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Continued Environmental Microbiology Monitoring of The International Space Station (ISS) Veggie Unit Used for In-Flight, Crop-Based Food Systems

The International Space Station is a closed environment where rotating sets of Crewmembers live and work. This environment is monitored to ensure occupants’ health and safety during their spaceflight residency by routine Environmental Health System (EHS) collection of microbial samples including air, surface, and water. The microbial samples are collected, enumerated, and analyzed quarterly to monitor on-board system contamination and potential risks to crew health. Quarterly monitoring of the microorganisms in the ISS environment supports crew safety and contributes to a large set of microbial concentration and diversity data. The current in-inflight microbial requirements were developed using this historical data collected by the routine environmental monitoring. These in-flight microbial requirements have been established to maintain the health and safety of the spacecraft environment. This study leverages quarterly operational EHS sampling by collecting additional microbial samples from the surface of the Veggie plant production system on ISS. These samples will yield microbial concentration and diversity that can be compared and analyzed with nominal surface samples from the vehicle. The data collected in this study will aid in the development of requirements for spaceflight-based food production systems. Continued surface sampling of the internal and external surfaces of the Veggie system, along with collaboration from both Johnson Space Center (JSC) & Kennedy Space Center (KSC) scientists studying the microbiome of the veggie-crop systems, will be implemented as part of the future development of crop-based food system requirements for the ISS and beyond.

Christian Mena↗

Thermal Vacuum and Vibration Testing of the Differential Thermal Expansion Thermal Switch

The Extended Stroke, Reverse Operation, Differential Expansion Thermal Switch for Extreme Variable Environments uses materials with both positive and negative coefficients of thermal expansion (CTE) arranged in concentric cylinders so that the thermal switch (TS) operates passively, opening a gap between interfaces to create a low thermal contact when cold, and closing the gap between interfaces to create a high thermal contact when hot. This paper details the testing of the TS at Marshall Space Flight Center including the pre-vibe thermal vacuum cycle test, vibration test, post-vibe thermal vacuum cycle test, and long duration thermal vacuum cycle test. The pre- and post-vibe thermal cycle and the long duration cycle test tested to hot and cold plateau initial temperatures of 40 °C, and -173 °C, respectively. The pre- and post-vibe tests required plateau holds of at least 2 hours, whereas the long duration cycle test required plateau holds of at least 20 hours. The tests each used a rate of temperature change of < 2 °C/min when transitioning between plateaus. The data collected from each thermal test is compared to show the operation of the TS both before and after the vibration test to GEVS levels, and throughout the long duration cycle test. From the data collected, the total conductance through the TS interfaces is calculated for both on (TS closed – during hot plateau) and off (TS open – during cold plateau) configurations, and the turndown ratio is also calculated. Challenges and lessons learned from the testing are also discussed.

thermal control technology↗

Validation of the Pulmonary Function System for Use on the International Space Station

Aerobic deconditioning occurs during long duration space flight despite the use of exercise countermeasures (Convertino, 1996). As a part of International Space Station (ISS) medical operations, periodic tests designed to estimate aerobic capacity are performed to track changes in aerobic fitness and to determine the effectiveness of exercise countermeasures. These tests are performed prior to, during, and after missions of greater than 30 days in duration. Crewmembers selected for missions aboard the ISS perform a graded exercise test on a cycle ergometer approximately 270 days prior to their scheduled launch date in order to measure peak oxygen consumption (VO2PK) and peak heart rate (HRpk). Approximately 30 to 45 days prior to launch, crewmembers perform a submaximal cycle ergometer test at work rates set to elicit 25, 50 and 75% of their pre-flight VO2PK. This test, known as the Periodic Fitness Evaluation (PFE), serves as a baseline measure to which subsequent in-and post-flight exercise tests are compared. While onboard the ISS, crewmembers are normally scheduled to perform the PFE beginning with flight day (FD) 14 and every 30 days thereafter. The PFE is also conducted 5 and 30 days following flight. Using PFE data, aerobic fitness is estimated by quantifying the VO2 vs. HR relationship using linear regression and calculating the VO2 that would occur at the crewmember s previously measured HRpk. Currently, for data collected during flight, this technique assumes that the pre- vs. in-flight oxygen consumption per given cycle workload is similar. However, the validity of this assumption is based upon a sparse amount of data collected during the Skylab era (Michel, et al. 1977). The method of using heart rate and cycle ergometer work rates has been used to estimate aerobic fitness in normal gravity (Astrand and Ryhming, 1954; Lee, 1993). Due to spaceflight induced physiological alterations, such as shifts in extracellular fluid (e.g. plasma) volume, this method may not be valid during space flight. In addition, the ergometer onboard ISS is vibration-isolated and moves with the astronaut s application of force into the pedals. The effect of this movement on the VO2 of cycle exercise on ISS has not been quantified.

