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At least 397 records · Page 22

A Cooperative Human-Adaptive Traffic Simulation (CHATS)

NASA is considering the development of a Cooperative Human-Adaptive Traffic Simulation (CHATS), to examine and evaluate performance of the National Airspace System (NAS) as the aviation community moves toward free flight. CHATS will be specifically oriented toward simulating strategic decision-making by airspace users and by the service provider s traffic management personnel, within the context of different airspace and rules assumptions. It will use human teams to represent these interests and make decisions, and will rely on computer modeling and simulation to calculate the impacts of these decisions. The simulation objectives will be to examine: 1. evolution of airspace users and the service provider s strategies, through adaptation to new operational environments; 2. air carriers competitive and cooperative behavior; 3. expected benefits to airspace users and the service provider as compared to the current NAS; 4. operational limitations of free flight concepts due to congestion and safety concerns. This paper describes an operational concept for CHATS, and presents a high-level functional design which would utilize a combination of existing and new models and simulation capabilities.

Phillips, Charles T.↗

Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible while producing stable and accurate cloud properties. This paper discusses the algorithms and results of applying those techniques to more than 5 years of Terra MODIS, 3 years of Aqua MODIS, and 4 years of TRMM VIRS data.

Minis, Patrick↗

A Model-Based, Bayesian Solution for Characterization of Complex Damage Scenarios in Aerospace Composite Structures

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined.

H. Reed↗

Physical and Electrical Characterization of Aluminum Polymer Capacitors

Conductive polymer aluminum capacitor (PA capacitor) is an evolution of traditional wet electrolyte aluminum capacitors by replacing liquid electrolyte with a solid, highly conductive polymer. On the other hand, the cathode construction in polymer aluminum capacitors with coating of carbon and silver epoxy for terminal connection is more like a combination of the technique that solid tantalum capacitor utilizes. This evolution and combination result in the development of several competing capacitor construction technologies in manufacturing polymer aluminum capacitors. The driving force of this research on characterization of polymer aluminum capacitors is the rapid progress in IC technology. With the microprocessor speeds exceeding a gigahertz and CPU current demands of 80 amps and more, the demand for capacitors with higher peak current and faster repetition rates bring conducting polymer capacitors to the center o( focus. This is because this type of capacitors has been known for its ultra-low ESR and high capacitance. Polymer aluminum capacitors from several manufacturers with various combinations of capacitance, rated voltage, and ESR values were obtained and tested. The construction analysis of the capacitors revealed three different constructions: conventional rolled foil, the multilayer stacking V-shape, and a dual-layer sandwich structure. The capacitor structure and its impact on the electrical characteristics has been revealed and evaluated. A destructive test with massive current over stress to fail the polymer aluminum capacitors reveals that all polymer aluminum capacitors failed in a benign mode without ignition, combustion, or any other catastrophic failures. The extraordinary low ESR (as low as 3 mOMEGA), superior frequency independence reported for polymer aluminum capacitors have been confirmed. For the applications of polymer aluminum capacitors in space programs, a thermal vacuum cycle test was performed. The results, as expected, show no impact on the electrical characteristics of the capacitors. The breakdown voltage of polymer capacitors has been evaluated using a steady step surge test. Initial results show the uniform distribution in the breakdown voltage for polymer aluminum capacitors. Polymer aluminum capacitors with a combination of very high capacitance, extraordinary low ESR, excellent frequency stability, and non-ignite benign failure mode make it a niche fit in space applications for both today and future. Polymer capacitors are apparently also the best substitutes of the currently used MnO2-based tantalum capacitors in the low voltage range. However, some critical aspects are still to be addressed in the next phase of the investigation for PA capacitors. These include the long term reliability test of 125 C dry life and 85 C/85%RH humidity, the failure mechanism and de-rating, the radiation tolerance, and the high temperature performance. All of the above requires the continuous NEPP funding and support.

Liu, David (Donghang)↗

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands. These wetlands provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service (USFWS), Environmental Protection Agency (EPA), Minnesota Department of Natural Resources (MDNR), the National Oceanic and Atmospheric Administration (NOAA), and Ducks Unlimited (DU). WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) satellite data. WET 2.0 is trained to classify anywhere in the Great Lakes Basin. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan. Findings and maps produced in WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗

Waste Management Options for Long-Duration Space Missions: When to Reject, Reuse, or Recycle

The amount of waste generated on long-duration space missions away from Earth orbit creates the daunting challenge of how to manage the waste through reuse, rejection, or recycle. The option to merely dispose of the solid waste through an airlock to space was studied for both Earth-moon libration point missions and crewed Mars missions. Although the unique dynamic characteristics of an orbit around L2 might allow some discarded waste to intersect the lunar surface before re-impacting the spacecraft, the large amount of waste needed to be managed and potential hazards associated with volatiles recondensing on the spacecraft surfaces make this option problematic. A second option evaluated is to process the waste into useful gases to be either vented to space or used in various propulsion systems. These propellants could then be used to provide the yearly station-keeping needs at an L2 orbit, or if processed into oxygen and methane propellants, could be used to augment science exploration by enabling lunar mini landers to the far side of the moon.

