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NASA NTRS2019

Carbon Nanotube Gas Sensor Using Neural Networks

The need to identify the presence and quantify the concentrations of gases and vapors is ubiquitous in NASA missions and societal applications. Sensors for air quality monitoring in crew cabins and ISS have been actively under development (Ref. 1). In particular, measuring the concentration of CO2 and NH3 is important because high concentrations of these gases pose a risk to ISS crew health. Detection of fuel and oxidant leaks in crew vehicles is critical for ensuring mission safety. Accurate gas and vapor concentrations can be measured, but this typically requires bulky and expensive instrumentation. Recently, inexpensive sensors with low power demands have been fabricated for use on the International Space Station (ISS). Carbon Nanotube (CNT) based chemical sensors are one type of these sensors. CNT sensors meet the requirements for low cost and ease of fabrication for deployment on the ISS. However, converting the measured signal from the sensors to human readable indicators of atmospheric air quality and safety is challenging. This is because it is difficult to develop an analytical model that maps the CNT sensor output signal to gas concentration. Training a neural network on CNT sensor data to predict gas concentration is more effective than developing an analytic approach to calculate the concentration from the same data set. With this in mind a neural network was created to tackle this challenge of converting the measured signal into CO2 and NH3 concentration values.

Norman, Thaddeus J.↗

NASA NTRS2018

Synthesizing a New Launch Vehicle Failure Probability Based on Historical Flight Data

New launch vehicles have historically had significantly higher failure rates in early flights than what has been predicted using Probabilistic Risk Assessment - PRA. This is because PRAs typically model a mature vehicle where a significant portion of the early failure probability contributors have been eliminated due to testing and improvements after actual field operation. To capture a more accurate early flight failure probability estimate, this paper develops a method that estimates ascent failure probability starting with the first flight based on historical launch vehicle records. With new launch vehicles being developed, such as the Space Launch System - SLS, a PRA model must be extended to cover early flight failure probability contributions that are either not covered in the mature-vehicle PRA or are underestimated. These failure probability contributions include design errors, quality control deficiencies, installation errors, and environmental impacts. There are also failure dependencies due to systemic errors that still exist due to limited entire-system testing.

Cross, Robert B.↗

DOE OSTI2022

Sensor-Equipped Unmanned Surface Vehicle for High-Resolution Mapping of Water Quality in Low- to Mid-Order Streams

Longitudinal profiling of water quality via the deployment of sensors from watercraft has advanced the understanding of spatial patterns in large rivers and lakes; however, a similar approach in low- to mid-order streams is lacking. To fill this gap, we developed an unmanned surface vehicle (USV)-water quality measurement platform (the “AquaBOT”). The components of the AquaBOT included a nitrate sensor, multiparameter sonde (temperature, conductivity, turbidity, dissolved oxygen, chlorophyll), quantum sensor, and global positioning system (GPS) mounted to a small pontoon-style USV. The AquaBOT was tested in four streams and rivers in Iowa and Tennessee. All measured water quality parameters varied longitudinally, and greater ranges were generally observed along the low-order, agriculturally influenced streams in Iowa. Nitrate, in particular, was spatially heterogeneous. For example, during one run in early June, concentrations ranged from 10.5 to 12.5 mg N L –1 along a 2.3 km reach and hotspots were observed directly downstream of some tile drains. The spatial resolution of AquaBOT data collected in June was 10× higher than grab sampling data, and measurements were collected in less time and at a comparable cost. Here, the AquaBOT can complement existing measurement approaches and will lead to advancements in understanding the processes driving water quality along the stream-to-river continuum.

47 OTHER INSTRUMENTATION↗

NASA NTRS2010

The Importance of HRA in Human Space Flight: Understanding the Risks

Human performance is critical to crew safety during space missions. Humans interact with hardware and software during ground processing, normal flight, and in response to events. Human interactions with hardware and software can cause Loss of Crew and/or Vehicle (LOCV) through improper actions, or may prevent LOCV through recovery and control actions. Humans have the ability to deal with complex situations and system interactions beyond the capability of machines. Human Reliability Analysis (HRA) is a method used to qualitatively and quantitatively assess the occurrence of human failures that affect availability and reliability of complex systems. Modeling human actions with their corresponding failure probabilities in a Probabilistic Risk Assessment (PRA) provides a more complete picture of system risks and risk contributions. A high-quality HRA can provide valuable information on potential areas for improvement, including training, procedures, human interfaces design, and the need for automation. Modeling human error has always been a challenge in part because performance data is not always readily available. For spaceflight, the challenge is amplified not only because of the small number of participants and limited amount of performance data available, but also due to the lack of definition of the unique factors influencing human performance in space. These factors, called performance shaping factors in HRA terminology, are used in HRA techniques to modify basic human error probabilities in order to capture the context of an analyzed task. Many of the human error modeling techniques were developed within the context of nuclear power plants and therefore the methodologies do not address spaceflight factors such as the effects of microgravity and longer duration missions. This presentation will describe the types of human error risks which have shown up as risk drivers in the Shuttle PRA which may be applicable to commercial space flight. As with other large PRAs of complex machines, human error in the Shuttle PRA proved to be an important contributor (~12 percent) to LOCV. An existing HRA technique was adapted for use in the Shuttle PRA, but additional guidance and improvements are needed to make the HRA task in space-related PRAs easier and more accurate. Therefore, this presentation will also outline plans for expanding current HRA methodology to more explicitly cover spaceflight performance shaping factors.

