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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗
NASA NTRS2011

Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers

Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (<50 ventricular premature complexes, VPCs); and 2) 12 dogs with occult DCM: 11/12 dogs had increased M-mode measurements (LVIDd . 49mm and/or LVIDs . 40mm) and 5/11 dogs had also >100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P < 0.05) between groups. Principal component factor analysis identified a 5-factor model with 81.4% explained variance. QRS dipolar and non-dipolar voltages, Cornell voltage criteria and QRS waveform residuum were increased significantly (P < 0.05), whereas mean HF QRS amplitude was decreased significantly (P < 0.05) in dogs with occult DCM. For the 5 selected parameters the prediction of occult DCM was performed using a binary logistic regression model with Chi-square tested significance (P < 0.01). ROC analyses showed that the five selected ECG parameters could identify occult ECG with sensitivity 89% and specificity 83%. Results suggest that 12-lead A-ECG might improve diagnostic value of short-duration ECG in earlier detection of canine DCM as five selected ECG parameters can with reasonable accuracy identify occult DCM in Doberman Pinschers. Future extensive clinical studies need to clarify if 12-lead A-ECG could be useful as an additional screening test for canine DCM.

Spiljak, M.↗
DOE OSTI2023

Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data

Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory networks and a number of methods with different learning frameworks have been developed to address this problem. Here, we present an expanded benchmarking study of eleven recent network inference methods on seven published scRNA-seq datasets in human, mouse, and yeast considering different types of gold standard networks and evaluation metrics. We evaluate methods based on their computing requirements as well as on their ability to recover the network structure. We find that, while most methods have a modest recovery of experimentally derived interactions based on global metrics such as Area Under the Precision Recall curve, methods are able to capture targets of regulators that are relevant to the system under study. Among the top performing methods that use only expression were SCENIC, PIDC, MERLIN or Correlation. Addition of prior biological knowledge and the estimation of transcription factor activities resulted in the best overall performance with the Inferelator and MERLIN methods that use prior knowledge outperforming methods that use expression alone. We found that imputation for network inference did not improve network inference accuracy and could be detrimental. Comparisons of inferred networks for comparable bulk conditions showed that the networks inferred from scRNA-seq datasets are often better or at par with the networks inferred from bulk datasets. Our analysis should be beneficial in selecting methods for network inference. At the same time, this highlights the need for improved methods and better gold standards for regulatory network inference from scRNAseq datasets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Information theory analysis of sensor-array imaging systems for computer vision

Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

Huck, F. O.↗
NASA NTRS2010

Use of Drying Technologies for Resource Recovery from Solid Wastes and Brines

Long term storage of unprocessed biological wastes and human wastes can present major health issues and a loss of potential resources. Space vehicles and planetary habitats are typically resource-scarce or resource-limited environments for long-term human habitation. To-date, most of the resources will need to be supplied from Earth, but this may not be possible for long duration human exploration. Based on present knowledge, there is only very limited in-situ resources on planetary habitats. Hence, the opportunity to "live off the land" in a planetary habitat is limited. However, if we assume that wastes generated by human explorers are viewed as resources, there is great potential to utilize and recycle them, thereby reducing the requirements for supply Earth and enabling the "live off the land" exploration scenario. Technologies used for the recovery of resources from wastes should be reliable, safe, easy to operate, fail-proof, modular, automated and preferably multifunctional in being capable of handling mixed solid and liquid wastes. For a lunar habitat, energy does not appear to be the major driving factor amongst the technologies studied. Instead, reliability appears to be more important[1] . This paper reports studies to date on drying technologies to remove water from solid wastes and brines. Experimental performance data obtained for recovery water from wastes and brine are presented. Simplicity of operation of hardware and energy efficiency are discussed. Some improvements and modifications to hardware were performed. Hopefully, this information will assist in future efforts in the "downselection" of technologies for recovery of water and resources from solid wastes and brines.

Wignarajah, Kanapathipillai↗
NASA NTRS2006

Numerical Propulsion System Simulation

The NASA Glenn Research Center, in partnership with the aerospace industry, other government agencies, and academia, is leading the effort to develop an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). NPSS is a framework for performing analysis of complex systems. The initial development of NPSS focused on the analysis and design of airbreathing aircraft engines, but the resulting NPSS framework may be applied to any system, for example: aerospace, rockets, hypersonics, power and propulsion, fuel cells, ground based power, and even human system modeling. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the NASA Aeronautics Research Mission Directorate Fundamental Aeronautics Program and the Advanced Virtual Engine Test Cell (AVETeC). NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes capabilities to facilitate collaborative engineering. The NPSS will provide improved tools to develop custom components and to use capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities extend NPSS from a zero-dimensional simulation tool to a multi-fidelity, multidiscipline system-level simulation tool for the full development life cycle.

Naiman, Cynthia↗
NASA NTRS1993

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project.

