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At least 307 records · Page 17

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NASA NTRSDate not supplied

RCA: Modeling Tools for CLmax Prediction

TACP06 is aimed at further research in maturing eddy-resolving modeling tools, in their accuracy and efficiency, and demonstrating the tools for application to the prediction of aircraft maximum lift (CLmax). The goal is to achieve CLmaxprediction accuracy of the same level as in aircraft certification flight tests. This will require comparison of various modeling approaches against experimental results from the planned wind tunnel tests, down selecting an approach, further maturing the technology and validating against flight test data. Advances in computational fluid dynamics (CFD) over the last several decadeshas fundamentally changed the aerospace design process. Advanced simulation capabilities not only enable reductions in ground-based and in-flight testing requirements, but also provide added physical insight, enable superior designs at reduced cost and risk, and open upnew frontiers in aerospace vehicle design and performance. The NASA sponsored CFD Vision 2030 Study, while highlighting these accomplishments, brought out several challenges and deficiencies in the computational technology and developed a research roadmap for advancing the state-of-the-art required for enabling NASA missions in aeronautics and space applications. Based on TC TACP01 research completed in May 2018, it became clear that unsteady flow simulation capability is needed for expanding the role of CFD across the entire flight envelope to enable design of future advanced aircraft and space vehicles, and that capability will be the primary outcome of this technical challenge.

Mujeeb R Malik↗

NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

Natural Language Processing↗

NASA NTRS2022

Space Weather Modeling and Prediction for Intermediate Time-scales

Much of solar activity within a sunspot cycle occurs as bursts, or 'seasons' of strong activity over several months, separated by periods of much less activity. The most important space weather effects occur during these bursts. Previous modeling and forecasting efforts have focused on time-scales of hours-to-days and decades-to-centuries. The recent discovery of Rossby waves in the Sun, together with recently developed global models of solar MHD Rossby waves and their interactions with differential rotation and spot-producing magnetic fields, reveal the opportunity to simulate and predict the occurrence, strength and location of enhanced activity bursts a few weeks up to several months in advance. We now have a golden opportunity to fill in this gap in time-scales of forecasting space weather. This requires a) continuous observations of solar Rossby waves by various techniques; b) development of coupled nonlinear MHD models that simulate both global Rossby waves and the much smaller spatial scale emergence of new active regions; c) application of advanced data assimilation techniques to couple surface observations to update the model-system to integrate forward in time for creating forecasts months ahead. Then it will be possible to build operational prediction models to meet the needs of customers and stakeholders, including support of future NASA missions, regarding what kind and level of space weather to expect a few weeks to several months ahead.

SMD↗

NASA NTRSDate not supplied

Advances in PSP Testing in LaRC High Reynolds Number Facilities

The use of luminescent coatings for the global measurement of surface aerodynamic properties at full-flight Reynolds numbers has been ongoing at the NASA Langley Research Center since the late 1990s, beginning with Temperature Sensitive Paint (TSP) for boundary layer analysis at the 0.3-m Transonic Cryogenics Tunnel. Since then, significant work has been made to extend these measurements to pressure using Pressure Sensitive Paint (PSP) as well as develop systems for application in larger scale, full-flight Reynolds number facilities, such as the National Transonic Facility (NTF). Recently, a system for the measurement of time-resolved pressure using recently developed unsteady PSP (uPSP) formulations has been designed and implemented in the Transonic Dynamics Tunnel (TDT). The use of PSP (or uPSP) in either of these large scale, full-fight Reynolds number wind tunnels is complicated by the fact that both facilities operate best in oxygen deficient environments; however, the PSP technique relies on the presence of oxygen to work. The NTF is typically operated in cryogenic conditions, which is achieved using liquid nitrogen. In this facility, temperatures can reach as low as 116 K (-250 °F) with nominal oxygen concentrations of less than 50 ppm. This has resulted in the development of specialized PSP formulations that can operate in the cryogenic environment with the introduction of low amounts of oxygen (typically less than 2000 ppm) for PSP response. Likewise, to achieve full-flight Reynolds number conditions in the TDT, the atmosphere in the tunnel is replaced with a “heavy gas” of R-134A (1,1,1,2-tetrafluoroethane), which also has minimal oxygen native in the flow. The use of uPSP in this case will also depend on the introduction of trace amounts of oxygen, with the precise concentrations to be determined in an upcoming test. This presentation will describe some recent advancements that have been made for PSP measurements in both facilities. For the NTF system, there has been significant development of enhanced lighting for use at cryogenic conditions, as well as improvements in the application efficiency of the PSP. Furthermore, there are efforts underway to incorporate advanced data analysis techniques to acquire additional surface aerodynamic properties using the PSP technique that can yield not only improved experimental efficiency, but also provide data needed for next generation vehicle design and development. For the uPSP system in TDT, significant efforts to improve the data transfer rates to a high-performance computing environment for analysis are underway and performance and initial results from the system in the heavy-gas environment will be presented.

