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NASA NTRS2007

Improvements to NASA's Debris Assessment Software

NASA's Debris Assessment Software (DAS) has been substantially revised and expanded. DAS is designed to assist NASA programs in performing orbital debris assessments, as described in NASA s Guidelines and Assessment Procedures for Limiting Orbital Debris. The extensive upgrade of DAS was undertaken to reflect changes in the debris mitigation guidelines, to incorporate recommendations from DAS users, and to take advantage of recent software capabilities for greater user utility. DAS 2.0 includes an updated environment model and enhanced orbital propagators and reentry-survivability models. The ORDEM96 debris environment model has been replaced by ORDEM2000 in DAS 2.0, which is also designed to accept anticipated revisions to the environment definition. Numerous upgrades have also been applied to the assessment of human casualty potential due to reentering debris. Routines derived from the Object Reentry Survival Analysis Tool, Version 6 (ORSAT 6), determine which objects are assessed to survive reentry, and the resulting risk of human casualty is calculated directly based upon the orbital inclination and a future world population database. When evaluating reentry risks, the user may enter up to 200 unique hardware components for each launched object, in up to four nested levels. This last feature allows the software to more accurately model components that are exposed below the initial breakup altitude. The new DAS 2.0 provides an updated set of tools for users to assess their mission s compliance with the NASA Safety Standard and does so with a clear and easy-to-understand interface. The new native Microsoft Windows graphical user interface (GUI) is a vast improvement over the previous DOS-based interface. In the new version, functions are more-clearly laid out, and the GUI includes the standard Windows-style Help functions. The underlying routines within the DAS code are also improved.

Opiela, J.↗

NASA NTRS2006

TOPEX Radar Altimeter Engineering Assessment Report Final Update-Side B Turn-On to End-of-Mission on October 9, 2005

This is the thirteenth and final report in a series of TOPEX Radar Altimeter Engineering Assessment Reports. The initial TOPEX Radar Altimeter Engineering Assessment Report, in February 1994, presented performance results for the NASA Radar Altimeter on the TOPEX/POSEIDON spacecraft, from its launch in August 1992 to February 1994. Since the time of that initial report and prior to this report, there have been eleven interim supplemental Engineering Assessment Reports, issued in March 1995, May 1996, March 1997, June 1998, August 1999, September 2000, June 2001, March 2002, May 2003, April 2004 and September 2005. The sixth supplement in September 2000 was the first assessment report that addressed Side B performance, and presented the altimeter performance from Side B turn-on until the end of calendar year 1999. This report extends the performance assessment of Side B to the final collection of data on October 9, 2005, and includes the performance assessment of Jason-1, the TOPEX follow-on mission, launched on December 7, 2001. This report provides some comparisons of Side A and Side B performance.

Lockwood, Dennis W.↗

NASA NTRS2008

Skill Assessment in Ocean Biological Data Assimilation

There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

Gregg, Watson W.↗

NASA NTRS2014

On Noise Assessment for Blended Wing Body Aircraft

A system noise study is presented for the blended-wing-body (BWB) aircraft configured with advanced technologies that are projected to be available in the 2025 timeframe of the NASA N+2 definition. This system noise assessment shows that the noise levels of the baseline configuration, measured by the cumulative Effective Perceived Noise Level (EPNL), have a large margin of 34 dB to the aircraft noise regulation of Stage 4. This confirms the acoustic benefits of the BWB shielding of engine noise, as well as other projected noise reduction technologies, but the noise margins are less than previously published assessments and are short of meeting the NASA N+2 noise goal. In establishing the relevance of the acoustic assessment framework, the design of the BWB configuration, the technical approach of the noise analysis, the databases and prediction tools used in the assessment are first described and discussed. The predicted noise levels and the component decomposition are then analyzed to identify the ranking order of importance of various noise components, revealing the prominence of airframe noise, which holds up the levels at all three noise certification locations and renders engine noise reduction technologies less effective. When projected airframe component noise reduction is added to the HWB configuration, it is shown that the cumulative noise margin to Stage 4 can reach 41.6 dB, nearly at the NASA goal. These results are compared with a previous NASA assessment with a different study framework. The approaches that yield projections of such low noise levels are discussed including aggressive assumptions on future technologies, assumptions on flight profile management, engine installation, and component noise reduction technologies. It is shown that reliable predictions of component noise also play an important role in the system noise assessment. The comparisons and discussions illustrate the importance of practical feasibilities and constraints in aircraft system noise studies, which include aerodynamic performance, propulsion efficiency, flight profile limitation and many other factors. For a future aircraft concept to achieve the NASA N+2 noise goal it will require a range of fully successful noise reduction technology developments.