Space processing↗

Norton-Thevenin Receptance Coupling (NTRC) as a Payload Analysis Tool

The NASA Engineering and Safety Center (NESC) has funded a study of a new method formulated by NASA Engineers called Norton-Thevenin Receptance Coupling (NTRC) to perform coupled loads analysis (CLA). The problem that NTRC attempts to solve is the dependency of the payload organization to high CLA costs, long schedules, lack of standard capabilities to evaluate multiple configurations and unavailability of loads when needed. NTRC solves the problem by providing a tool that payload developers can use to obtain loads at a fraction of the cost of a CLA at any time that it is required. While NTRC is not intended to replace the formal load cycles performed by the launch vehicle (LV) provider, it will provide the ability to reduce the conservatism in defining preliminary design loads, assess the impact of design changes between formal load cycles, perform trade studies and perform parametric loads analysis where many different design configurations can be evaluated with a minimum amount of data required from the LV provider. NTRC condenses all the necessary information into the launch vehicle to payload/s connection points or boundary degrees of freedom (BD). The launch vehicle model is represented by its impedance at its BDs; its forcing functions are represented by the acceleration at those BDs when the payload is absent and the latter is represented by its impedance at the same BDs. Payload responses are represented by transfer functions of selected response to interface BDs. The methodology has contributed to the Loads and Dynamics discipline advancement and successfully passed Peer Reviews. NTRC is exact in the frequency domain. Time domain replication and accuracy is outstanding. A second phase is envisioned to benchmark the whole set of CLA events for the Agency's most utilized Launch Vehicles, and ready it for operational deployment at NASA.

Kaufman, Daniel↗

Assessment of Crew Time for Maintenance and Repairs Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

Analytical-HZETRN Model for Rapid Assessment of Active Magnetic Radiation Shielding

The use of active radiation shielding designs has the potential to reduce the radiation exposure received by astronauts on deep-space missions at a significantly lower mass penalty than designs utilizing only passive shielding. Unfortunately, the determination of the radiation exposure inside these shielded environments often involves lengthy and computationally intensive Monte Carlo analysis. In order to evaluate the large trade space of design parameters associated with a magnetic radiation shield design, an analytical model was developed for the determination of flux inside a solenoid magnetic field due to the Galactic Cosmic Radiation (GCR) radiation environment. This analytical model was then coupled with NASA's radiation transport code, HZETRN, to account for the effects of passive/structural shielding mass. The resulting model can rapidly obtain results for a given configuration and can therefore be used to analyze an entire trade space of potential variables in less time than is required for even a single Monte Carlo run. Analyzing this trade space for a solenoid magnetic shield design indicates that active shield bending powers greater than 15 Tm and passive/structural shielding thicknesses greater than 40 g/cm2 have a limited impact on reducing dose equivalent values. Also, it is shown that higher magnetic field strengths are more effective than thicker magnetic fields at reducing dose equivalent.

Washburn, S. A.↗

Constraining Fossil Fuel CO2 Emissions from Urban Area Using OCO-2 Observations of Total Column CO2

Satellite observations of the total column dry-air CO2(XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals to optimize whole-city emissions, using a Bayesian inversion system and high-resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: “plume city” located in relatively flat terrain, represented by Riyadh and Cairo; “basin city” located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least number of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 5, 8, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.

Xinxin Ye↗

Weight and Balance Considerations for Electrified Aircraft Propulsion Applied to the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) Concept

The focus of this research was to understand the impact of batteries and electric motors on the weight and balance of the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) concept. Because electrified aircraft propulsion components can comprise a large part of an aircraft’s weight, their integration has a significant impact on the center of gravity location and the related stability characteristics of the aircraft. We developed an analysis framework that enabled estimating the weight and volume of electrified aircraft components, their contribution to the center of gravity location, and the stability and performance of the aircraft. Trades were performed on battery placement, wing attachment point, and electric motor power to determine their impact on figures of merit such as maximum takeoff weight and block fuel. We identified batteries, and to a lesser extent electric motors, as having a large impact on aircraft center of gravity and the required horizontal tail size for longitudinal static stability. Placing electric component weight as far forward as possible resulted in reductions in the horizontal tail size required to maintain static stability. Configurations output from this framework were also evaluated using a six-degree-of-freedom simulation to quantify dynamic stability characteristics. Although shifting weight forward reduced horizontal tail size, it negatively impacted dynamic stability. This study confirms that mass property modeling and dynamic simulation, which are usually limited in conceptual design, are important for electrified aircraft concepts.

