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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study as of 2021. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

N Newby↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crew members and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80individual crew landings has been collected through this study as of September 2023. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3%) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

N Newby↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study as of September 2023. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

P Greenhalgh↗
DOE OSTI2022

Correlation between the relative blob fraction and plasma parameters in NSTX

Here, we present a simple analysis of the fraction of blobs observed in the scrape-off layer of NSTX and calculates the correlation between this blob fraction and various plasma parameters. The measurements were made using the gas puff imaging (GPI) diagnostic on a database of 103 shots from 2010 with neutral beam power P NBI = 0–6 MW. The blob fraction ranged from f b = 0.1% to 4.8%, where f b is defined as the fraction of time the GPI signal was larger than three times its average value within 0–7.5 cm outside the separatrix. The blob fraction generally decreased with increasing neutral beam injection power and was lower on average in H-mode plasmas than Ohmic and L-mode plasmas. The blob fraction had its highest correlation with the measured poloidal turbulence velocity and its radial gradient just inside the separatrix. This is in part consistent with a model in which the blob generation rate increases with the poloidal velocity shear.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Crowd Sourcing Medical Data Collection Using Medical Students

OBJECTIVE We undertook an upgrade of the Evidence Library database of NASA HRP’s Integrated Medical Model, assessing 120 medical conditions which integrate with a novel probabilistic risk assessment (IMPACT) tool of medical risk and resource utilization for long duration exploration human spaceflight. This data collection process included a selection of these conditions crowd sourced over one year via three 4-week medical student electives at the University of Colorado School of Medicine (IDPT 8059 Space Medicine: Human Spaceflight Factors & Medical Risk Assessment). Students undertook a rapid systematic review of each medical condition, under close preceptors with backgrounds in clinical medicine, library science, epidemiology, biostatistics, and evidence-based medicine. As part of the elective, students also received instruction in core space medicine concepts, evidence based medicine and problem based learning sessions as a flight surgeon supporting a simulated Mars mission. METHODS The list of 120 medical conditions includes both common, terrestrial illness/injury (epistaxis, diverticulitis) as well as spaceflight-specific ones (space adaptation conditions, EVA-related injuries). A rapid systematic review process was developed that would allow students to find the data for determining disease incidence/prevalence, return to definitive care (often a surrogate such as hospitalization rates), loss of crew life, and treatment duration. Each data point required a tailored, specialized search process using different databases and corresponding specialized search filters. Databases were selected on their ability to provide high quality literature in an efficient manner and prioritized by their ability to provide graded evidence via a set rubrics specific to human spaceflight. Students were responsible for performing all literature searches and identifying the highest quality available evidence for each data point. Completed student data sheets underwent initial review by faculty preceptors followed by a secondary editing review by the ExMC Clinical Science Team. RESULTS Over the course of three electives, approximately 105 medical conditions were researched by students using spreadsheets with pre-crafted search strategies. Overall, this process was successful in allowing students to perform the preponderance of work to update incidence, treatment duration, return to definitive care, and loss of crew life data points. Students were successful in running searches, identifying the necessary data points within the literature, and determining the types of terrestrial data that most aligns with the astronaut population for successful completion of their tasks. Limitations included variable student experience with search methodologies [PubMed], differing values of evidence grading [best practice evidence based medicine vs. relevant to spaceflight], and students’ unfamiliarity with spaceflight specific conditions. CONCLUSION Finding the relevant literature for medical conditions in spaceflight within terrestrial databases in a systematic method is time consuming and not intuitive. However, the stepwise process that balanced sensitivity with specificity allowed for students to be highly successful in a short amount of time. Additionally, as the process was refined over the course of three electives, preceptors were better able to anticipate where students were likely to encounter barriers, which allowed the course to be adjusted to account for certain data points needing more time for completion. This replicable process may be an efficient way to accomplish rapid systematic reviews for a large volume of data in a short amount of time.