Hamlin, Teri↗

NASA NTRS1993

A model for rotorcraft flying qualities studies

This paper outlines the development of a mathematical model that is expected to be useful for rotorcraft flying qualities research. A computer model is presented that can be applied to a range of different rotorcraft configurations. The algorithm computes vehicle trim and a linear state-space model of the aircraft. The trim algorithm uses non linear optimization theory to solve the nonlinear algebraic trim equations. The linear aircraft equations consist of an airframe model and a flight control system dynamic model. The airframe model includes coupled rotor and fuselage rigid body dynamics and aerodynamics. The aerodynamic model for the rotors utilizes blade element theory and a three state dynamic inflow model. Aerodynamics of the fuselage and fuselage empennages are included. The linear state-space description for the flight control system is developed using standard block diagram data.

Mittal, Manoj↗

DOE OSTI2026

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1990

Experimental performance and acoustic investigation of modern, counterrotating blade concepts

The aerodynamic, acoustic, and aeromechanical performance of counterrotating blade concepts were evaluated both theoretically and experimentally. Analytical methods development and design are addressed. Utilizing the analytical methods which evolved during the conduct of this work, aerodynamic and aeroacoustic predictions were developed, which were compared to NASA and GE wind tunnel test results. The detailed mechanical design and fabrication of five different composite shell/titanium spar counterrotating blade set configurations are presented. Design philosophy, analyses methods, and material geometry are addressed, as well as the influence of aerodynamics, aeromechanics, and aeroacoustics on the design procedures. Blade fabrication and quality control procedures are detailed; bench testing procedures and results of blade integrity verification are presented; and instrumentation associated with the bench testing also is identified. Additional hardware to support specialized testing is described, as are operating blade instrumentation and the associated stress limits. The five counterrotating blade concepts were scaled to a tip diameter of 2 feet, so they could be incorporated into MPS (model propulsion simulators). Aerodynamic and aeroacoustic performance testing was conducted in the NASA Lewis 8 x 6 supersonic and 9 x 15 V/STOL (vertical or short takeoff and landing) wind tunnels and in the GE freejet anechoic test chamber (Cell 41) to generate an experimental data base for these counterrotating blade designs. Test facility and MPS vehicle matrices are provided, and test procedures are presented. Effects on performance of rotor-to-rotor spacing, angle-of-attack, pylon proximity, blade number, reduced-diameter aft blades, and mismatched rotor speeds are addressed. Counterrotating blade and specialized aeromechanical hub stability test results are also furnished.

Hoff, G. E.↗

NASA NTRSDate not supplied

Copula-based Method to Generate Consistent Surface Pressures Under Uncertainty

This paper establishes a method to create surface pressure databases that allow for uncertainty quantification. Aerodynamic databases are critical products for launch vehicles and other aeronautical systems, and surface pressure databases are one such database that constains large quantities of data. The focus of this work is the relationship between the integrated force and moment data base and the surface pressure database. In particular, the work attempts to provide a method that maintains consistency between these two databases when accounting for uncertainty. The integrated force and moment database and surface pressure databases are constructed from CFD data which is high-density but low-trust. However, the force and moment database will often also include data from high-trust but low-density sources such as from wind tunnel experiments. This means that the quantified uncertainty of the force and moment database is higher quality as it includes this high fidelity wind tunnel data. This motivates the idea to use the force and moment database uncertainty when constructing the surface pressure database uncertainty. The method utilizes the statistical idea of a copula in order to generate surface pressures that match with uncertain integrated force and moment distributions as well as being consistent with known CFD data. This statistical consistency is quantified by using the Maximum Mean Discrepancy two-sample test. The predictive error of the method is also approximated using leave-one-out error estimation and the good overall performance of the method is presented using probability boxes in a simulated uncertainty scenario.

