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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform

The goal of the Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform project is to derisk the manufacturing scalability for a high chip count heterogeneous smart lighting platform, with the potential to enable significant energy savings through dynamic directional light control and custom. Specifically, the project derisks the scalability of a disruptive new computer controlled microassembly fabrication process SRI International is developing, to address fundamental cost barriers to mass production of high chip count systems. This is key for enabling mass adoption and thus maximum societal energy savings impact. The LED light sheet technology is a smart illumination platform that can be applied to lighting, signage, and display. It has features and a form factor similar to bendable or conformal OLED light sheets but uses more efficient LEDs with a remote phosphor layer that is very close to the LED to deliver a luminous efficacy that exceeds 125 lumen/Watt and enable > 50% Lighting Application Efficiency (LAE) energy savings. During Budget Period 1 (BP1), all of the BP1 milestones were successfully completed: (M2.0.1) Design demonstrator details that will meet the final project goals, (M6.1.1) Show lighting output model can predict illuminance, spatial, spectral distribution for specific light-sheet designs and use case, (M3.2.1) Automated loading supports 200 chip arrays, and (M3.3.1) Finish first interconnect process run for 200 chip array. The BP1 Go/No-Go Decision Point (G/NG 1) 200 chip demonstrator sample was in the process of final assembly and test at the end of BP1 on December 31, 2023. The objective was successfully achieved on January 16, 2024, when a wired 200-chip sample underwent confirmation testing that demonstrated a 93.75% first pass electrical yield that successfully exceeded the 75% first-pass electrical yield BP1 G/NG requirement. In addition, all 93.75% of the sample devices lit up, further demonstrating the ability to assemble and transfer small LED chips without damaging their functionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2009

Damage Tolerance Testing of a NASA TransHab Derivative Woven Inflatable Module

Current options for Lunar habitat architecture include inflatable habitats and airlocks. Inflatable structures can have mass and volume advantages over conventional structures. However, inflatable structures carry different inherent risks and are at a lower Technical Readiness Level (TRL) than more conventional metallic structures. One of the risks associated with inflatable structures is in understanding the tolerance to induced damage. The Damage Tolerance Test (DTT) is designed to study the structural integrity of an expandable structure. TransHab (Figure 1) was an experimental inflatable module developed at the NASA/Johnson Space Center in the 1990 s. The TransHab design was originally envisioned for use in Mars Transits but was also studied as a potential habitat for the International Space Station (ISS). The design of the TransHab module was based on a woven design using an Aramid fabric. Testing of this design demonstrated a high level of predictability and repeatability with analytical predictions of stresses and deflections. Based on JSC s experience with the design and analysis of woven inflatable structures, the Damage Tolerance Test article was designed and fabricated using a woven design. The DTT article was inflated to 45 psig, representing 25% of the ultimate burst pressure, and one of the one-inch wide longitudinal structural members was severed by initiating a Linear Shaped Charge (LSC). Strain gage measurements, at the interface between the expandable elements (straps) and the nonexpandable metallic elements for pre-selected longitudinal straps, were taken throughout pressurization of the module and strap separation. Strain gage measurements show no change in longitudinal strap loading at the bulkhead interface after strap separation indicating loads in the restraint layer were re-distributed local to the damaged area due to the effects of friction under high internal pressure loading. The test completed all primary objectives with better than expected results. This paper will discuss space inflatable structures, damage tolerance analysis, test results, and applicability to the Lunar architecture.

Edgecombe, John↗
NASA NTRS2021

Satellite Remote Sensing Observations of Trans-Atlantic Dust Transport and Deposition: A Multi-Sensor Analysis

We analyze the decade-long (2007-2016) record of aerosol measurements from four distinctive sensors, namely CALIOP, MODIS, MISR, and IASI, to quantify the trans-Atlantic dust transport and deposition. These satellite sensors use different techniques to characterize particle size and shape properties; and we have developed sensor-specific methods (broadly categorized into size-based and shape-based method) to derive dust optical depth (DOD). The size-based DOD from MODIS and IASI generally agrees better with AERONET-derived DOD than the shape-based DOD from CALIOP and MISR does. Overall, the shape-based DOD is smaller than the size-based DOD by about 25%, which is consistent with distinctive ways of accounting for coarse-spherical particles of dust-pollution internal mixture. While such dust-pollution mixtures are counted as dust in the size-based DOD, they are excluded in the shape-based DOD. DOD is not a good proxy for dust deposition. Instead, the dust deposition depends strongly on the gradient of DOD on a monthly basis and can be derived by calculating the meridional and zonal dust mass flux based on the three-dimensional distributions of dust. Among the remote sensing measurements, difference in dust deposition is smaller than that of DOD, suggesting that different satellites characterize the DOD gradient more consistently than DOD itself. Satellite measurements of dust deposition and DOD also provide an accurate estimate of the dust loss frequency (LF) that measures how efficient the dust is removed from the atmosphere. We found that these remote sensing measurements yield similar LF values of 0.078 –0.102 d-1, which however is factors of 2-5 smaller than model simulations. This analysis provides valuable insights into potential deficiencies in models’ emission and transport/removal processes and hence helps guide model improvement.