J Lemery↗
DOE OSTI2024

Late-Stage Research Development and Demonstration Sub-activities Updates – FY24 Q3

Oak Ridge National Laboratory (ORNL), in collaboration with the Pacific Northwest National Laboratory (PNNL), the National Renewable Energy Laboratory (NREL), the Lawrence Berkeley National Laboratory (LBNL), and the Hummingbird Firm (a specialized consulting firm focused on promoting diversity, equity, and inclusion considerations), has initiated a national initiative known as the Heat Pump (HP) and Heat Pump Water Heater (HPWH) Field Validation Partnership. This effort involves active participation from numerous critical entities involved in research and market transformation within the field. The ORNL team is responsible for leading Late-Stage Research Development and Demonstration (LSRDD) among the four different topics. The overall outcomes of this project will be: (1) A structured Field Validation Partnership between DOE, the national labs, research, implementation, and market transformation organizations. This will result in unique way to coordinate field validation plans and collect relevant data from around the country into the HP and HPWH Field Validation Database. (2) The Field Validation Partnership will result in a continuous stream of information between DOE and the major industry players in the space of HPs and HPWHs. If desired, DOE could use this information to inform roadmaps related to HP and HPWH market adoption and research going forward. (3) The structure of this Partnership provides a mechanism for sharing lessons learned directly between Late-Stage RD&D, Building Integration Barriers, Regional Market and Policy and Workforce Development efforts. The result will be training content that is well-reviewed by the Partnership which will lead to a workforce that meets the industry’s quality and workforce supply demands. (4) The structure of this Partnership also provides an opportunity for regions to share lessons learned on policy and market transformation with each other through the Market and Policy core Committee. This report includes an update in Late-Stage Research Development and Demonstration.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Which Role Plays 2-Hydroxybutyric Acid on Insulin Resistance?

Type 2 Diabetes Mellitus (T2D) is defined as a chronic condition caused by beta cell loss and/or dysfunction and insulin resistance (IR). The discovering of novel biomarkers capable of identifying T2D and other metabolic disorders associated with IR in a timely and accurate way is critical. In this review, 2-hydroxybutyric acid (2HB) is presented as that upheaval biomarker with an unexplored potential ahead. Due to the activation of other metabolic pathways during IR, 2HB is synthesized as a coproduct of protein metabolism, being the progression of IR intrinsically related to the increasing of 2HB levels. Hence, the focus of this review will be on the 2HB metabolite and its involvement in glucose homeostasis. A literature review was conducted, which comprised an examination of publications from different databases that had been published over the previous ten years. A total of 19 articles fulfilled the intended set of criteria. The use of 2HB as an early indicator of IR was separated into subjects based on the number of analytes examined simultaneously. In terms of the association between 2HB and IR, it has been established that increasing 2HB levels can predict the development of IR. Thus, 2HB has demonstrated considerable promise as a clinical monitoring molecule, not only as an IR biomarker, but also for disease follow-up throughout IR treatment.

Sousa, André P. (ORCID:0000000314605361)↗
NASA NTRS1985

Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge.

Kawamura, K.↗
NASA NTRS1995

Advanced Dependent Pressure Vessel (DPV) nickel-hydrogen spacecraft cell and battery design

The dependent pressure vessel (DPV) nickel-hydrogen (NiH2) battery is being developed as a potential spacecraft battery design for both military and commercial satellites. Individual pressure vessel (IPV) NiH2 batteries are currently flying on more than 70 Earth orbital satellites and have accumulated more than 140,000,000 cell-hours in actual spacecraft operation. The limitations of standard NiH2 IPV flight battery technology are primarily related to the internal cell design and the battery packaging issues associated with grouping multiple cylindrical cells. The DPV cell design offers higher specific energy and reduced cost, while retaining the established IPV NiH2 technology flight heritage and database. The advanced cell design offers a more efficient mechanical, electrical and thermal cell configuration and a reduced parts count. The internal electrode stack is a prismatic flat-plate arrangement. The flat individual cell pressure vessel provides a maximum direct thermal path for removing heat from the electrode stack. The cell geometry also minimizes multiple-cell battery packaging constraints by using an established end-plateltie-rod battery design. A major design advantage is that the battery support structure is efficiently required to restrain only the force applied to a portion of the end cell. As the cells are stacked in series to achieve the desired system voltage, this increment of the total battery weight becomes small. The geometry of the DPV cell promotes compact, minimum volume packaging and places all cell terminals along the length of the battery. The resulting ability to minimize intercell wiring offers additional design simplicity and significant weight savings. The DPV battery design offers significant cost and weight savings advantages while providing minimal design risks. Cell and battery level design issues will be addressed including mechanical, electrical and thermal design aspects. A design performance analysis will be presented at both the cell and battery level. The DPV is capable of delivering up to 76 Watt-hours per kilogram (Wh/kg) at the cell level and 70 Wh/kg at the full battery level. This represents a 40 percent increase in specific energy at the cell level and a 60 percent increase in specific energy at the battery level compared to current IPV NiH2 technology.

