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Spaceflight Biospecimen and Data Sharing in Support of Science Discovery and Exploration

For decades, NASA and international partners have conducted biological experiments in space to understand effects of spaceflight and address potential hazards. To enable spaceflight back to the Moon, and then to Mars and beyond, it is imperative to further understand basic science and health risks associated with spaceflight, along with developing countermeasures. The sending of experiments and organisms into space is a costly endeavor. To maximize scientific return, sharing with the scientific community both space-flown biospecimens and data from completed experiments is essential. New fundamental, applied, and bioinformatic science insights can be gained from specimen and data sharing efforts. Data reuse enables spaceflight health risk modeling, analyzing adverse outcomes across spaceflight hazards, and deep space autonomous support for the flight medical officer. Space-flown biospecimens not required by mission Principal Investigators are regularly archived and made available for scientific request. The largest biorepository of these samples are found within NASA’s Institutional Scientific Collection at Ames Research Center (ISC-ARC), which stores over 32,000 specimens mostly from Shuttle and International Space Station (ISS) missions, but also some ground-based analog samples. The Ames Life Sciences Data Archive manages the ISC-ARC. Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. Only a handful of other similar collections exist worldwide. Rodent biospecimens exposed to simulated space radiation at Brookhaven National Laboratory are archived under the purview of NASA HRP Space Radiation Element. Microbial collection and analyses from 20 years of routine environmental monitoring of air, surfaces, and water systems of the ISS were performed to ensure a safe environment for astronauts. Samples from the ISC-ARC, space radiation and microbial collections are searchable and requestable through the NASA Life Sciences Data Archive (LSDA). Decades of planetary protection microbial isolates derived from spacecraft bioburden are archived in JPL’s microbial collection. Rodent biospecimens from spaceflight investigations conducted by the Japan Aerospace Exploration Agency (JAXA) are archived and available at the JAXA Biorepository at Tsukuba Space Center. The Russian Institute of Biomedical Problems also has a collection of animal, microbial, cellular, and fungi available for research from ground analog experiments. Several data repositories exist for scientists to utilize. The LSDA is the primary NASA source of life sciences research data and information. It contains decades of spaceflight and ground-analog research involving human, microbial, cellular, plant, and animal subjects. Data is collected from NASA-funded investigations through the Human Research Program and the Space Biology Program. The NASA Lifetime Surveillance of Astronaut Health collects and grants access to clinical and occupational health monitoring data from astronauts, with a list and description of data collected available for request through the LSDA. NASA GeneLab at ARC collects genomic, transcriptomic, proteomic, and metabolomic data from any species. It is a repository and platform for collaborative open-science bioinformatic approaches. JAXA is establishing an ‘omics-based repository in collaboration with the Tohoku Medical Megabank (ToMMo), called the JAXA-ToMMo Integrated Biobank for Space Life Science. Overall, the sharing of these biospecimen and data resources can assist researchers worldwide in understanding spaceflight effects on biology, along with enabling next generation data science applications for space exploration platforms. Websites: https://lsda.jsc.nasa.gov/ ; https://www.nasa.gov/ames/research/space-biosciences/isc-bsp ; https://www.nasa.gov/ames/research/space-biosciences/alsda

Ryan T. Scott↗

Studying Microbial Adaptation in the Laboratory: Sensor & Control Upgrades for an Experimental Evolution Biofluidics System