Pressure Sensitive Paint↗

NASA NTRS2022

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning↗

NASA NTRSDate not supplied

Human Factors Research Needs for In-Time Aviation Safety Management Systems (IASMS) Design: Enabling the NASA “Sky for All” Future Airspace Vision

Integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System. Addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers, is essential for realizing the vision. The proposal, if accepted, will discuss safety management system challenges and how the concept of In-time Aviation Safety Management Systems addresses the need. It will also discuss human factors challenges involved in future integrated safety management, including trust, over-reliance, human-optimized data visualization, human-autonomy teaming, training, communication and dissemination of data, situation awareness, task load, and accountability.

Lawrence J Prinzel III↗

NASA NTRS2023

Contractor Support Building #7 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Work Plan

This Work Plan documents the proposed field sampling activities for a per- and polyfluoroalkyl substances (PFAS) Site Assessment at the Contractor Support Building (CSB) #7 at Kennedy Space Center (KSC). The Work Plan provides a background of the historical activities that occurred at CSB #7, and the limited environmental investigations performed at CSB #7. The proposed Site Assessment activities at CSB #7 include the advancement of a soil lithologic boring to 60 feet below ground surface, the installation of a staff gauge in site surface water, perform direct push groundwater sampling at eight locations, and collect four surface water samples. Sampling details, depths, and locations are presented in the Work Plan. The Work Plan was presented to the KSC Remediation Team in the form of an Advance Data Package in February 2023. Following STRIVES approval, the CSB #7 PFAS Site Assessment Work Plan will be formally submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗

NASA NTRS2023

Former SLF Fire and Rescue Building SWMU #120 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Work Plan

This Work Plan documents the proposed field sampling activities for a per- and polyfluoroalkyl substances (PFAS) Site Assessment at the Former Space Shuttle Landing Facility (SLF) Fire and Rescue Building (FRB) at Kennedy Space Center (KSC). The Work Plan provides a background of the historical activities that occurred at the SLF FRB, and the limited environmental investigations performed at the SLF FRB. The proposed Site Assessment activities at SLF FRB includes the collection of soil samples from eight locations, the advancement of a soil lithologic boring to 60 feet below ground surface, the installation of a staff gauge in site surface water, the installation of four monitoring wells, perform direct push groundwater sampling at seven locations, and collect one surface water sample. Sampling details, depths, and locations are presented in the Work Plan. The Work Plan was presented to the KSC Remediation Team in the form of an Advance Data Package in February 2023. Following STRIVES approval, the SLF FRB PFAS Site Assessment Work Plan will be formally submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗

NASA NTRS2023

Morpheus Test Area SWMU #119 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Work Plan

This Work Plan documents the proposed field sampling activities for a per- and polyfluoroalkyl substances (PFAS) Site Assessment at the Morpheus Test Area (MTA) at Kennedy Space Center (KSC). The Work Plan provides a background of the historical activities that occurred at the MTA, and the limited environmental investigations performed at the MTA. The proposed Site Assessment activities at MTA includes the collection of soil samples from seven locations, the installation of a staff gauge in site surface water, the installation of four monitoring wells, perform direct push groundwater sampling at ten locations, and collect one surface water sample. Sampling details, depths, and locations are presented in the Work Plan. The Work Plan was presented to the KSC Remediation Team in the form of an Advance Data Package in February 2023. Following STRIVES approval, the SLF FRB PFAS Site Assessment Work Plan will be formally submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗

NASA NTRS2023

Contractors Road Heavy Equipment Area (SWMU 055) 2022 Annual Groundwater Monitoring Report

This document presents a summary of activities completed at the Contractors Road Heavy Equipment (CRHE) Area, located at Kennedy Space Center (KSC), Florida, from June through December 2022. The activities conducted at the CRHE Area include: - Annual groundwater sampling activities associated with sitewide plume monitoring and Underground Injection Control (UIC) monitoring in the former bioremediation Interim Measures (IM) Hot Spot 1 (HS1) area; - Direct push technology (DPT) groundwater investigation; - Semiannual vapor intrusion (VI) evaluation activities. This facility is designated Solid Waste Management Unit (SWMU) Number 055 (SWMU 055) under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action program. HydroGeoLogic, Inc. (HGL) prepared this report for the National Aeronautics and Space NASA) under contract number 80KSC019F0096/80KSC019D0012, Technical Directive-03. An Advance Data Package (ADP) presentation of the elements of this report received Team (KSCRT) agreement at the April 5, 2023, KSCRT meeting. The chlorinated volatile organic compound plume appears to be stable vertically and horizontally. Additional DPT groundwater sampling will be completed to support a remedial alternatives evaluation for potential means to expedite groundwater cleanup. There are per- and polyfluorinated alkyl substances in site groundwater, and assessment is planned in the future. Sub-slab soil gas monitoring results do not indicate any concerns with indoor vapor intrusion. Based on the 2022 annual groundwater sampling results, it is recommended that annual sampling continue to alternate with the wet and dry season, with the next sampling event planned for December 2023.

groundwater↗

NASA NTRSDate not supplied

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

L. Prinzel↗

NASA NTRSDate not supplied

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

Aviation Safety↗

NASA NTRSDate not supplied

Unsteady PSP in the NASA Transonic Dynamics Tunnel

For the first time, unsteady pressure sensitive paint (uPSP) has been applied in the NASA Langley Transonic Dynamics Tunnel. Obtaining global surface pressure measurements using the uPSP technique required the development of a new paint formulation for use in the low oxygen heavy gas atmosphere, as well as environmental enclosures to protect sensitive electro-optical components from the high temperature, low pressure environment present during tunnel operation. A high-speed datalink connecting the wind tunnel to Langley’s local high performance compute resource was also established for this test to enable near real time processing of the large datasets that were obtained throughout the campaign. A high-speed lifetime measurement technique was also utilized to yield steady state surface pressures at each condition using the same equipment that was used to provide unsteady measurements. Important metrics such as pressure time histories and power spectral density are compared against traditional unsteady pressure point measurements, and more advanced data products such as dynamic mode decomposition are also explored to provide insight into the underlying flow phenomena.

Daniel T. Reese↗

NASA NTRS2024

Launch Complex 39A Operations Support Building Area SWMU 111 Year 3 Air Sparge System Performance Monitoring Report

This Air Sparge (AS) System Performance Monitoring Report (PMR) presents the findings, observations, and results for Year 3 of operation, maintenance, and monitoring activities for the AS Interim Measure (IM) at the Launch Complex 39A Operations Support Building Area (AOSB) at Kennedy Space Center (KSC), Florida. This report was presented as an Advance Data Package during the October 2024 KSC Remediation Team (KSCRT) meeting. The reporting period for activities covered under this PMR is from August 2023 through October 2024.