Coates, Dwaine↗
NASA NTRS2008

A Physical Model to Estimate Snowfall over Land using AMSU-B Observations

In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Kim, Min-Jeong↗
DOE OSTI2023

Completeness of the NASA/IPAC Extragalactic Database (NED) Local Volume Sample

We introduce the NASA/IPAC Extragalactic Database (NED) Local Volume Sample (NED-LVS), a subset of ~1.9 million objects with distances out to 1000 Mpc. We use UV and IR fluxes available in NED from all-sky surveys to derive physical properties, and estimate the completeness relative to the expected local luminosity density. The completeness relative to near-IR luminosities (which traces a galaxy's stellar mass) is roughly 100% at D < 30 Mpc and remains moderate (70%) out to 300 Mpc. For brighter galaxies (≳L * ), NED-LVS is ~100% complete out to ~400 Mpc. When compared to other local Universe samples (GLADE and HECATE), all three are ~100% complete below 30 Mpc. At distances beyond ~80 Mpc, NED-LVS is more complete than both GLADE and HECATE by ~10%–20%. NED-LVS is the underlying sample for the NED gravitational-wave follow-up service (NED-GWF), which provides prioritized lists of host candidates for GW events within minutes of alerts issued by the LIGO–Virgo–KAGRA collaboration. We test the prioritization of galaxies in the volume of GW170817 by three physical properties, where we find that both stellar mass and inverse specific star formation rate place the correct host galaxy in the top 10. In addition, NED-LVS can be used for a wide variety of other astrophysical studies: galaxy evolution, star formation, large-scale structure, galaxy environments, and more. The data in NED are updated regularly, and NED-LVS will be updated concurrently. Consequently, NED-LVS will continue to provide an increasingly complete sample of galaxies for a multitude of astrophysical research areas for years to come.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of the occurrences of injury during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study. Injuries are classified as either contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), and Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), and then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings. The MDRI is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI also vastly under predicts those injuries as well. Given this data, it will be important to re-evaluate the expected injury rates for future vehicles, and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning.

N Newby↗
DOE OSTI2020

Residential Building Energy Efficiency Field Studies: Low-Rise Multifamily

In recent years, the U.S. Department of Energy (DOE) has conducted a series of research studies to validate energy efficient building technologies in the field. Much of the work has focused on single-family construction, and some has also addressed commercial energy codes. The work detailed in this DOE-funded study (EE0007616) focuses on low-rise multifamily buildings (three stories or fewer above grade) in various regions of the United States, and reports on how state-level building codes are being implemented, both in terms of observed characteristics and also in terms of estimated energy impacts. Nearly 100 buildings across four states—Illinois, Minnesota, Oregon, and Washington—were sampled, which represent a range of climate types from mild temperature to very cold continental. Both common entry and outdoor entry buildings were included, and a parallel research project evaluated envelope air tightness and current still-evolving air tightness testing methods. Finally, a set of structured interviews of building designers and other relevant professionals was carried to out to gain more insight into this market. To the greatest extent possible, the methodology developed under the project for low-rise multifamily buildings mirrored the approach established by Pacific Northwest National Laboratory (PNNL) for single-family residential buildings (https://www.energy.gov/eere/buildings/downloads/residential-building-energy-code-field-study). This included the general approach to sampling, recruitment, and data collection, as well as data analysis and presentation. The range of permitting dates for the