remote sensing↗
DOE OSTI2020

A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm

Introduction: hERG block potency is widely used to calculate a drug's safety margin against its torsadogenic potential. Previous studies are confounded by use of different patch clamp electrophysiology protocols and a lack of statistical quantification of experimental variability. Since the new cardiac safety paradigm being discussed by the International Council for Harmonisation promotes a tighter integration of nonclinical and clinical data for torsadogenic risk assessment, a more systematic approach to estimate the hERG block potency and safety margin is needed. Methods: A cross-industry study was performed to collect hERG data on 28 drugs with known torsadogenic risk using a standardized experimental protocol. A Bayesian hierarchical modeling (BHM) approach was used to assess the hERG block potency of these drugs by quantifying both the inter-site and intra-site variability. A modeling and simulation study was also done to evaluate protocol-dependent changes in hERG potency estimates. Results: A systematic approach to estimate hERG block potency is established. The impact of choosing a safety margin threshold on torsadogenic risk evaluation is explored based on the posterior distributions of hERG potency estimated by this method. The modeling and simulation results suggest any potency estimate is specific to the protocol used. Discussion: This methodology can estimate hERG block potency specific to a given voltage protocol. The relationship between safety margin thresholds and torsadogenic risk predictivity suggests the threshold should be tailored to each specific context of use, and safety margin evaluation may need to be integrated with other information to form a more comprehensive risk assessment.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

International Space Station (ISS) Bacterial Filter Elements (BFEs): Filter Efficiency and Pressure Testing of Returned Units

The air revitalization system aboard the International Space Station (ISS) provides the vital function of maintaining a clean cabin environment for the crew and the hardware. This becomes a serious challenge in pressurized space compartments since no outside air ventilation is possible, and a larger particulate load is imposed on the filtration system due to lack of sedimentation due to the microgravity environment in Low Earth Orbit (LEO). The ISS Environmental Control and Life Support (ECLS) system architecture in the U.S. Segment uses a distributed particulate filtration approach consisting of traditional High-Efficiency Particulate Adsorption (HEPA) media filters deployed at multiple locations in each U.S. Segment module; these filters are referred to as Bacterial Filter Elements, or BFEs. These filters see a replacement interval, as part of maintenance, of 2-5 years dependent on location in the ISS. In this work, we present particulate removal efficiency, pressure drop, and leak test results for a sample set of 8 BFEs returned from the ISS after filter replacement. The results can potentially be utilized by the ISS Program to ascertain whether the present replacement interval can be maintained or extended to balance the on-ground filter inventory with extension of the lifetime of ISS beyond 2024. These results can also provide meaningful guidance for particulate filter designs under consideration for future deep space exploration missions.

Filtration↗
DOE OSTI2021

Characterisation of nano-assemblies inside mesopores using neutron scattering

Adsorption of molecular and nanoscale matter in mesoporous materials is important in filtration and chromatography as well as membrane processes. However, the morphology and distribution of self-assembled structures of adsorbate formed within nanoconfined environments is largely unknown. Small Angle Neutron Scattering (SANS) with porous matrix matching the neutron scattering length density of the solvent has the potential to provide detailed information on the self-assemblies formed in pore spaces. However, analysis of such SANS profiles remains a challenge. In this study, we extend the SANS analysis method previously developed by Findenegg and co-workers to include interparticle correlations, providing a qualitative characterisation of the adsorption state of surfactants and nanoparticles in the cylindrical pores of silica nanomaterials. We find that the pore filling fraction and the self-assembled state of the adsorbate governs the scattering profile. We apply the model to two materials namely, triethyleneglycol monohexyl ether (C 6 E 3 ) surfactant and gold nanoparticles adsorbed in SBA-15 mesoporous silica. In contrast to the C 6 E 3 system, Bragg scattering dominates the diffuse scattering in gold nanoparticle system, which we attribute to the immobile internal structure of the nanoparticles. In conclusion, this new SANS analysis method has potential to elucidate structures of soft matter nanoassemblies inside mesopores.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1999