Guo, Yueping↗

NASA NTRS2014

Open Rotor Tone Shielding Methods for System Noise Assessments Using Multiple Databases

Advanced aircraft designs such as the hybrid wing body, in conjunction with open rotor engines, may allow for significant improvements in the environmental impact of aviation. System noise assessments allow for the prediction of the aircraft noise of such designs while they are still in the conceptual phase. Due to significant requirements of computational methods, these predictions still rely on experimental data to account for the interaction of the open rotor tones with the hybrid wing body airframe. Recently, multiple aircraft system noise assessments have been conducted for hybrid wing body designs with open rotor engines. These assessments utilized measured benchmark data from a Propulsion Airframe Aeroacoustic interaction effects test. The measured data demonstrated airframe shielding of open rotor tonal and broadband noise with legacy F7/A7 open rotor blades. Two methods are proposed for improving the use of these data on general open rotor designs in a system noise assessment. The first, direct difference, is a simple octave band subtraction which does not account for tone distribution within the rotor acoustic signal. The second, tone matching, is a higher-fidelity process incorporating additional physical aspects of the problem, where isolated rotor tones are matched by their directivity to determine tone-by-tone shielding. A case study is conducted with the two methods to assess how well each reproduces the measured data and identify the merits of each. Both methods perform similarly for system level results and successfully approach the experimental data for the case study. The tone matching method provides additional tools for assessing the quality of the match to the data set. Additionally, a potential path to improve the tone matching method is provided.

Bahr, Christopher J.↗

NASA NTRS2016

NASA Human System Risk Assessment Process

NASA utilizes an evidence based system to perform risk assessments for the human system for spaceflight missions. The center of this process is the multi-disciplinary Human System Risk Board (HSRB). The HSRB is chartered from the Chief Health and Medical Officer (OCHMO) at NASA Headquarters. The HSRB reviews all human system risks via an established comprehensive risk and configuration management plan based on a project management approach. The HSRB facilitates the integration of human research (terrestrial and spaceflight), medical operations, occupational surveillance, systems engineering and many other disciplines in a comprehensive review of human system risks. The HSRB considers all factors that influence human risk. These factors include pre-mission considerations such as screening criteria, training, age, sex, and physiological condition. In mission factors such as available countermeasures, mission duration and location and post mission factors such as time to return to baseline (reconditioning), post mission health screening, and available treatments. All of the factors influence the total risk assessment for each human risk. The HSRB performed a comprehensive review of all potential inflight medical conditions and events and over the course of several reviews consolidated the number of human system risks to 30, where the greatest emphasis is placed for investing program dollars for risk mitigation. The HSRB considers all available evidence from human research and, medical operations and occupational surveillance in assessing the risks for appropriate mitigation and future work. All applicable DRMs (low earth orbit for 6 and 12 months, deep space for 30 days and 1 year, a lunar mission for 1 year, and a planetary mission for 3 years) are considered as human system risks are modified by the hazards associated with space flight such as microgravity, exposure to radiation, distance from the earth, isolation and a closed environment. Each risk has a summary two-page assessment representing the state of knowledge/evidence of that risk, available risk mitigations, traceability to the Space Flight Human System Standards (SFHSS) and program requirements, and future work required. These data then can drive coordinated budgets across the Human Research Program, the International Space Station, Crew Health and Safety and Advanced Exploration System budgets to provide the most economical and timely mitigations. The risk assessments were completed for the 6 DRMs and serve as the baseline for which subsequent research and technology development and crew health care portfolios can be assessed. The HSRB reviews each risk at least annually or when new evidence/information is available that adds to the body of evidence. The current status of each risk can be reported to program management for operations, budget reviews and general oversight of the human system risk management program.

Francisco, D.↗

NASA NTRS2015

Technical Report Series on Global Modeling and Data Assimilation: Soil Moisture Active Passive (SMAP) Project Assessment Report for the Beta-Release L4_SM Data Product - Volume 40

ubRMSE↗

NASA NTRS2015

Inconsistent Strategies to Spin up Models in CMIP5: Implications for Ocean Biogeochemical Model Performance Assessment

During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to- model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

histories↗

NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

NASA NTRS2018

Using Remote Sensing to Assess of Growth and Distribution for Floating Invasive Plants and Growth Response Times to Altered Environments

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA (U. S. Dept. of Agriculture)-sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency of invasive plant management in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used to map area of plant coverage and estimate biomass density to aid operations and assess management impacts on plant communities. Modeling at local and watershed scales using the SWAT (Soil Water Assessment Tool) modeling tool provides insight into land-use effects on water quality. Environmental variability in the Delta occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), and light effects. These provide response parameters for plant growth models in response to environmental variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plant communities in the California Delta.