Experimental evolution (EE) involves iteratively exposing a microbial community to specific stressors to study its response to changes in environment over time. EE work is commonly done manually in the laboratory, but, when there are many environmental variables to measure and adjust, it is highly labor intensive, prone to human error, and challenging to scale. Single-purpose automated continuous culturing chambers exist, but implement only limited stressor types. A more general-purpose design is desirable. The BeING Lab at Ames Research Center created the prototype Automated Adaptive Directed Evolution Chamber (AADEC) to address these problems, beginning with Escherichia coli tolerance of short-wave ultraviolet (UV-C) radiation and of temperature. In newer versions, AADEC monitors microbial activity and can adjust the UV-C and temperature levels automatically. An optical density measurement is used to determine how many cells are present in the growth medium—over time, this corresponds to how many survive and reproduce. Oxidation-reduction potential provides information on consumed metabolic energy, and pH and electrical conductivity on metabolic products. Dissolved oxygen content is used to determine aerobic vs anaerobic growth. A Raspberry Pi computer processes all this data to set the UV-C stressor level. AADEC’s auxiliary systems include peristaltic pumps to change media and agitation to counteract cell settling. These actuators can also act as additional stressors. With the Raspberry Pi monitoring sensors and adjusting actuators in real time, AADEC takes measurements and controls the environment much more accurately than can be done with a manual EE implementation. The third and latest AADEC iteration is the first to simplify design and usage with circuits on PCBs and the ability to pre-program experimental protocols. Still planned is expansion to a multi-well design for the study of varying cell cultures in parallel, which will enable researchers to retain and re-inoculate cultures exhibiting the desired trait most strongly while flushing out others. AADEC’s special capabilities make it a valuable tool for studying life under multiple stressors, enabling scientists to replicate changes in climate on microbes for study in a lab setting.

Microbial Adaptation↗

Early And Late Neurobehavioral Effects Of Male And Female Mice Exposed To Five-Ion GCRSim

With upcoming missions to the Moon and beyond to Mars, it is increasingly imperative to elucidate the detrimental effects of space travel beyond the lower Earth orbit, particularly to galactic cosmic radiation. Additionally, with the first female astronaut to soon travel to the Moon there is a strong need to understand the biological sex differences to adaptation to the deep space environment. While the effects of spaceflight on the nervous system are not fully known, studies in animal models have shown that exposure to ionizing radiation can cause neuronal damage and lead to downstream cognitive and behavioral deficits. Here, we investigated the neurobehavioral responses to space environment-like radiation exposure. Male and female 23–24-week-old mice (age-matched to average astronaut age) were exposed to 5, 15 and 50 cGy via Five-Ion Galactic Cosmic Ray Simulation at the NASA National Space Radiation Laboratory at Brookhaven National Laboratory. Both early (72hrs post exposure) and late (1-4 months post exposure) cognitive and behavioral deficits were investigated. Early analysis was performed by observing in-cage behavior including frequency/duration of digging, rearing, and grooming and nestlet building. Additionally, late effects were analyzed at NASA Ames via in-cage behavior as well as Catwalk (gait), Zero Maze (anxiety), Adhesive Removal (sensory motor), Novel Object Recognition and Barnes Maze (working memory). There were pronounced sex differences in both early and late time points. Females scored better than males in nestlet building, gait and working memory while males scored better at the sensory motor (adhesive removal) test. Dose effects were primarily observed at 50 cGy for both sexes, particularly with the Barnes Maze (working memory), where both males and females exposed to 50 cGy showed little to no improvement in test performance, though females again performed better than males. Currently, we are investigating the correlations between the observed behavior and cytokine levels in the plasma and brain. Future studies will continue to investigate cognitive consequences of galactic cosmic radiation in combination with other space-like environment stressors, including antigravity and social versus single housing.

S Puukila↗

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

A methodology to emulate and evaluate a productive virtual workstation

The Advanced Display and Computer Augmented Control (ADCACS) Program at ACT is sponsored by NASA Ames to investigate the broad field of technologies which must be combined to design a 'virtual' workstation for the Space Station Freedom. This program is progressing in several areas and resulted in the definition of requirements for a workstation. A unique combination of technologies at the ACT Laboratory have been networked to effectively create an experimental environment. This experimental environment allows the integration of nonconventional input devices with a high power graphics engine within the framework of an expert system shell which coordinates the heterogeneous inputs with the 'virtual' presentation. The flexibility of the workstation is evolved as experiments are designed and conducted to evaluate the condition descriptions and rule sets of the expert system shell and its effectiveness in driving the graphics engine. Workstation productivity has been defined by the achievable performance in the emulator of the calibrated 'sensitivity' of input devices, the graphics presentation, the possible optical enhancements to achieve a wide field of view color image and the flexibility of conditional descriptions in the expert system shell in adapting to prototype problems.