Microgravity Experiments to Evaluate Electrostatic Forces in Controlling Cohesion and Adhesion of Granular Materials

The bulk behavior of dispersed, fluidized, or undispersed stationary granular systems cannot be fully understood in terms of adhesive/cohesive properties without understanding the role of electrostatic forces acting at the level of the grains themselves. When grains adhere to a surface, or come in contact with one another in a stationary bulk mass, it is difficult to measure the forces acting on the grains, and the forces themselves that induced the cohesion and adhesion are changed. Even if a single gain were to be scrutinized in the laboratory, it might be difficult, perhaps impossible, to define the distribution and character of surface charging and the three- dimensional relationship that charges (electrons, holes) have to one another. The hypothesis that we propose to test in microgravity (for dielectric materials) is that adhesion and cohesion of granular matter are mediated primarily by dipole forces that do not require the presence of a net charge; in fact, nominally electrically neutral materials should express adhesive and cohesive behavior when the neutrality results from a balance of positive and negative charge carriers. Moreover, the use of net charge alone as a measure of the electrical nature of grain-to-grain relationships within a granular mass may be misleading. We believe that the dipole forces arise from the presence of randomly-distributed positive and negative fixed charge carriers on grains that give rise to a resultant dipole moment. These dipole forces have long-range attraction. Random charges are created whenever there is triboelectrical activity of a granular mass, that is, whenever the grains experience contact/separation sequences or friction. Electrostatic forces are generally under-estimated for their role in causing agglomeration of dispersed grains in particulate clouds, or their role in affecting the internal frictional relationships in packed granular masses. We believe that electrostatic, in particular dipole-mediated processes, are pervasive and probably affect, at some level, everything from astrophysical-scale granular systems such as interstellar nebulae, protoplanetary dust and debris disks, planetary-scale systems such as debris palls from meteorite impact, volcanic eruptions, and aeolian dust storms, all the way to industrial-scale systems in mining, powder and grain processing, pharmaceuticals, and smoke-stack technologies. NASA must concern itself with the electrostatic behavior of dust and sand on Mars because of its potentially critical importance to human exploration. The motion and adhesion of martian surface materials will affect the design and performance of spacesuits, habitats, processing plants, solar panels, and any externally exposed equipment such as surface rovers or communication and weather stations. Additionally, the adhesion of dust and sand could greatly enhance contact with the potentially toxic components of the martian soil.

Marshall, J.↗
NASA NTRS2015

IceCube: CubeSat 883-GHz Radiometry for Future Ice Cloud Remote Sensing

Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Accurate observations of global cloud ice and its distribution have been a challenge from space, and require good instrument sensitivities to both cloud mass and microphysical properties. Despite great advances from recent spaceborne radar and passive sensors, uncertainty of current ice water path (IWP) measurements is still not better than a factor of 2. Submillimeter (submm) wave remote sensing offers great potential for improving cloud ice measurements, with simultaneous retrievals of cloud ice and its microphysical properties. The IceCube project is to enable this cloud ice remote sensing capability in future missions, by raising 874-GHz receiver technology TRL from 5 to 7 in a spaceflight demonstration on 3-U CubeSat in a low Earth orbit (LEO) environment. The NASAs Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes Inc (VDI) on the 874-GHz receiver through its Vector Network Analyzer (VNA) extender module product line, to develop an instrument with precision of 0.2 K over 1-second integration and accuracy of 2.0 K or better. IceCube is scheduled to launch to and subsequent release from the International Space Station (ISS) in mid-2016 for nominal operation of 28 plus days. We will present the updated design of the payload and spacecraft systems, as well as the operation concept. We will also show the simulated 874-GHz radiances from the ISS orbits and cloud scattering signals as expected for the IceCube cloud radiometer.

cloud ice remote sensing↗
DOE OSTI2026

Effect of recoils on soft-drop-groomed observables in 𝛾-tagged jets in a multistage approach

We investigate medium-induced modifications to jet substructure observables that characterize hard components in central Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV. Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and 𝛾-tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to 𝑝−𝑝 ratio of the soft drop prong angle 𝑟 𝑔 , the relative prong transverse momentum 𝑘 𝑇,𝑔 , and the groomed mass 𝑚 𝑔 distributions. Due to this nonmonotonic modification, 𝛾-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. Further systematic studies demonstrate that these effects are dominated by recoil medium response. This work highlights the potential of hard substructures in 𝛾-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions, in particular by enabling detailed investigations of jet-medium parton scatterings via their associated medium response. All simulations for 𝛾-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Advancing Transportation Efficiency and Electric Vehicles in Tonga: A Review of Relevant Trends and Best Practices

