailable for other operations for the duration of the measurement. The range of placement is also limited by mobility, particularly in the case of a lander. Placement is also subject to irregularities in contact quality, resulting in non-repeatable heat transfer to the material under test. Most important from a scientific perspective, the varieties of materials which can be measured are limited to unconsolidated or weakly-cohesive regolith materials, rocks, and ices being too hard for nominal insertion strengths. Accurately measuring thermal properties in the laboratory requires significant experimental finesse, involving sample preparation, controlled and repeatable procedures, and, practically, instrumentation much more voluminous than the sample being tested (heater plates, insulation, temperature sensors). Remote measurements (infrared images from orbiting spacecraft) can reveal composite properties like thermal inertia, but suffer both from a large footprint (low spatial resolution) and convolution of the thermal properties of a potentially layered medium. In situ measurement techniques (the Phoenix TECP is the only robotic measurement of thermal properties to date) suffer from problems of placement range, placement quality, occupation of robotic resources, and the ability to only measure materials of low mechanical strength. A spacecraft needs the ability to perform a non-contact thermal properties measurement in situ. Essential components include low power consumption, leveraging of existing or highly-developed flight technologies, and mechanical simplicity. This new in situ method, by virtue of its being non-contact, bypasses all of these problems. The use of photons to both excite and measure the thermal response of any surface material to a high resolution (estimated footprint = 10 square centimeters) is a generational leap in physical properties measurements. The proposed method consists of spot-heating the surface of a material with a low (less than 1 W) power laser. This produces a moderate (5-10 K) temperature increase in the material.

Hudson, Troy L.↗

Pick-and-Eat Space Crop Production Flight Testing on the International Space Station

Fresh, nutritious, palatable produce for crew consumption on long-duration spaceflight missions may provide health-promoting, bioavailable nutrients and enhance the dietary experience. VEG-04A and VEG-04B explored growing leafy greens on the International Space Station using the Veggie Vegetable Production System. Two flight tests with ground controls were conducted in 2019 growing mizuna mustard, where Veggie chambers were set to different red-to-blue-to-green light formulations. Light quality affects plant growth, nutrition, microbiology, and organoleptic characteristics on Earth, and we examined how these vary in microgravity and under different harvest scenarios. Astronauts harvested and weighed mizuna and completed organoleptic evaluations. Flight samples were returned to Earth for nutritional quality and microbial food safety analyses. Yield and chemistry differed between ground and flight samples and light treatments, and bacterial and fungal counts were lower in ground than in flight samples. This research helps increase our understanding of the requirements for growing high-quality crops in spaceflight.

Food Safety, International Space Station, Nutritio↗