McCleary, Frank A.↗

Scientific Visualization & Modeling for Earth Systems Science Education

Providing research experiences for undergraduate students in Earth Systems Science (ESS) poses several challenges at smaller academic institutions that might lack dedicated resources for this area of study. This paper describes the development of an innovative model that involves students with majors in diverse scientific disciplines in authentic ESS research. In studying global climate change, experts typically use scientific visualization techniques applied to remote sensing data collected by satellites. In particular, many problems related to environmental phenomena can be quantitatively addressed by investigations based on datasets related to the scientific endeavours such as the Earth Radiation Budget Experiment (ERBE). Working with data products stored at NASA's Distributed Active Archive Centers, visualization software specifically designed for students and an advanced, immersive Virtual Reality (VR) environment, students engage in guided research projects during a structured 6-week summer program. Over the 5-year span, this program has afforded the opportunity for students majoring in biology, chemistry, mathematics, computer science, physics, engineering and science education to work collaboratively in teams on research projects that emphasize the use of scientific visualization in studying the environment. Recently, a hands-on component has been added through science student partnerships with school-teachers in data collection and reporting for the GLOBE Program (GLobal Observations to Benefit the Environment).

Chaudhury, S. Raj↗

Comparison of the Effects of using Tygon Tubing in Rocket Propulsion Ground Test Pressure Transducer Measurements

This paper documents acoustics environments data collected during liquid oxygen- ethanol hot-fire rocket testing at NASA Marshall Space Flight Center in November- December 2003. The test program was conducted during development testing of the RS-88 development engine thrust chamber assembly in support of the Orbital Space Plane Crew Escape System Propulsion Program Pad Abort Demonstrator. In addition to induced environments analysis support, coincident data collected using other sensors and methods has allowed benchmarking of specific acoustics test measurement methodologies during propulsion tests. Qualitative effects on data characteristics caused by using tygon sense lines of various lengths in pressure transducer measurements is discussed here.

Farr, Rebecca A.↗

ICESat-2 Simulated Data from Airborne Altimetery

Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is scheduled to launch in 2015 and will carry onboard the Advanced Topographic Laser Altimeter System (ATLAS), which represents a new approach to spaceborne determination of surface elevations. Specifically, the current ATLAS design is for a micropulse, multibeam, photon-counting laser altimeter with lower energy, a shorter pulse width, and a higher repetition rate relative to the Geoscience Laser Altimeter (GLAS), the instrument that was onboard ICESat. Given the new and untested technology associated with ATLAS, airborne altimetry data is necessary (1) to test the proposed ATLAS instrument geometry, (2) to validate instrument models, and (3) to assess the atmospheric effects on multibeam altimeters. We present an overview of the airborne instruments and datasets intended to address the ATLAS instrument concept, including data collected over Greenland (July 2009) using an airborne SBIR prototype 100 channel, photon-counting, terrain mapping altimeter, which addresses the first of these 3 scientific concerns. Additionally, we present the plan for further simulator data collection over vegetated and ice covered regions using Multiple Altimeter Beam Experimental Lidar (MABEL), intended to address the latter two scientific concerns. As the ICESAT-2 project is in the design phase, the particular configuration of the ATLAS instrument may change. However, we expect this work to be relevant as long as ATLAS pursues a photon-counting approach.