Tonga is facing a transportation sector characterized by private passenger vehicles, poorly maintained roads and walkways, and an inadequate public transit system. By understanding detailed global and regional trends for transport energy efficiency and electric vehicles (EVs) within this context, the Government of Tonga can proactively plan its future transportation systems. In addition to global and regional trends, this report also covers a variety of international case studies and examines Tonga's own transportation policies and actions through this lens. Jurisdictions leading in EV adoption have implemented policies such as reducing taxes on EVs compared to internal combustion engine (ICE) vehicles, providing subsidies and rebates for EV charger installation, instituting an age limit on imported ICE vehicles, and developing EV maintenance courses to expand the skill set of current automotive technicians. Although there are key challenges and barriers to widespread EV adoption in Tonga, multiple studies have researched potential political, technical, financial, and educational interventions that can be adapted and applied in Tonga. Therefore, the purpose of this report is to synthesize the relevant trends and best practices in order to provide Tonga's Ministry of Meteorology, Energy, Information, Disaster Management, Environment, Climate Change and Communication (MEIDECC) with a wide range of information on electric vehicles (EVs) and transportation efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Constraints on the Origin of Mercury’s Large Core from Core-Mantle Differentiation Models

Mercury’s core is notoriously large when compared to other planets of our solar system. The origin of this large core is still uncertain. Available data on the surface composition and internal structure of Mercury from the past MESSENGER mission and future data collected by BepiColombo will continue to provide clues to Mercury’s formation. Here, we present results combining experimental data on elemental distribution between core and mantle with spacecraft data, to estimate bulk Mercury composition. We applied this strategy to major elements (Fe, Si, Mg, Al and O), as well as minor elements (Cr and Ti), and compared derived compositions to chondritic data and the chemical compositions of the other terrestrial planets. Our results show that Mercury has a chemical composition significantly different from all known materials of the solar system. In addition, numerous scenarios were proposed to explain Mercury’s structure, including “chaotic models” such as giant impacts and “orderly models” such as aerodynamic sorting. Here, we tested whether Mercury’s composition can be explained by mantle stripping by impacts. We will show how such a scenario reconciles several features of Mercury’s geochemistry with chondritic data. We will also discuss the outlook of additional constraints from supplementary data potentially collected by BepiColombo.

Mercury↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗
DOE OSTI2025

Gating Single Molecules with Counterions

We report atomic-scale gating and visualization of local charge distribution within individual rare-earth-based molecular complexes on a metallic surface. The complexes are formed by a positively charged lanthanum ion coordinated to a (pcam)3 molecule and a negatively charged counterion trapped underneath via electrostatic interactions on a Au(111) surface. Local gating is performed by adding an additional negatively charged counterion to one side of the complex, which results in the redistribution of charges within the complex and a positive shift of the frontier orbitals. This is caused by the internal Stark effect induced by the added counterion. This effect is directly captured using tunneling spectroscopy and spectroscopic mapping at 5 K substrate temperature. The polarizability of the complex is corroborated by density functional theory and analytical calculations based on experimental findings. Furthermore, the influence of charge polarization on nearby complexes is investigated in a cluster purposely assembled using three complexes, which reveals maintaining the charge states as in single complexes. These findings will enable the design of robust charged rare-earth complexes to be tailored for potential solid-state applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Improving Cycling Performance of Anode-Free Lithium Batteries by Pressure and Voltage Control

The anode-free lithium (Li) batteries (AFLBs) have great potential to provide higher energy density than most other batteries. However, the performance of AFLBs is very sensitive to pressure and other operating parameters, especially for coin cells widely used in AFLB investigations. Therefore, optimizing cell assembly parameters and test protocol is critical to get reliable and comparable results in this field. In this work, the operating voltage range of AFLBs using a localized high concentration electrolyte has been optimized. The morphology of the deposited Li in AFLBs is much more indicting to the pressure than other type of batteries due to the absence of anode active material (i.e. Li) as a pressure cushion layer in the as prepared cells. With an optimized cycling protocol, a thin layer of uniform nucleation sites can be formed in the initial cycle which will facilitate smooth Li desposition/stripping in the subsequent cycles of AFLBs. The solid electrolyte interphase layer formed under optimized pressure and uniform pressure distribution exhibits a good mechanical stability even after long-term cycling. In conclusion, with an optimized cell configuration, the internal pressure in the coin cells has been optimized to improve the cycling performance of AFLBs (Cu||NMC811) with 72% of capacity retention in 100 cycles.