sites encompassed two energy code cycles in most regions. All states in the study had adopted a variation of the International Energy Conservation Code (IECC) for the structure of their state code. The low-rise multifamily occupancy presents a hybrid building type: most of the building’s conditioned floor area was covered by the residential chapter of the code while portions of the building (such as corridors and common spaces) fell under the commercial code chapter. The key items assessed in this work were: Building Shell—exterior wall insulation, ceiling insulation, foundation insulation, windows. Common Areas—HVAC and lighting. Living Units—lighting, ventilation. A few items were not assessed in detail, given their relative paucity in this occupancy type; these included duct leakage, pipe insulation, and hot water circulation controls. Building characteristics were collected via a combination of architectural, mechanical, electrical, and plumbing plan reviews and field inspections, and entered into a spreadsheet-based tool that was later queried to build a database. Data went through quality control both upon arrival and via a later semi-automated review and assurance process. Most of the data are presented graphically so that the reader can quickly assess compliance with the applicable energy codes (both by state and by code year). As a final step, EnergyPlus™ simulations were created for all buildings in the study to estimate both the as-found energy use intensity (EUI) and the energy and CO 2 that could be saved if features that were found to not meet code minimums were brought up to code. The savings estimates were tabulated for each of the four states in the study. The research team found that the single-family approach was largely applicable to low-rise multifamily buildings. This applies to both the data collection and the prototype EUI analysis. Most of the occupied space is living units and falls under residential energy codes, and many characteristics use similar envelope construction and relatively straightforward mechanical systems and lighting. One of the most challenging aspects of this work was to build an effective spreadsheet-based data collection instrument that could allow efficient collection of both building plan and field data. The research team is of the view that other methods could be equally effective if the work is done carefully with diligent quality control. The primary findings for the work center around the thermal envelope and mechanical systems and lighting at the sites: For thermal envelope components, the majority of buildings met or were better than the prescriptive code.This suggests that building designers and builders are aware of code requirements. In some cases, surveyed buildings were designed to qualify for energy efficiency certification programs. These buildings made up at least 20% of sampled buildings in each state. Almost all buildings met mechanical system efficiency requirements (for both living units and common areas). In some cases, sites employed systems that were considerably more efficient than required by the applicable energy code. Dwelling units had a majority of high-efficacy lighting, often in excess of the state’s residential code requirements. While high-efficacy fixtures were also typical in common areas (corridors and stairwells), lighting power densities (LPDs) in these areas were sometimes higher than levels dictated by the applicable part of the state commercial energy code. The simulation models run on a series of low-rise multifamily prototypes, informed by a composite of the field data collected, calculated annual EUIs of between 20 and 50 kBtu/ft2-yr, with the range representing the effects of both building characteristics and building location (climate zone). A detailed process (based on simulations of prototype buildings) was used to estimate the amount of avoided energy use that would occur if 100% adherence to energy codes were attained. The results indicated modest savings are attainable for items such as window thermal performance and common area lighting. The result is overall only a modest potential for additional energy savings, averaging about 10% of EUI.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