Brunt, Kelly M.↗

Crew Autonomy Through Self-Scheduling: Operational Characterization

NASA’s future long-duration exploration missions (LDEMs) will encounter increasing communication transmission delays as they move farther from Earth-based ground stations. This necessitates a new approach, as crews can no longer rely on real-time support from ground planners and must self-schedule their own operational timelines effectively and efficiently. To enable this transition, our team has developed Playbook, a mission planning and scheduling tool. Our research focuses on quantifying scheduling performance using Playbook to inform the design and development of future features to streamline timeline creation. We also aim to propose standards and guidelines for autonomous crews in LDEMs. In the past year, we have focused on further validating and quantifying the effects of countermeasure aids on self-scheduling performance. There are two software aids in Playbook (self-scheduling platform): Suggested Fixes, which propose an edit to resolve violations within a timeline, and No-Go Zones, which highlight where activities should not be scheduled on a timeline. We have made significant progress in HERA Campaign 7 (C7) data collection, increasing the number of days crew must self-schedule from 4 to 8. As a result, almost 20% of the mission is self-scheduled by the analog astronauts. We have also started data collection on a controlled lab experiment designed to quantify performance effects due to the countermeasures. We expect to present the preliminary results from both efforts. Finally, we have conducted an exploratory analysis of NASA’s HERA Campaign 6 (C6), investigating the mission-level impacts of self-scheduling. We derived basic patterns and descriptive statistics to better characterize crew autonomy through self-scheduling. We also assessed if there are any individual indicators of preference for self-scheduling, such as experience or predilection for autonomy. Preliminary analysis indicates that the HERA C6 crew self-scheduled one out of four flexible activities, indicating unprompted adoption of self-scheduling as a concept of operation for crew autonomy.

analog↗

Communication-Aware Orbit Design for Small Spacecraft Swarms around Small Bodies

Exploration of small Solar System bodies has traditionally been performed by single monolithic spacecraft carrying a number of science instruments. However, science instruments typically cannot be operated simultaneously due to the instrument requirements including optimal viewing angle, surface illumination, altitude and ground resolution, power, and data constraints. This observation has motivated interest in multi-spacecraft architectures where a swarm of small spacecraft, each carrying a single science instrument, studies a small body after being deployed by a carrier spacecraft, which then collects data from the vehicles and relays it to Earth. Such architectures hold promise to yield significant improvements in mission efficiency, increases in data quality, and shorter mission duration. A key difficulty in the design of such missions is the selection of orbits for the small spacecraft, which must satisfy not only instrument requirements, but also strict inter-spacecraft communication and on-board storage constraints. To address this, in this paper, we present a novel computationally-efficient optimization algorithm for \emph{communication-aware design} of the orbits of a small spacecraft swarm orbiting a small body. The proposed approach captures constraints including instrument requirements, inter-spacecraft communication bandwidths, and on-board memory usage, and it can accommodate highly irregular gravity field models and surface geometries. We propose an efficient algorithm for optimization of instrument observations and inter-spacecraft communications; we then leverage the differentiable nature of the proposed algorithm to accelerate a gradient-based global search algorithm. Numerical simulations of a six-spacecraft swarm studying 433 Eros show that the proposed approach successfully identifies high-quality orbits, and significantly outperform communication-agnostic optimization techniques, resulting in a 10% increase in scientific returns and a 30% increase in the quality of the collected data.

Rahmani, Amir↗

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Soman, Vishwas V.↗

The Challenges of Field Testing the Traffic Management Advisor (TMA) in an Operational Air Traffic Control Facility

The Traffic Management Advisor (TMA), the sequence and schedule tool of the Center/TRACON Automation System (CTAS), was evaluated at the Fort Worth Center (ZFW) in the summer of 1996. This paper describes the challenges encountered during the various phases of the TMA field evaluation, which included system (hardware and software) installation, personnel training, and data collection. Operational procedures were developed and applied to the evaluation process that would ensure air safety. The five weeks of field evaluation imposed minimal impact on the hosting facility and provided valuable engineering and human factors data. The collection of data was very much an opportunistic affair, due to dynamic traffic conditions. One measure of the success of the TMA evaluation is that, rather than remove TMA after the evaluation until it could be fully implemented, the prototype TMA is in continual use at ZFW as the fully operational version is readied for implementation.