Floating↗

NASA NTRSDate not supplied

Virtual Fit Assessment: Validation using Historical Spacesuit Fit Data

Virtual fit tests using 3D body scans have provided a cost-effective means to predictively assess spacesuit fit for the current and future astronaut population. However, fit is a complex issue influenced by physical interferences, subjective preference, and many other factors. Fit can substantially differ between the type of hardware, environmental conditions, and tasks being performed. Namely, fit changes across different contexts, such as 3D printed mockup evaluations, pressurized one-g suited test events, neutral buoyancy and other training events, and flight extravehicular activities (EVA). These challenges make it difficult to validate virtual fit frameworks to physical suit sizing. This study proposes a new method of validation using the wealth of historically archived suit fit data. Physically Assessed Fit (PAF) data was assessed from astronauts and test volunteers who wore the legacy Extravehicular Mobility Unit (EMU). The data was collected during the past decades at NASA and considered to be most reliable and dependable. Each participant was 3D scanned for body shape and spacesuit-critical dimensions were measured per NASA guidelines. The participants’ size preference for hard upper torso (HUT) assembly was retrieved from their pressurized suit fit check records. Fit assessments were also updated after one-g EVA training, neutral buoyancy training, and EVA flights. Virtually Assessed Fit (VAF) was done by overlaying the CAD model of a HUT with the 3D body scans of the PAF participants. Each body scan was iteratively adjusted for the position inside the HUT to minimize the suit-to-body contact interference while satisfying a set of prescribed requirements. Then the residual contact area, depth, and volume were quantified as VAF metrics. This process was repeated for the different HUT sizes, including medium, large, and extra-large. Statistical modeling is currently in progress and will be presented at the conference. A statistical classifier will be developed to predict a fit probability for different HUT sizes as a function of the corresponding person’s VAF metrics. The HUT size with the highest fit probability will constitute the most likely size selection for the person, and the prediction will be compared against the corresponding PAF data. The participant data will be randomly pre-grouped into either a model development or validation subset. While the model development subset will be used to build the probability model, the validation subset will be used to assess the model accuracy. Also, the locations and magnitudes of suit-body-contacts will be estimated from VAF. This information can identify the critical suit geometry and body shape features that influence suit fit. The variations found in PAF size selections by subjects with similar VAF metrics will allow for investigations into subjective preferences, for example, tight versus loose fit. Overall, this study is expected to provide a structured validation of a virtual suit fit framework, which has not been possible in the past. The outcome can also provide useful insights and potential limitations for interpreting virtual fit tests for future spacesuit designs and population accommodation.

Han Kim↗

NASA NTRS2021

Application of Quasi-Deep Convective Clouds Method for VIIRS and MODIS TEB Calibration Assessments

A technique that utilizes quasi-deep convective clouds (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has been proven viable. The Terra and Aqua MODIS and S-NPP and NOAA-20 VIIRS TEB calibration uses a nonlinear algorithm whose nonlinear coefficients rely on on-orbit blackbody (BB) warm-up and cooldown operations for updates. However, a limited BB temperature range affects the calibration’s accuracy particularly for cold scenes. The deep convective clouds (DCC) core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments; more specifically, for the evaluation of the offset term’s effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide with the advantage of removing solar reflectance effects during daytime, thus enhancing the assessment’s accuracy for the midwave infrared TEB. In this paper, this qDCC method is applied to the Terra MODIS and VIIRS TEB; and their stabilities are assessed using long-term qDCC trending measurements over the instruments’ missions. The measurements from bands with an 11-μm wavelength are used to identify the DCC pixels. The 11-μm bands, MODIS band 31 and VIIRS bands M15 and I5, are stable throughout the MODIS and VIIRS missions and have shown excellent calibration accuracy and noise performance. Hence, using these bands as references, a normalization method is employed to enhance the accuracy of the stability and consistency assessments. The S-NPP VIIRS TEB show stable trends over the instrument’s mission. The S-NPP-to-N20 VIIRS comparison shows their TEB measurements are consistent over qDCC. The Terra MODIS TEB also show stable performance – except for bands 27, 29, and 30. Terra MODIS band 30 shows a large downward trend throughout the mission, while bands 27 and 29 show slight, upward drifts. Lastly, a calibration correction using qDCC assessments is discussed and intended to be used in a future calibration algorithm collection.