25 ENERGY STORAGE↗
DOE OSTI2020

Database of pharmacokinetic time-series data and parameters for 144 environmental chemicals

Time courses of compound concentrations in plasma are used in chemical safety analysis to evaluate the relationship between external administered doses and internal tissue exposures. This type of experimental data is rarely available for the thousands of non-pharmaceutical chemicals to which people may potentially be unknowingly exposed but is necessary to properly assess the risk of such exposures. In vitro assays and in silico models are often used to craft an understanding of a chemical’s pharmacokinetics; however, the certainty of the quantitative application of these estimates for chemical safety evaluations cannot be determined without in vivo data for external validation. To address this need, we present a public database of chemical time-series concentration data from 567 studies in humans or test animals for 144 environmentally-relevant chemicals and their metabolites (187 analytes total). All major administration routes are incorporated, with concentrations measured in blood/plasma, tissues, and excreta. We also include calculated pharmacokinetic parameters for some studies, and a bibliography of additional source documents to support future extraction of time-series. In addition to pharmacokinetic model calibration and validation, these data may be used for analyses of diferential chemical distribution across chemicals, species, doses, or routes, and for meta-analyses on pharmacokinetic studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2009

CCSDS Spacecraft Monitor and Control Mission Operations Interoperability Prototype

We are entering a new era in space exploration. Reduced operating budgets require innovative solutions to leverage existing systems to implement the capabilities of future missions. Custom solutions to fulfill mission objectives are no longer viable. Can NASA adopt international standards to reduce costs and increase interoperability with other space agencies? Can legacy systems be leveraged in a service oriented architecture (SOA) to further reduce operations costs? The Operations Technology Facility (OTF) at the Johnson Space Center (JSC) is collaborating with Deutsches Zentrum fur Luft- und Raumfahrt (DLR) to answer these very questions. The Mission Operations and Information Management Services Area (MOIMS) Spacecraft Monitor and Control (SM&C) Working Group within the Consultative Committee for Space Data Systems (CCSDS) is developing the Mission Operations standards to address this problem space. The set of proposed standards presents a service oriented architecture to increase the level of interoperability among space agencies. The OTF and DLR are developing independent implementations of the standards as part of an interoperability prototype. This prototype will address three key components: validation of the SM&C Mission Operations protocol, exploration of the Object Management Group (OMG) Data Distribution Service (DDS), and the incorporation of legacy systems in a SOA. The OTF will implement the service providers described in the SM&C Mission Operation standards to create a portal for interaction with a spacecraft simulator. DLR will implement the service consumers to perform the monitor and control of the spacecraft. The specifications insulate the applications from the underlying transport layer. We will gain experience with a DDS transport layer as we delegate responsibility to the middleware and explore transport bridges to connect disparate middleware products. A SOA facilitates the reuse of software components. The prototype will leverage the capabilities of existing legacy systems. Various custom applications and middleware solutions will be combined into one system providing the illusion of a set of homogenous services. This paper will document our journey as we implement the interoperability prototype. The team consists of software engineers with experience on the current command, telemetry and messaging systems that support the International Space Station (ISS) and Space Shuttle programs. Emphasis will be on the objectives, results and potential cost saving benefits.

Lucord, Steve↗
NASA NTRSDate not supplied

Calcium and Magnesium Distribution Between Sulfide and Silicate Melts: Thermodynamic Modeling and Insights into Mercury's Mantle-Crust Differentiation

Mercury stands out as the terrestrial planet with the lowest degree of oxidation among all planets of our solar system. It is characterized by a high abundance of sulfur, which is expected to replace oxygen in silicate melts. This sulfur enrichment could lead to sulfide saturation in its mantle, potentially resulting in the formation of sulfides rich in calcium and magnesium. Utilizing experimental data from the literature, we constructed a thermodynamic model to explore the partitioning of calcium and magnesium between sulfide and silicate melts. This model aims to improve our comprehension of the chemical equilibria driving the process of mantle-crust differentiation on Mercury. Our models indicate that increased temperature, decreased pressure, and low concentrations of iron, oxygen, and carbon within the sulfide phase, along with low sulfur concentrations in the silicate phase, favor calcium’s partitioning into the sulfide. Additionally, magnesium partitioning into the sulfide melt is favored with decreased pressure, decreased temperature, low concentrations of iron and calcium within the sulfide, and low concentrations of sulfur within the silicate. Our results suggest that up 9.4% and 5.6% Ca and Mg, respectively, can be present in sulfides equilibrated with sulfide-saturated silicate melts during mantle-crust differentiation. Further investigation will focus on the distribution of sulfide phases within the mantle and crust to better constrain Mercury’s internal structure.

Taylor McCombs↗