Hoang, Ty↗

UV-Visible Spectroscopic Method and Models for Assessment and Monitoring of Harmful Algal Blooms

The development of an enhanced predictive and early warning capability for the occurrence and impact of harmful algal blooms (HABs) would be of great benefit to coastal communities. A critical issue for early detection and monitoring of HABs is the need to detect harmful algal species within a mixed-species phytoplankton assemblage. Possession of UV-absorbing compounds called mycosporine-like amino acids (MAAs) may be one factor that allows HAB species to out-compete their phytoplankton neighbors. Possession of MAAs, which we believe can be inferred from strong UV-absorption signals in phytoplankton absorption coefficients, can be used as a flag for potential HAB outbreak. The goal of this project was to develop a solar simulating UV-visible incubator to grow HAB dinoflagellates, to begin MAA analysis of samples collected on global cruises, and to carry out initial experiments on HAB dinoflagellate species in pure culture. Our scientific objectives are to quantify MAA production and spectral induction mechanisms in HAB species, to characterize spectral absorption of MAAs, and to define the ecological benefit of MAAs (i.e. photoprotection). Data collected on cruises to the global oceans will be used to parameterize phytoplankton absorption in the UV region, and this parameterization could be incorporated into existing models of seawater optical properties in the UV spectral region. Data collected in this project were used for graduate fellowship applications by Elizabeth Frame. She has been awarded an EPA STAR fellowship to continue the work initiated by this project.

Mitchell, B. Greg↗

Flight Test Series 3: Flight Test Report

This document is a flight test report from the Operational perspective for Flight Test Series 3, a subpart of the Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) project. Flight Test Series 3 testing began on June 15, 2015, and concluded on August 12, 2015. Participants included NASA Ames Research Center, NASA Armstrong Flight Research Center, NASA Glenn Research Center, NASA Langley Research center, General Atomics Aeronautical Systems, Inc., and Honeywell. Key stakeholders analyzed their System Under Test (SUT) in two distinct configurations. Configuration 1, known as Pairwise Encounters, was subdivided into two parts: 1a, involving a low-speed UAS ownship and intruder(s), and 1b, involving a high-speed surrogate ownship and intruder. Configuration 2, known as Full Mission, involved a surrogate ownship, live intruder(s), and integrated virtual traffic. Table 1 is a summary of flights for each configuration, with data collection flights highlighted in green. Section 2 and 3 of this report give an in-depth description of the flight test period, aircraft involved, flight crew, and mission team. Overall, Flight Test 3 gathered excellent data for each SUT. We attribute this successful outcome in large part from the experience that was acquired from the ACAS Xu SS flight test flown in December 2014. Configuration 1 was a tremendous success, thanks to the training, member participation, integration/testing, and in-depth analysis of the flight points. Although Configuration 2 flights were cancelled after 3 data collection flights due to various problems, the lessons learned from this will help the UAS in the NAS project move forward successfully in future flight phases.

Unmanned↗

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗

Performance of MODIS Thermal Emissive Bands On-orbit Calibration Algorithms

Two nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (MODIS) are currently operated on-board the Terra and Aqua spacecrafts, launched in December 1999 and May 2002, respectively. Together, they have produced an unprecedented amount of science data products, which are widely used for the studies of changes in the Earth's system of land, oceans, and atmosphere. MODIS is a cross-track scanning radiometer, which uses a two-sided scan mirror and collects data continuously over a wide scan angle range (+/-55 degree relative to the instrument nadir) each scan of 1.47 seconds. It has 36 spectral bands with wavelengths ranging from visible (VIS) to long-wave infrared (LWIR). MODIS bands 1-19 and 26 are the reflective solar bands (RSB) and bands 20-25 and 27-36 are the thermal emissive bands (TEB). MODIS was developed and designed with improvements made over its heritage sensors (such as AVHRR and Landsat) and, in particular, with more stringent calibration requirements. Because of this, MODIS was built with a set of state-of-art on-board calibrators (OBC), which include a solar diffuser (SD), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly (SRCA), and a space view (SV) port. With the exception of view angle differences, MODIS OBC measurements and the Earth View (EV) observations are made via the same optical path. MODIS TEB have a total of 160 individual TEB detectors (10 per band), which are located on two cold focal plane assemblies (CFPA). For nominal on-orbit operation, the CFPA temperature is controlled at 83K via a passive radiative cooler. For the TEB, the calibration requirements at specified typical scene radiances are less than or equal to 1% with an exception for the fire detection (low gain) band. MODIS TEB on-orbit calibration is performed on a scan-by-scan basis using a quadratic calibration algorithm, and data collected from sensor responses to the onboard BB and SV. The BB serves as the thermal calibration source and the SV provides measurements for the sensor's background and offsets. MODIS on-board BB is a v-grooved plate with its temperature measured using 12 platinum resistive thermistors (PRT) uniformly embedded in the BB substrate. All the BB thermistors were characterized pre-launch with reference to the NIST temperature standards. Unlike typical BB operations in many heritage sensors, which have no temperature control capability, the MODIS on-board BB can be operated at any temperatures between instrument ambient (about 270K) and 315K and can also be varied continuously within this range. This feature has significantly enhanced the MODIS' capability of tracking and updating the TEB nonlinear calibration coefficients over its entire mission. Following a brief description of MODIS TEB on-orbit calibration methodologies and its onboard BB operational activities, this paper provides a comprehensive performance assessment of MODIS TEB quadratic calibration algorithm. It examines the scan-by-scan, orbit-by-orbit, daily, and seasonal variations of detector responses and associated impact due changes in the CFPA and instrument temperatures. Specifically, this paper will analyze the contribution by each individual thermal emissive source term (BB, scan cavity, and scan mirror), the impact on the Level 1 B data product quality due to pre-launch and on-orbit calibration uncertainties. A comparison of Terra and Aqua TEB on-orbit performance, lessons learned, and suggestions for future improvements will also be made.