MODIS↗

NASA NTRSDate not supplied

Predictive Modeling to Assess and Address Challenges and Limitations Associated with Clinical Care and Decision Support in Deep Space

Probabilistic risk assessment (PRA) is a method for assessing and integrating the risk of failure in a multivariate system. While it is often applied by engineers designing complex machines, it could also be applied to humans to assess the probability of a health “failure” treating diseases as the multiple “variables” and the human as the “complex machine.” The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) was developed to apply PRA to assess medical risk for exploration spaceflight and inform the design of medical systems for space flight. The NASA engineering community utilizes event-driven and fault tree probabilistic techniques to classify risk in the space flight environment by leveraging the inherent knowledge of complex space flight system design and testing to quantify risk. However, in harmonizing the risk of human space flight, answering the question of “How do we balance astronaut health, performance and resource risks with other engineering risks on exploration space missions?” remains a profoundly challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the Human Research Program’s efforts to represent space fight human health and performance risks quantitatively.

L Mcintyre↗

NASA NTRSDate not supplied

pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment

Metadata quality is essential to effective data discovery and has become increasingly vital as more Earth Science data sets become available. The Common Metadata Repository (CMR) hosts metadata describing NASA’s Earth Observation data products, which are archived across 12 Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, conducts metadata quality assessments to ensure that these data products are discoverable, accessible, and usable. To achieve these goals, the ARC team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency. ARC uses a combination of manual and automated methods to assess these three components and identify areas of improvement; the team then collaborates with the DAACs to resolve any findings. To streamline this process, ARC is currently developing a host of scripts, known as pyQuARC, to automate metadata quality assessments as much as possible. pyQuARC is an open source library for Earth Observation Metadata Quality Assessment, and the tool utilizes ARC’s metadata quality assessment framework to make basic validation checks, pinpoint inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identify opportunities for more descriptive and robust information. Since pyQuARC is also customizable, other users can make modifications as needed, and future metadata standards can also be implemented. Once pyQuARC is fully developed, it will support multiple schema types to serve the broader EOSDIS metadata community. This presentation will provide an overview of pyQuARC and its process of development while showcasing the tool’s valuable features and uses.

Jenny Wood↗

NASA NTRSDate not supplied

Can Resilience Assessments Inform Early Design Human Factors Decision-making?

There is a growing call among researchers for tighter coupling between human factors and human reliability assessments. In this research, we explore if early design stage resilience assessments can help bridge some of the gaps between human factors and human reliability assessments. Resilience in systems is their ability to recover reasonably and operate within acceptable bounds during failures and unexpected events. The fmdtools toolkit allows designers to assess the resilience of a system by modeling the human error and machine-related failure propagation in both nominal and faulty scenarios during the early design stages. As a result, the fmdtools toolkit has a low-fidelity dynamic human reliability assessment component built into it. In this paper, we study if the results from the fmdtools simulations can help inform and prioritize human factors design decision-making, resulting in tighter coupling between human factors and human reliability assessments during the design process. Specifically, we explore the results from a rover design example to understand the types of information that can help guide human factor-related decision-making.

Resilience-based Design↗

NASA NTRSDate not supplied

Connecting Federal Agencies to Satellite Earth Observations: NASA’s Satellite Needs Working Group Assessment Process

The Satellite Needs Working Group (SNWG), part of the U.S. Group on Earth Observations (USGEO), surveys agencies across the U.S. Government to identify the satellite Earth observations each agency needs to fulfill its high-priority objectives and responsibilities. Around 20 civilian agencies participate in the SNWG survey every two years. After receiving the surveys, the National Aeronautics and Space Administration (NASA) conducts an in-depth evaluation of each agency's needs in collaboration with fellow satellite Earth data providers, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS). This assessment process, which takes place over an eight-month period, is divided into distinct phases. NASA first assembles an assessment team with the necessary subject matter expertise to evaluate each submitted need. An in-depth interview with each submitting agency then follows, featuring discussion of current and upcoming satellite missions as well as potential new activities that NASA, NOAA, and/or USGS could undertake to meet the agency's needs. The assessment teams then further evaluate these potential activities or solutions to identify how many agencies would benefit and estimate how much their level of satisfaction would increase. Solutions expected to have broad-reaching and significant agency benefits are proposed by NASA for funding. SNWG agencies receive an assessment report for each submitted need, in which the tri-agency assessment teams provide a detailed evaluation of the agency need, information on relevant satellite missions, and links to specific datasets or training resources. The SNWG Management Office at NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) contributes to NASA’s SNWG assessment in a variety of capacities, including statistical analysis of the survey responses to identify trends and similar needs across multiple agencies. The Management Office also provides analytics for the new proposed solutions, demonstrating and quantifying their potential value. For activities that receive funding, the Management Office manages the implementation process and works to maximize the benefit to SNWG agencies via a Stakeholder Engagement Program.