Krubsack, David↗

Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

Suorsa, Raymond↗

Modular Pulsed Plasma Electric Propulsion System for Cubesats

Current capabilities of CubeSats must be improved in order to perform more ambitious missions. Electric propulsion systems will play a key role due to their large specific impulse. Compared to other propulsion alternatives, their simplicity allows an easier miniaturization and manufacturing of autonomous modules into the nano and pico-satellite platform. Pulsed Plasma Thrusters (PPTs) appear as one of the most promising technologies for the near term. The utilization of solid and non-volatile propellants, their low power requirements and their proven reliability in the large scale make them great candidates for rapid implementation. The main challenges are the integration and miniaturization of all the electronic circuitry into a printed circuit board (PCB) that can satisfy the strict requirements that CubeSats present. NASA Ames and the George Washington University have demonstrated functionality and control of three discrete Micro-Cathode Arc Thrusters (CAT) using a bench top configuration that was compatible with the ARC PhoneSat Bus. This demonstration was successfully conducted in a vaccum chamber at the ARC Environmental Test Laboratory. A new effort will integrate a low power Plasma Processing Unit and two plasma thrusters onto a single printed circuit board that will utilize less than 13 U of Bus volume. The target design will be optimized for the accommodation into the PhoneSatEDISON Demonstration of SmallSatellite Networks (EDSN) bus as it uses the same software interface application, which was demonstrated in the previous task. This paper describes the design, integration and architecture of the proposed propulsion subsystem for a planned Technology Demonstration Mission. In addition, a general review of the Pulsed Plasma technology available for CubeSats is presented in order to assess the necessary challenges to overcome further development.

PCB↗

BRCore: an R package implementing flexible selection of core taxa using contribution to Bray-Curtis dissimilarity and neutral model fitting

Identifying core taxa in microbial ecology highlights groups likely to participate in a broad range of potential ecological interactions. Here, we present BRCore, an R package to identify core taxa using abundance-occupancy distributions and beta-diversity contributions across ecological niches, and predict stochastic and deterministic taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Aerosol hygroscopicity over the southeast Atlantic Ocean during the biomass burning season – Part 1: From the perspective of scattering enhancement​​​​​​​

Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f(RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f(80 %) from ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the southeast Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f(80 %) of 1.40 ± 0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f(80 %) of 1.51 ± 0.22, consistent with higher values of BB aerosol hygroscopicity found in the literature. The hygroscopicity parameter of OA (κ OA ) is retrieved from the Mie model with a mean value of 0.11 ± 0.08, which is in the middle to upper range compared to the literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced biomass burning aerosol (BBA) hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulfate fraction, and greater κ OA at lower altitudes. We propose a parameterization that quantifies f(RH) with chemical composition and κOA based on Mie simulation of internally mixed OA–(NH 4 ) 2 SO 4 –BC mixtures. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA–(NH 4 ) 2 SO 4 –BC internal mixture with respect to the f(RH) prediction. The sensitivity of f(RH) to κ OA indicates that applying a constant κ OA is only suitable when the OA fraction is low and κ OA shows limited variation. However, in situations deviating these two criteria, κ OA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κ OA variability is recommended.

54 ENVIRONMENTAL SCIENCES↗

Development of Advanced Life Cycle Costing Methods for Technology Benefit/Cost/Risk Assessment

The overall objective of this three-year grant is to provide NASA Langley's System Analysis Branch with improved affordability tools and methods based on probabilistic cost assessment techniques. In order to accomplish this objective, the Aerospace Systems Design Laboratory (ASDL) needs to pursue more detailed affordability, technology impact, and risk prediction methods and to demonstrate them on variety of advanced commercial transports. The affordability assessment, which is a cornerstone of ASDL methods, relies on the Aircraft Life Cycle Cost Analysis (ALCCA) program originally developed by NASA Ames Research Center and enhanced by ASDL. This grant proposed to improve ALCCA in support of the project objective by updating the research, design, test, and evaluation cost module, as well as the engine development cost module. Investigations into enhancements to ALCCA include improved engine development cost, process based costing, supportability cost, and system reliability with airline loss of revenue for system downtime. A probabilistic, stand-alone version of ALCCA/FLOPS will also be developed under this grant in order to capture the uncertainty involved in technology assessments. FLOPS (FLight Optimization System program) is an aircraft synthesis and sizing code developed by NASA Langley Research Center. This probabilistic version of the coupled program will be used within a Technology Impact Forecasting (TIF) method to determine what types of technologies would have to be infused in a system in order to meet customer requirements. A probabilistic analysis of the CER's (cost estimating relationships) within ALCCA will also be carried out under this contract in order to gain some insight as to the most influential costs and the impact that code fidelity could have on future RDS (Robust Design Simulation) studies.