Xiong, Xiaoxiong↗

Circadian temperature rhythms of older people

This collection of studies had the aim of exploring whether older (77+ years) men and women have circadian body temperature rhythms different from those of younger adults. A total of 20 older men and 28 older women were compared with either 22 young men or 14 middle-aged men in four protocols; all but the first protocol using a subset of the sample. The four protocols were: 1) 24 h, and 2) 72 h data collections on a normal laboratory routine (sleeping at night); 3) between 36 h and 153 h of field data collection at home; and 4) 36 h of a constant conditions routine (wakeful bedrest under temporal isolation) in the laboratory. There was some evidence for an age-related phase advance in temperature rhythm, especially for the older men on a normal routine, though this was not present in the constant conditions protocol, where 5 of the older subjects showed major delays in the timing of the body temperature trough (10:00 or later). There was no statistically significant evidence from any of the protocols that older subjects generally had lower temperature rhythm amplitudes than younger adults. Only when older men were compared with younger men in 24-h rhythm amplitude by simple t-test did any comparison involving amplitude achieve statistical significance (p < 0.05).

Non-NASA Center↗

Imaging Radar in the Mojave Desert-Death Valley Region

The Mojave Desert-Death Valley region has had a long history as a test bed for remote sensing techniques. Along with visible-near infrared and thermal IR sensors, imaging radars have flown and orbited over the area since the 1970's, yielding new insights into the geologic applications of these technologies. More recently, radar interferometry has been used to derive digital topographic maps of the area, supplementing the USGS 7.5' digital quadrangles currently available for nearly the entire area. As for their shorter-wavelength brethren, imaging radars were tested early in their civilian history in the Mojave Desert-Death Valley region because it contains a variety of surface types in a small area without the confounding effects of vegetation. The earliest imaging radars to be flown over the region included military tests of short-wavelength (3 cm) X-band sensors. Later, the Jet Propulsion Laboratory began its development of imaging radars with an airborne sensor, followed by the Seasat orbital radar in 1978. These systems were L-band (25 cm). Following Seasat, JPL embarked upon a series of Space Shuttle Imaging Radars: SIRA (1981), SIR-B (1984), and SIR-C (1994). The most recent in the series was the most capable radar sensor flown in space and acquired large numbers of data swaths in a variety of test areas around the world. The Mojave Desert-Death Valley region was one of those test areas, and was covered very well with 3 wavelengths, multiple polarizations, and at multiple angles. At the same time, the JPL aircraft radar program continued improving and collecting data over the Mojave Desert Death Valley region. Now called AIRSAR, the system includes 3 bands (P-band, 67 cm; L-band, 25 cm; C-band, 5 cm). Each band can collect all possible polarizations in a mode called polarimetry. In addition, AIRSAR can be operated in the TOPSAR mode wherein 2 antennas collect data interferometrically, yielding a digital elevation model (DEM). Both L-band and C-band can be operated in this way, with horizontal resolution of about 5 m and vertical errors less than 2 m. The findings and developments of these earlier investigations are discussed.

Farr, Tom G.↗

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