Katrina Virts↗

NASA NTRSDate not supplied

Independent Reliability Assessment of the Laser Transmitter for the ESA-NASA Laser Interferometer Space Antenna (LISA) Program

As part of the laser development process, NASA’s Goddard Space Flight Center (GSFC) requested support from the NASA Engineering and Safety Center (NESC) to independently assess the Technology Readiness Level (TRL) of the LISA Laser System (LS). The independent assessment included the following tasks: (a) assess the design for weaknesses and suggest improvements to mitigate risks, (b) assess the laser reliability plan for weaknesses and suggest improvements to mitigate risks and improve effectiveness, and (c) assess the current redundancy plan on laser subsystems for weaknesses and suggest improvements to mitigate risks and improve effectiveness. The presentation will focus on the assessment findings and the current development progress of the LISA laser to meet the mission requirements with a delivery of a form, fit, and functional TRL6 laser to the LISA mission by late 2023.

Laser Interferometry↗

NASA NTRSDate not supplied

Independent Technical Assessment of NASA and External Quantum Sensing Capability

The recent FY 2020 federal Research and Development Budget Priorities memo addresses the leadership need in Quantum Information Science (QIS) directing agencies to “prioritize QIS research and development (R&D), which will build the technical and scientific base necessary to explore the next generation of QIS theory, devices, and applications.” Quantum Sensing (QS) is an integral part of QIS. NASA is a key part of the directive to forward American space exploration and commercialization by providing “capabilities that have broad potential applications in space and on Earth.” QS provides an arena for NASA to demonstrate leadership in both areas of the administrative directive. QS uses quantum properties to achieve unprecedented measurement sensitivity and performance, including quantum-enhanced methodologies that outperform their classical counterparts. Typical quantum sensors exploit techniques such as atomic systems, matter waves, quantum entanglement, quantum superposition of states, quantum illumination methods, and manipulation of photons and atoms, in general. Guided by advancements in our ability to generate, manipulate, and control quantum systems, the emerging quantum sensing technologies promise unrivalled sensitivity, resolution, and precision, potentially leading to game-changing applications. Significant gains include technologies important for a range of NASA missions such as remote sensing, in situ measurements, metrology, interferometry, quantum communication, ranging, imaging, radar and lidar receivers, and gravity measurements. NASA Engineering and Safety Center has convened an independent external panel, comprising of Quantum Sensing Experts from Government, DoD, academia, and Federally funded Research and Development Center to conduct an independent technical assessment of the agency's capabilities in Quantum Sensing to understand NASA's internal needs and competencies related to Quantum Sensing and compare agency capabilities with those available externally including industry, academia, and other government agencies. The outcomes of the assessment will help the agency in establishing appropriate strategies and investments to develop and maintain the state-of-the-art sensing competence and capabilities required to meet the agency’s future needs. The External Experts Panel (EEP) is collaborating with HQ, various NASA Center and the representatives in the NASA Quantum Sensing Community of Practice (QS CoP), a part of NASA Sensors and Instrumentation Technical Fellow Technical Discipline Team, in obtaining common, current understanding of agency mission needs where QS can be an important enabler for future needs, and any programs, projects, assets, and technologists working in QS. The EEP organized a Quantum Sensing Workshop of practitioners from industry, academia, other government agencies, external experts, and interested NASA personnel to gather the assessment information. EEP also conducted information gathering on the industry at large, educational institutions, and other government agency research efforts for capture in the assessment database. At the conclusion of this assessment, EEP team will develop findings and conclusions describing NASA’s capabilities for the mission needs, NASA's relative position on new, enabling technologies, and an analysis of the gaps that may present any risks to near-term or far-term mission needs. This presentation will give details of the NASA and External Quantum Sensing Assessment outcomes, findings, observations, and its recommendation to NASA as how it can advance Quantum Sensing technologies and techniques for its science and explorations related missions.

External Quantum Sensing Capability↗