HarDWR - Raw Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Switched source data from collecting records from each state independently to using the WestDAAT dataset v1.0 - Initial public release Description In order to hold a water right in the western United States, an entity, (e.g., an individual, corporation, municipality, sovereign government, or non-profit) must register a physical document with the state's water regulatory agency. State water agencies each maintain their own database containing all registered water right documents within the state, along with relevant metadata such as the point of diversion and place of use of the water. All western U.S. states have digitized their individual water rights databases, as well as geospatial data defining the areas in which water rights are managed. Each state maintains and provides their own water rights data in accordance with individual state regulations and standards. In addition, while all states make their water rights publicly available, each provides their records in unique formats, meaning that file types, field availability, and terms vary from state to state. This leads to additional challenges to managing resources which cross state lines, or conducting consistent multi-state water analyses. For the first version of HarDWR, we collected the water rights databases from 11 Western States of the United States. In order to preform regional analyses with the collected data, the raw records had to be harmonized into one single format. The Water Data Exchange (WaDE) is a program dedicated to the sharing of water-related data for the Western U.S. in a singular consistent format. Created by the Western States Water Council (WSWC) to facilitate the collection and dissemination of water data among WSWC's member states and the public, WaDE provides an important service for those interested in water resource planning and management in their focus region. Of the services which WaDE provides, the one of the most interesting is the WestDAAT dataset, which is a collection of water rights data provided by the 18 WSWC member states that have been standardized into a single format, much like we had done on a more limited scale with HarDWR v1. For this version of HarDWR we decided to use WestDAAT, specifically a snapshot created in Feburary 2024, as our water rights source data. A full explanation of the benefits gained from this switch can be found in the description of the updated Harmonized Water Rights Records v2.0, but in short it has allowed us to focus more of our efforts on answering research questions and gaining a more realistic understanding of how water rights are allocated. For more information on how the data for WestDAAT was collected, please see the WaDE data summary. Terms of Use While WaDE works directly with the state agencies to collect and standardize the water rights records, the ultimate authority for the water rights data remains the individual states. Each state, and their respective water right authorities, have made their water right records available for non-commercial reference uses. In addition, the states make no guarantees as to the completeness, accuracy, or timeliness of their respective databases, let alone the modifications which we, the authors of this paper, have made to the collected records. None of the states should be held liable for using this data outside of its intended use. As several of the states update their water rights databases daily, the information provided here is not the latest possible, and should not be used for legal purposes. WestDAAT itself has irregular updates. Additional questions about the data the source states provided should be directed to the respective state agencies (see methods.csv and organization.csv files described below). In addition, although data was presented here was not collected directly from the states, several states requested specifically worked disclaimers when sharing their data. These disclaimers are included here as an acknowledgement from where the water rights data is primarily sourced. Colorado: "The data made available here has been modified for use from its original source, which is the State of Colorado. THE STATE OF COLORADO MAKES NO REPRESENTATIONS OR WARRANTY AS TO THE COMPLETENESS, ACCURACY, TIMELINESS, OR CONTENT OF ANY DATA MADE AVAILABLE THROUGH THIS SITE. THE STATE OF COLORADO EXPRESSLY DISCLAIMS ALL WARRANTIES, WHETHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. The data is subject to change as modifications and updates are complete. It is understood that the information contained in the Web feed is being used at one's own risk." Montana: "The Montana State Library provides this product/service for informational purposes only. The Library did not produce it for, nor is it suitable for legal, engineering, or surveying purposes. Consumers of this information should review or consult the primary data and information sources to ascertain the viability of the information for their purposes. The Library provides these data in good faith but does not represent or warrant its accuracy, adequacy, or completeness. In no event shall the Library be liable for any incorrect results or analysis; any direct, indirect, special, or consequential damages to any party; or any lost profits arising out of or in connection with the use or the inability to use the data or the services provided. The Library makes these data and services available as a convenience to the public, and for no other purpose. The Library reserves the right to change or revise published data and/or services at any time." Oregon: "This product is for informational purposes and may not have been prepared for, or be suitable for legal, engineering, or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information." File Descriptions The unmodified February, 2024 WestDAAT snapshot is composed of nine files. Below is a brief description of each file, as well as how they were utilized for HarDWR. WaDEDataDictionaryTerms.xlsx: As the file's name implies, this is a data dictionary for all of the below named files. This file describes the column names for each of the following files, with the exception of citation.txt which does not have any columns. The descriptions for each file are divided by tab,with the same name as their associated file, within this document. allocationamount.csv: The "main" file of the group, it contains the water right records for each state. Of particular note, each water right is broken down into one or more water allocations. Allocations may be withdrawn from one or more locations, or even multiple allocations associated with a particular location. This is a more subtle and realistic representation of how water is used than what was available in the first version of HarDWR. For the records from some states, this can mean that multiple allocations listed under a single right will appear as rows within this file. citation.txt: A combination of contact information for WaDE personnel, disclaimer about how the data should be used, and guidelines for citing WestDAAT. methods.csv: A file describing the source and method by which WaDE collected water rights data from each state. organization.csv: A file listing the water rights authoritative agencies for each state. sites.csv: This file provides the geographic, and other descriptors, of the physical location of allocations, called 'sites'. To reiterate, it is possible for one allocation to be associated with multiple sites, as well as one site to be associated with multiple allocations. The two descriptors which we were most interested in where the site's coordinates, as well as whether the site was classified as a Point of Diversion (POD) or a Place of Use (POU). As a general rule, PODs are geographic points, while POUs are areas typically represented as property boundaries or irregularly shaped polygons. sites_pouGeometry.csv: For those allocations with a POU site, this file contains the defining points for the associated polygons. variables.csv: A file describing the units in which an allocation's water amount is reported within WestDAAT. This information is essentially a repeat of the 'AllocationFlow_CFS' and 'AllocationVolume_AF' columns within allocationamount.csv, at least for our purposes. watersources: This file describes the source of water from which each site extracts from. For our purposes, this table was used to determine whether the water came from Surface Water, Groundwater, or Unspecified Water.