Yackovetsky, Robert↗

Updating Mars-GRAM to Increase the Accuracy of Sensitivity Studies at Large Optical Depths

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM s perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL). During the Mars Science Laboratory (MSL) site selection process, it was discovered that Mars-GRAM, when used for sensitivity studies for MapYear=0 and large optical depth values such as tau=3, is less than realistic. From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). MGCM results that were used for Mars-GRAM with MapYear set to 0 were from a MGCM run with a fixed value of tau=3 for the entire year at all locations. This has resulted in an imprecise atmospheric density at all altitudes. As a preliminary fix to this pressure-density problem, density factor values were determined for tau=0.3, 1 and 3 that will adjust the input values of MGCM MapYear 0 pressure and density to achieve a better match of Mars-GRAM MapYear 0 with Thermal Emission Spectrometer (TES) observations for MapYears 1 and 2 at comparable dust loading. Currently, these density factors are fixed values for all latitudes and Ls. Results will be presented from work being done to derive better multipliers by including variation with latitude and/or Ls by comparison of MapYear 0 output directly against TES limb data. The addition of these more precise density factors to Mars-GRAM 2005 Release 1.4 will improve the results of the sensitivity studies done for large optical depths.

Justh, Hiliary L.↗

Desert Research and Technology Studies (DRATS) Traverse Planning

Slide 1] The Desert Research and Technology Studies (DRATS) include large scale field tests of manned lunar surface exploration systems; these tests are sponsored by the Director s Office of Integration (DOI) [sic, Directorate Integration Office (DIO)] within the Constellation Program and they include geological exploration objectives along well designed traverses. These traverses are designed by the Traverse Team, an ad hoc group of some 10 geologists form NASA and academia, as well as experts in mission operation who define the operational constraints applicable to specific simulation scenarios. [Slide 2] These DRATS/DOI tests focus on 1) the performance of major surface systems, such as rovers, mobile habitats, communication architecture, navigation tools, earth-moving equipment, unmanned reconnaissance robots etc. under realistic field conditions and 2) the development of operational concepts that integrate all of these systems into a single, optimized operation. The participation of science is currently concentrating on geological sciences, with the objective of developing suitable tools and documentation protocols to sample representative rocks for Earth return, and to generate some conceptual understanding of the ground support structure that will be needed for the real time science-support of a lunar surface crew. [Slide 3] Major surface systems exercised in the June 2008 analog tests at the Moses Lake site, WA. [Upper left] The Chariot Rover (developed at Johnson Space Center) is an unpressurized vehicle driven by fully suited crews. [Upper right] Mobile Habitat provided by the Jet Propulsion Laboratory. Chariot is the more nimble and mobile vehicle and the idea is to drive the habitat remotely to some rendezvous place where Chariot would catch up - after a lengthy traverse - at the end of the day. [Lower left] The K-10 remotely operated robot (provided by NASA Ames Research Center) conducting scientific/geologic reconnaissance of the prospective traverse region, locating specific sites for more detailed exploration by Chariot and its crew. [Lower right] This earth-moving equipment (provided by NASA KSC) can be attached to Chariot and is envisioned to, for example, level an outpost site or to mine lunar soi

Horz, Friedrich↗

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗

Variable conductance heat pipes from the laboratory to space

Heat pipes were developed which can be used as (1) a variable conductance link between a heat source and sink which provides temperature stability; (2) a feedback control mechanism that acts to directly maintain the source at a constant temperature; (3) or as a thermal diode that allows heat to be transferred in one direction only. To establish flight level confidence in these basic control techniques, the Ames Heat Pipe Experiment (AHPE) was launched in August 1972 and the Advanced Thermal Control Flight Experiment (ATFE) is scheduled for launch in May 1973. The major efforts of the technology development, initial flight results of the AHPE, and ground test data of the ATFE are discussed.