Holcomb, Lee↗
NASA NTRS1994

NASA High Performance Computing and Communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 1(X)-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientists' abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project, exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects, as well as summaries of early accomplishments and the significance, status, and plans for individual research and development programs within each project. Areas of emphasis include benchmarking, testbeds, software and simulation methods.

Holcomb, Lee↗
NASA NTRS2013

Human Factors Evaluation of Conflict Detection Tool for Terminal Area

A conflict detection and resolution tool, Terminal-area Tactical Separation-Assured Flight Environment (T-TSAFE), is being developed to improve the timeliness and accuracy of alerts and reduce the false alert rate observed with the currently deployed technology. The legacy system in use today, Conflict Alert, relies primarily on a dead reckoning algorithm, whereas T-TSAFE uses intent information to augment dead reckoning. In previous experiments, T-TSAFE was found to reduce the rate of false alerts and increase time between the alert to the controller and a loss of separation over the legacy system. In the present study, T-TSAFE was tested under two meteorological conditions, 1) all aircraft operated under instrument flight regimen, and 2) some aircraft operated under mixed operating conditions. The tool was used to visually alert controllers to predicted Losses of separation throughout the terminal airspace, and show compression errors, on final approach. The performance of T-TSAFE on final approach was compared with Automated Terminal Proximity Alert (ATPA), a tool recently deployed by the FAA. Results show that controllers did not report differences in workload or situational awareness between the T-TSAFE and ATPA cones but did prefer T-TSAFE features over ATPA functionality. T-TSAFE will provide one tool that shows alerts in the data blocks and compression errors via cones on the final approach, implementing all tactical conflict detection and alerting via one tool in TRACON airspace.

Verma, Savita Arora↗
NASA NTRSDate not supplied

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring a multitude of capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for a particular mission is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) to defining gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities, gaps, and KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed. The paper will contain a summary of the approximately 60 gaps. Gaps are classified as to their type (architecture, knowledge, technology, developmental, or engineering) depending on the magnitude of the gap. The paper will provide brief overviews of a few major technology challenges and the technologies being considered, but will reference detailed papers for a more thorough treatment of the challenges and state of the art. Data analysis of the gaps is in work and results are not currently available for this abstract. It is anticipated the paper will include examples of select KPPs with descriptions as to why these are the relevant measures. Additionally some KPPs will be graphically presented over time to show progress to date and when performance targets need to be achieved to support exploration missions. Graphical summaries of how gaps closures with near term mission elements support follow-on mission elements will be provided.

Life Support↗
NASA NTRS1989

Rationale for Mars Rover/Sampler Return mission

A Mars Rover/Sample Return (MRSR) mission is currently being studied for the late 1990's. The objectives of the mission are to better understand the origin and evolution of Mars, to search for evidence of former life, and to improve the knowledge of the Martian environment in preparation for subsequent human exploration. Having formed in a different part of the Solar System from Earth, Mars will provide clues that will better enable the discrimination between conflicting theories of Solar System formations. Mars is also a natural laboratory on which a wide range of geologic and meteorological processes have operated under conditions very different from those on Earth. Samples are needed so that the full range of analytical techniques available here on Earth can be applied to the study of these issues. The rover provides the mobility needed to access different materials, and can be equipped with an analytical capability so that the planet can be sampled intelligently. The rover will also provide the means of exploring the planet on a human scale and performing a wide range of in situ measurements at different locations. Different mission scenarios are currently being studied with the goal of achieveing sample return before the end of the century.

Carr, Michael H.↗
NASA NTRS2002

An infrared system for monitoring Drosophila motility during microgravity

Presently, the precise mechanisms of the aging process are unknown. Examination and comprehension of the aging process in other species could lead to significant advances in the understanding of human aging. Drosophila melanogaster (fruit fly), commonly used for aging studies, is a widely studied organism in terms of behavior, development, and genetics. Previous microgravity experiments have shown a significant decrease in the life span of young male Drosophila after microgravity exposure. This decrease in lifespan may be related to locomotor activity, a convenient measure of overall physiological performance. This study describes the design and performance of a Drosophila Infrared Motility Monitoring System (DIMMS). The DIMMS uses a unique design of two infrared (IR) beams per fly to measure the locomotor activity of 240 flies. Locomotor activity is measured in terms of number of IR crossings per unit time, instantaneous velocity, and continuous velocity. Ground-based results using the DIMMS equipment agree well with previous values for Drosophila locomotor velocity. DIMMS is an improvement over equipment previously used due to its ability to continuously monitor locomotor activity throughout short-duration microgravity exposure. DIMMS is also lightweight, compact, and power efficient. DIMMS has been flight tested onboard NASA's KC-135 reduced gravity research aircraft and a Nike-Orion sounding rocket.