Mark P Speranza↗

NASA NTRSDate not supplied

The CLVTOPS Toolchain for NASA Space Launch System Liftoff Analysis and Post Flight Validation

This paper showcases the unique technical capabilities of the CLVTOPS multi-body flight dynamics toolchain developed by Marshall Space Flight Center (MSFC) for analyzing NASA’s Space Launch System (SLS) liftoff events. The CLVTOPS toolchain integrates high-fidelity simulations, geometric algorithms, advanced data analytics, and post-flight telemetry to demonstrate positive clearance between separating bodies and inform design decisions that enhance mission reliability. Proper liftoff separation is crucial to the success of the launch vehicle’s mission; vehicle impacts with the launch tower and supporting components incur a heightened risk of mission failure. For liftoff analysis, the CLVTOPS toolchain enables the integration of vehicle, launch pad, and environmental input models for the investigation of key clearance effectors. Furthermore, recent enhancements to the CLVTOPS toolchain allow for validation via photogrammetric trajectory reconstruction and plume pressure impingement estimation on the tower. The following sections will walk through the tool-chain, SLS liftoff ground rules and assumptions, key models, standard analysis, recent enhancements, and post-flight validation of the Artemis I mission liftoff event.

CLVTOPS↗

NASA NTRSDate not supplied

Space Launch System: CLVTOPS Toolchain for SLS Liftoff Separation Analysis

This presentation showcases the unique technical capabilities of the CLVTOPS multi-body flight dynamics tool chain developed by Marshall Space Flight Center (MSFC) for analyzing NASA’s Space Launch System (SLS) liftoff events. The CLVTOPS tool chain integrates high-fidelity simulations, geometric algorithms, advanced data analytics, and post-flight telemetry to demonstrate positive clearance between separating bodies and inform design decisions that enhance mission reliability. Proper liftoff separation is crucial to the success of the launch vehicle’s mission; vehicle impacts with the launch tower and supporting components incur a heightened risk of mission failure. For liftoff analysis, the CLVTOPS tool chain enables the integration of vehicle, launch pad, and environmental input models for the investigation of key clearance effectors. Furthermore, a novel capability of the CLVTOPS tool chain allows for verification and validation of trajectory reconstruction via photogrammetric imagery analysis. The following sections will walk through the tool chain, SLS liftoff ground rules and assumptions, model integration, pre-flight verification, and post-flight validation of the Artemis I mission liftoff event.

CLVTOPS↗

NASA NTRSDate not supplied

Enabling Reliable, Fault-Tolerant Autonomous Lunar Habitats with High-Performance Spaceflight Computing

The lunar surface presents unfavorable constraints and harsh living conditions. To address these challenges, autonomous habitats will require complex integrated systems that combine advanced software, high-performance hardware, and cutting-edge sensors to ensure sustainability, safety, and operational efficiency. Consequently, maintaining a sustainable presence on the Moon requires reliable infrastructure and efficient development, precise monitoring, and utilization of resources within a lunar installation. These elements are essential not only to ensure that lunar settlement can be long-term, self-sustaining, and resource-efficient, but also to serve as a foundation for future missions and eventual human habitation on Mars. Humans are not native to the Moon; therefore, our survival and ability to thrive will depend on autonomous systems that can foster safety and resilience through high-availability architectures, graceful degradation, and highly fault-tolerant spaceflight hardware capable of continuing operation during failures. This requires advanced human-rated distributed systems architectures with specialized electronics, scalable capabilities, and an integrated design approach. Unlike current practices focused on short-term missions and regularly maintained components, permanent lunar compute systems must be designed for extended operations beyond mission durations. This paper explores the necessity of transitioning toward fault- tolerant, highly autonomous hardware systems designed for multi-year missions. It also identifies critical subsystems that require high levels of autonomy, supported by radiation-hardened processors and extreme thermal loads, which are essential to mitigate long-term degradation and ensure sustainable lunar habitation. Finally, the paper aligns with NASA’s identified Civil Space Shortfalls, particularly in high-performance onboard computing, advanced data acquisition, extreme-environment avionics, radiation monitoring and countermeasures, and autonomous health management. It proposes NASA’s new High-Performance Spaceflight Computing (HPSC) processor as a turnkey solution, delivering 100 times the performance-per-watt of legacy rad-hard CPUs and enabling onboard AI, edge computing, and fault-tolerant features essential for sustained lunar autonomy and beyond.

Sarkis S Mikaelian↗