electrified aircraft propulsion↗

Applications of Constituent Data Assimilation Systems

Organizations in Europe, Australia, and the United States have recently broadened constituent assimilation activities beyond that water vapor, which has been assimilated for years in the numerical weather prediction community. Many of these activities have focused on ozone, with some efforts focused on the entire suite of reactive constituents that control the ozone distribution. This talk will draw from results from the near real-time ozone data assimilation system being run by NASA's Data Assimilation Office. This system utilizes ozone observations from both the TOMS and the SBUV instrument to generate global synoptic maps of ozone. The initial application of this product is to provide ozone fields to assist in the atmospheric corrections' that are necessary for the retrieval of information from other NASA instruments. The validation of the ozone assimilation system shows that the assimilated product agrees well with independent HALOE and ozonesonde observations. This suggests that the product is of sufficient quality to be extended to other applications. This talk will enumerate these other applications and present initial results from exploratory research. The applications being considered include estimates of tropospheric ozone, provision of ozone fields for interactive retrievals, use of analysis increments from the assimilation to evaluate model performance, and development of long-term consistent three-dimensional global ozone fields. The results from the exploratory studies are promising, and help demonstrate how assumptions made in the p development of the ozone assimilation impact the other applications. For instance, RMS errors in the current product are large near the tropopause, which is sensitive to the specification of vertical correlation functions, which in turns impacts the amount of ozone analyzed to be in the troposphere. How these sensitivities impact the different applications will also be discussed.

Rood, Richard B.↗

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

Human Mars Landing Site and Impacts on Mars Surface Operations

NASA has begun a process to identify and discuss candidate locations where humans could land, live and work on the Martian surface. These locations are referred to as Exploration Zones (EZs). Given current mission concepts, an EZ is a collection of Regions of Interest (ROIs) that are located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. The EZ also contains a landing site and a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. These candidate EZs will be used by NASA as part of a multi‐year process of determining where and how humans could explore Mars. In the near term this process includes: (a) identifying locations that would maximize the potential science return from future human exploration missions, (b) identifying locations with the potential for resources required to support humans, (c) developing concepts and engineering systems needed by future human crews to conduct operations within an EZ, and (d) identifying key characteristics of the proposed candidate EZs that cannot be evaluated using existing data sets, thus helping to define precursor measurements needed in advance of human missions. Existing and future robotic spacecraft will be tasked to gather data from specific Mars surface sites within the representative EZs to support these NASA activities. The proposed paper will describe NASA's initial steps for identifying and evaluating candidate EZs and ROIs. This includes plans for the "First Landing Site/Exploration Zone Workshop for Human Missions to the Surface of Mars" to be held in October 2015 at which proposals for EZs and ROIs will be presented and discussed. It will also include a discussion of how these considerations are (or will be) taken into account as future robotic Mars missions are defined and developed. One or more representative EZs, drawn from similar previous studies involving Mars sites, will be used in the proposed paper to illustrate the process NASA envisions for gathering additional data from robotic precursor missions to assist in making a final selection of an EZ for human crews as well as the steps likely to occur during the buildup of a habitation site. Examples of the systems and operations likely to be used by human crews, assisted by robotic vehicles, to explore the scientific ROIs as well as developing the resource ROIs within the example EZs will be discussed.