Kirkpatrick, J. P.↗

Proceedings of a conference on Cardiovascular Bioinstrumentation

The Ames Research Center (ARC) has a long history in the development of cardiovascular (CV) instrumentation for human and animal research. The ARC Cardiovascular Research Lab under the Space Physiology Branch, Space Research Directorate, supports both ground-based and space-based animal and human research goals. The Cardiovascular Research Laboratory was established at ARC in the mid 1960's to conduct ground-based animal research and support development of advanced cardiovascular instrumentation applicable to spaceflight. The ARC Biomedical Research Program also conducts human studies with a CV instrumentation focus.

Ballard, Rodney W.↗

SPRITE: A TPS Test Bed for Ground and Flight

Engineers in the Entry Systems and Technology Division at NASA Ames Research Center developed a fully instrumented, small atmospheric entry probe called SPRITE (Small Probe Reentry Investigation for TPS Engineering). SPRITE, conceived as a flight test bed for thermal protection materials, was tested at full scale in an arc-jet facility so that the aerothermal environments the probe experiences over portions of its flight trajectory and in the arc-jet are similar. This ground-to-flight traceability enhances the ability of mission designers to evaluate margins needed in the design of thermal protection systems (TPS) of larger scale atmospheric entry vehicles. SPRITE is a 14-inch diameter, 45 deg. sphere-cone with a conical aftbody and designed for testing in the NASA Ames Aerodynamic Heating Facility (AHF). The probe is a two-part aluminum shell with PICA (phenolic impregnated carbon ablator) bonded on the forebody and LI-2200 (Shuttle tile material) bonded to the aftbody. Plugs with embedded thermocouples, similar to those installed in the heat shield of the Mars Science Laboratory (MSL), and a number of distributed sensors are integrated into the design. The data from these sensors are fed to an innovative, custom-designed data acquisition system also integrated with the test article. Two identical SPRITE models were built and successfully tested in late 2010-early 2011, and the concept is currently being modified to enable testing of conformable and/or flexible materials.

Ablation↗

Mass measurement of 51 Fe for the determination of the 51 Fe($p, γ$) 52 Co reaction rate

Background: The 51 Fe(p, γ) 52 Co reaction lies along the main rp-process path leading up to the 56 Ni waiting point. The uncertainty in the reaction Q value, which determines the equilibrium between the forward protoncapture and reverse photodisintegration 52 Co(γ,p) 51 Fe reaction, contributes to considerable uncertainty in the reaction rate in the temperature range of interest for Type I x-ray bursts and thus to an ≈10% uncertainty in burst ashes lighter than A = 56. Purpose: With a recent Penning trap mass measurement of 52 Co reducing the uncertainty on its mass to 6.6 keV [Nesterenko et al., J. Phys. G 44, 065103 (2017)], the dominant source of uncertainty in the reaction Q value is now the mass of 51 Fe, reported in the 2016 atomic mass evaluation to a precision of 9 keV [Wang et al., Chin.Phys. C 41, 030003 (2017)]. A new, high-precision Penning trap mass measurement of 51 Fe was performed to allow the determination of an improved precision Q value and thus new reaction rates. Method: 51 Fe was produced using projectile fragmentation at the Coupled Cyclotron Facility at the National Superconducting Cyclotron Laboratory, and separated using the A1900 fragment separator. The resulting secondary beam was then thermalized in the beam stopping area before a mass measurement was performed using the LEBIT 9.4T Penning trap mass spectrometer. Results: The new mass excess, ME = -40189.2(1.6) keV, is sixfold more precise than the current AME value, and 1.6σ less negative. This value was used to calculate a new proton separation energy for 52 Co of 1431(7) keV. New excitation levels were then calculated for 52 Co using the NUSHELLX code with the GXPF1A interaction, and a new reaction rate and burst ash composition was calculated. Conclusions:With a new measured Q value, the uncertainty on the 51 Fe(p, γ ) reaction rate is dominated by the poorly measured 52 Co level structure. Finally, reducing this uncertainty would allow a more precise rate calculation and a better determination of the mass abundances in the burst ashes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