unmanned↗
NASA NTRS2005

Incremental Scheduling Engines: Cost Savings through Automation

As humankind embarks on longer space missions farther from home, the requirements and environments for scheduling the activities performed on these missions are changing. As we begin to prepare for these missions it is appropriate to evaluate the merits and applicability of the different types of scheduling engines. Scheduling engines temporally arrange tasks onto a timeline so that all constraints and ob.jectives are met and resources are not over-booked. Scheduling engines used to schedule space missions fall into three general categories: batch, mixed-initiative, and incremental. This paper, presents an assessment of the engine types, a discussion of the impact of human exploration of the moon and Mars on planning and scheduling, and the applicability of the different types of scheduling engines. This paper will pursue the hypothesis that incremental scheduling engines may have a place in the new environment; they have the potential to reduce cost, to improve the satisfaction of those who execute or benefit from a particular timeline (the customers), and to allow astronauts to plan their own tasks and those of their companion robots.

Jaap, John↗
NASA NTRS2005

Standardized Action Modules for Humanoid Robot Control

Humanoid robots could reduce the risks of hazardous work by replacing humans in dangerous environments and they could be useful helpers in environments designed primarily for humans. Currently, no robot is capable enough to fulfill either of these roles for any practical application, and the Humanoid Project at the Jet Propulsion Laboratory's Bio-Inspired Technologies and Systems group is striving to change that. For this summer, our goal was to endow a Fujitsu HOAP 2 humanoid robot with the necessary intelligence and knowledge to autonomously assemble a cubical frame structure from tubular bars and corner joints. Performing such a complicated task requires that the robot have a robust control architecture that allows for a multitude of abilities and Operation modes. We have designed and implemented a modular control architecture that allows reusability of existing code and the integration of work by many team members into the larger control system while providing an easy way to implement later improvements. Such a control system has allowed us to achieve important milestones in the humanoid robot assembly task.

Csaszar, Ambrus↗
NASA NTRSDate not supplied

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis mission, the development of an exploration portable life support system (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the design, verification, and testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the exploration pressure garment system (xPGS) and simulating five extravehicular activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. This data was compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗
NASA NTRS2024

Multi-Agency Ensemble Forecast of Wildfire Air Quality in the United States: Toward Community Consensus of Early Warning

Wildfires pose increasing risks to human health and properties in North America. Due to large uncertainties in fire emission, transport, and chemical transformation, it remains challenging to accurately predict air quality during wildfire events, hindering our collective capability to issue effective early warnings to protect public health and welfare. Here we present a new real-time Hazardous Air Quality Ensemble System (HAQES) by leveraging various wildfire smoke forecasts from three U.S. federal agencies (NOAA, NASA, and Navy). Compared to individual models, the HAQES ensemble forecast significantly enhances forecast accuracy. To further enhance forecasting performance, a weighted ensemble forecast approach was introduced and tested. Compared to the unweighted ensemble mean, the multilinear regression weighted ensemble reduced fractional bias by 34% in the major fire regions, false alarm rate by 72%, and increased hit rate by 17%. Finally, we improved the weighted ensemble using quantile regression and weighted regression methods to enhance the forecast of extreme air quality events. The advanced weighted ensemble increased the PM2.5 exceedance hit rate by 55% compared to the ensemble mean. Our findings provide insights into the development of advanced ensemble forecast methods for wildfire air quality, offering a practical way to enhance decision-making support to protect public health.

Yunyao Li↗
NASA NTRSDate not supplied

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis Mission, the development of an Exploration Portable Life Support Subsystem (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the Design, Verification, and Testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the Exploration Pressure Garment System (xPGS) and simulating five Extravehicular Activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. These data were compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗
NASA NTRS2022

Irrigation Characterization Improved by the Direct Use of SMAP Soil Moisture Anomalies Within a Data Assimilation System

Prior soil moisture data assimilation (DA) efforts to incorporate human management features such as agricultural irrigation has only shown limited success. This is partly due to the fact that observational rescaling approaches for bias correction used in soil moisture DA systems are less effective when unmodeled processes such as irrigation are the dominant source of systematic biases. In this article, we demonstrate an alternative approach, i.e. anomaly correction for overcoming this limitation. Unlike the rescaling approaches, the proposed method does not scale remote sensing soil moisture retrievals to the model climatology, but it extracts the temporal variability information from the retrievals. The study demonstrates this approach through the assimilation of soil moisture retrievals from the Soil Moisture Active Passive mission into the Noah land surface model. The results demonstrate that DA using the anomaly correction method can better capture the effect of irrigation on soil moisture in agricultural areas while providing comparable performance to the DA integrations using rescaling approaches in non-irrigated areas. These findings emphasize the need to reduce inconsistencies between remote sensing and the models so that assimilation methods can employ information from remote sensing more directly to develop representations of unmodeled processes such as irrigation.

soil moisture↗