Bussey, Ben↗

Next Gen One Portal Usability Evaluation

Each exercise device on the International Space Station (ISS) has a unique, customized software system interface with unique layouts / hierarchy, and operational principles that require significant crew training. Furthermore, the software programs are not adaptable and provide no real-time feedback or motivation to enhance the exercise experience and/or prevent injuries. Additionally, the graphical user interfaces (GUI) of these systems present information through multiple layers resulting in difficulty navigating to the desired screens and functions. These limitations of current exercise device GUI's lead to increased crew time spent on initiating, loading, performing exercises, logging data and exiting the system. To address these limitations a Next Generation One Portal (NextGen One Portal) Crew Countermeasure System (CMS) was developed, which utilizes the latest industry guidelines in GUI designs to provide an intuitive ease of use approach (i.e., 80% of the functionality gained within 5-10 minutes of initial use without/limited formal training required). This is accomplished by providing a consistent interface using common software to reduce crew training, increase efficiency & user satisfaction while also reducing development & maintenance costs. Results from the usability evaluations showed the NextGen One Portal UI having greater efficiency, learnability, memorability, usability and overall user experience than the current Advanced Resistive Exercise Device (ARED) UI used by astronauts on ISS. Specifically, the design of the One-Portal UI as an app interface similar to those found on the Apple and Google's App Store, assisted many of the participants in grasping the concepts of the interface with minimum training. Although the NextGen One-Portal UI was shown to be an overall better interface, observations by the test facilitators noted specific exercise tasks appeared to have a significant impact on the NextGen One-Portal UI efficiency. Future updates to the NextGen One Portal UI will address these inefficiencies.

Cross, E. V., III↗

Use of Shuttle Heritage Hardware in Space Launch System (SLS) Application-Structural Assessment

NASA is moving forward with the development of the next generation system of human spaceflight to meet the Nation's goals of human space exploration. To meet these goals, NASA is aggressively pursuing the development of an integrated architecture and capabilities for safe crewed and cargo missions beyond low-Earth orbit. Two important tenets critical to the achievement of NASA's strategic objectives are Affordability and Safety. The Space Launch System (SLS) is a heavy-lift launch vehicle being designed/developed to meet these goals. The SLS Block 1 configuration (Figure 1) will be used for the first Exploration Mission (EM-1). It utilizes existing hardware from the Space Shuttle inventory, as much as possible, to save cost and expedite the schedule. SLS Block 1 Elements include the Core Stage, "Heritage" Boosters, Heritage Engines, and the Integrated Spacecraft and Payload Element (ISPE) consisting of the Launch Vehicle Stage Adapter (LVSA), the Multi-Purpose Crew Vehicle (MPCV) Stage Adapter (MSA), and an Interim Cryogenic Propulsion Stage (ICPS) for Earth orbit escape and beyond-Earth orbit in-space propulsive maneuvers. When heritage hardware is used in a new application, it requires a systematic evaluation of its qualification. In addition, there are previously-documented Lessons Learned (Table -1) in this area cautioning the need of a rigorous evaluation in any new application. This paper will exemplify the systematic qualification/assessment efforts made to qualify the application of Heritage Solid Rocket Booster (SRB) hardware in SLS. This paper describes the testing and structural assessment performed to ensure the application is acceptable for intended use without having any adverse impact to Safety. It will further address elements such as Loads, Material Properties and Manufacturing, Testing, Analysis, Failure Criterion and Factor of Safety (FS) considerations made to reach the conclusion and recommendation.

Aggarwal, Pravin↗

Culture-Independent Microbial Air Profiling using a Spaceflight-Compatible Nanopore Sequencing Method

Microbial monitoring of spacecraft air is critical toward assessing the efficacy of microbial controls within the environmental control and life support systems to protect both the crew and the vehicle environment. Additionally, understanding of the atmospheric microbial profiles will be essential toward Mars-forward planetary protection planning. Currently, onboard the International Space Station (ISS), the air is monitored on a quarterly basis using an impaction air sampler. With this method, bacterial and fungal cells and spores are pulled onto plates containing growth medium. Following five days of ambient incubation onboard the ISS, the crew compares the growth to density charts and provides the approximations to the ground. Upon return of the culture plates to the Johnson Space Center’s Microbiology Laboratory, the isolates present are identified for crew health risk assessments. As NASA moves beyond the low-Earth orbit of ISS, sample return will be impractical. As such, a near real-time monitoring capability for the assessment of the spacecraft atmosphere is necessary. Significant strides have been made in recent years to utilize a molecular-based method for microbial profiling of ISS surfaces. The developed method is not dependent on microbial culture, thus removing the associated risk to the crew from high microbial levels, the bias toward detecting only the culturable organisms, and eliminates the need for sample return. The work described here details the evaluation of three different air sampling platforms whose product is amenable to downstream molecular processing and nanopore sequencing. The three samplers were compared in terms of mass and power requirements, ease-of -use, and the resulting data. For the two highest ranking samplers, a basic concept of operations was developed to transfer the sample into the already established preparation and sequencing process. Using these concepts of operations, an in-depth comparison of the molecular data generated was compared to the historical culture-based method. Data from both methods detailed similar microbial profiles, while the molecular method detailed microbial identifications that could not be identified through the culture-based method. The developed method will enable the generation of near real-time microbial profiles of the spacecraft atmosphere.

Brandon J Dunbar↗