Lisk, Matthew↗
NASA NTRS2002

Novel Advancements in Internet-Based Real Time Data Technologies

AZ Technology has been working with MSFC Ground Systems Department to find ways to make it easier for remote experimenters (RPI's) to monitor their International Space Station (ISS) payloads in real-time from anywhere using standard/familiar devices. AZ Technology was awarded an SBIR Phase I grant to research the technologies behind and advancements of distributing live ISS data across the Internet. That research resulted in a product called "EZStream" which is in use on several ISS-related projects. Although the initial implementation is geared toward ISS, the architecture and lessons learned are applicable to other space-related programs. This paper presents the high-level architecture and components that make up EZStream. A combination of commercial-off-the-shelf (COTS) and custom components were used and their interaction will be discussed. The server is powered by Apache's Jakarta-Tomcat web server/servlet engine. User accounts are maintained in a My SQL database. Both Tomcat and MySQL are Open Source products. When used for ISS, EZStream pulls the live data directly from NASA's Telescience Resource Kit (TReK) API. TReK parses the ISS data stream into individual measurement parameters and performs on-the- fly engineering unit conversion and range checking before passing the data to EZStream for distribution. TReK is provided by NASA at no charge to ISS experimenters. By using a combination of well established Open Source, NASA-supplied. and AZ Technology-developed components, operations using EZStream are robust and economical. Security over the Internet is a major concern on most space programs. This paper describes how EZStream provides for secure connection to and transmission of space- related data over the public Internet. Display pages that show sensitive data can be placed under access control by EZStream. Users are required to login before being allowed to pull up those web pages. To enhance security, the EZStream client/server data transmissions can be encrypted to preclude interception. EZStream was developed to make use of a host of standard platforms and protocols. Each are discussed in detail in this paper. The I3ZStream server is written as Java Servlets. This allows different platforms (i.e. Windows, Unix, Linux . Mac) to host the server portion. The EZStream client component is written in two different flavors: JavaBean and ActiveX. The JavaBean component is used to develop Java Applet displays. The ActiveX component is used for developing ActiveX-based displays. Remote user devices will be covered including web browsers on PC#s and scaled-down displays for PDA's and smart cell phones. As mentioned. the interaction between EZStream (web/data server) and TReK (data source) will be covered as related to ISS. EZStream is being enhanced to receive and parse binary data stream directly. This makes EZStream beneficial to both the ISS International Partners and non-NASA applications (i.e. factory floor monitoring). The options for developing client-side display web pages will be addressed along with the development of tools to allow creation of display web pages by non-programmers.

Myers, Gerry↗
DOE OSTI2024

A machine learning estimator trained on synthetic data for real-time earthquake ground-shaking predictions in Southern California

Abstract After large-magnitude earthquakes, a crucial task for impact assessment is to rapidly and accurately estimate the ground shaking in the affected region. To satisfy real-time constraints, intensity measures are traditionally evaluated with empirical Ground Motion Models that can drastically limit the accuracy of the estimated values. As an alternative, here we present Machine Learning strategies trained on physics-based simulations that require similar evaluation times. We trained and validated the proposed Machine Learning-based Estimator for ground shaking maps with one of the largest existing datasets (<100M simulated seismograms) from CyberShake developed by the Southern California Earthquake Center covering the Los Angeles basin. For a well-tailored synthetic database, our predictions outperform empirical Ground Motion Models provided that the events considered are compatible with the training data. Using the proposed strategy we show significant error reductions not only for synthetic, but also for five real historical earthquakes, relative to empirical Ground Motion Models.

Environmental Sciences & Ecology↗
DOE OSTI2020

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2018

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2018 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2018. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. A statistically significant increasing trend was identified in the frequency of FTLR demands for emergency power system (EPS) and high pressure core spray (HPCS) EDGs and a statistically significant decreasing trend was identified in the frequency of run > 1H hours for EPS and HPCS EDGs.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

A sensitive 1.5 GHz radio survey around the north ecliptic pole

A 29.3 sq deg region surrounding the north ecliptic pole (NEP; alpha = 18h00m, delta = +66 deg 30 min) was mapped with the Very Large Array at 1.5 GHz to support the deepest portion of the ROSAT all-sky soft X-ray survey. The resulting VLA-NEP survey catalog contains 2435 radio sources with flux densities in the range of 0.3-1000 mJy, including over 200 fainter than 1 mJy. The 28 fields of the inner 1.5 deg have noise levels sigma approximately equals 60 mu-Jy, and the 85 fields centered between 1.5 and 3.0 deg from the NEP have sigma approximately equals 120 mu-Jy. The typical spatial resolution is 20 sec HPBW, and most positions are accurate to less than 2 sec. Approximately 6% of the sources are found to be extended with size greater than 30 sec. We have compared the VLA-NEP catalog with four other radio catalogs made at lower resolution, as well as with the NASA Extragalactic Database and find counterparts for approximately 18% of the VLA-NEP objects. The normalized, differential radio source count is in agreement with previous studies. Between 1 and 150 mJy the slope of the log N-log S relation is 0.68 +/- 0.03. The catalog and related tables are available electronically.

Kollgaard, Ronald I.↗