SLS↗

NASA NTRS2010

Ares I-X Range Safety Simulation Verification and Analysis IV and V

NASA s ARES I-X vehicle launched on a suborbital test flight from the Eastern Range in Florida on October 28, 2009. NASA generated a Range Safety (RS) flight data package to meet the RS trajectory data requirements defined in the Air Force Space Command Manual 91-710. Some products included in the flight data package were a nominal ascent trajectory, ascent flight envelope trajectories, and malfunction turn trajectories. These data are used by the Air Force s 45th Space Wing (45SW) to ensure Eastern Range public safety and to make flight termination decisions on launch day. Due to the criticality of the RS data in regards to public safety and mission success, an independent validation and verification (IV&V) effort was undertaken to accompany the data generation analyses to ensure utmost data quality and correct adherence to requirements. Multiple NASA centers and contractor organizations were assigned specific products to IV&V. The data generation and IV&V work was coordinated through the Launch Constellation Range Safety Panel s Trajectory Working Group, which included members from the prime and IV&V organizations as well as the 45SW. As a result of the IV&V efforts, the RS product package was delivered with confidence that two independent organizations using separate simulation software generated data to meet the range requirements and yielded similar results. This document captures ARES I-X RS product IV&V analysis, including the methodology used to verify inputs, simulation, and output data for an RS product. Additionally a discussion of lessons learned is presented to capture advantages and disadvantages to the IV&V processes used.

Tarpley, Ashley↗

NASA NTRS2006

Simulink-Based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV)

The Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) is a Simulink-based approach to providing an engineering quality desktop simulation capability for finding trim solutions, extracting linear models for vehicle analysis and control law development, and generating open-loop and closed-loop time history responses for control system evaluation. It represents a useful level of maturity rather than a finished product. The layout is hierarchical and supports concurrent component development and validation, with support from the Concurrent Versions System (CVS) software management tool. Real Time Workshop (RTW) is used to generate pre-compiled code for substantial component modules, and templates permit switching seamlessly between original Simulink and code compiled for various platforms. Two previous limitations are addressed. Turn around time for incorporating tabular model components was improved through auto-generation of required Simulink diagrams based on data received in XML format. The layout was modified to exploit a Simulink "compile once, evaluate multiple times" capability for zero elapsed time for use in trimming and linearizing. Trim is achieved through a Graphical User Interface (GUI) with a narrow, script definable interface to the vehicle model which facilitates incorporating new models.

Christhilf, David m.↗

NASA NTRS2006

Mode I Toughness Measurements of Core/Facesheet Bonds in Honeycomb Sandwich Structures

Composite sandwich structures will be used in many future applications in aerospace, marine and offshore industries due to the fact that the strength and stiffness to mass ratios surpass any other structural type. Sandwich structure also offers advantages over traditional stiffened panels such as ease of manufacturing and repair. During the last three decades, sandwich structure has been used extensively for secondary structure in aircraft (fuselage floors, rudders and radome structure). Sandwich structure is also used as primary structure in rotorcraft, the most common example being the trailing edge of rotor blades. As with other types of composite construction, sandwich structure exhibits several types of failure mode such as facesheet wrinkling, core crushing and sandwich buckling. Facesheet/core debonding has also been observed in the marine and aerospace industry. During this failure mode, peel stresses applied to an existing facesheet/core debond or an interface low in toughness, results in the facesheet being peeled from the core material, possibly leading to a significant loss in structural integrity of the sandwich panel. In an incident during a test on a liquid hydrogen fuel tank of the X-33 prototype vehicle, the outer graphite/epoxy facesheet and honeycomb core became debonded from the inner facesheet along significant areas, leading to failure of the tank. As a consequence of the accident; significant efforts were made to characterize the toughness of the facesheet/core bond. Currently, the only standardized method available for assessing the quality of the facesheet/core interface is the climbing drum peel test (ASTM D1781). During this test a sandwich beam is removed from a panel and the lip of one of the facesheets is attached to a drum, as shown in Fig. 1. The drum is then rotated along the sandwich beam, causing the facesheet to peel from the core. This method has two major drawbacks. First, it is not possible to obtain quantitative fracture data from the test and so the results can only be used in a qualitative manner. Second, only sandwich structure with thin facesheets can be tested (to facilitate wrapping of the facesheet around the climbing drum). In recognition of the need for a more quantitative facesheet/core fracture test, several workers have devised experimental techniques for characterizing the toughness of the facesheet/core interface. In all of these cases, the tests are designed to yield a mode I-dominated fracture toughness of the facesheet/core interface in a manner similar to that used to determine mode I fracture toughness of composite laminates. In the current work, a modified double cantilever beam is used to measure the mode I-dominated fracture toughness of the interface in a sandwich consisting of glass/phenolic honeycomb core reinforced with graphite epoxy facesheets. Two specimen configurations were tested as shown in Fig 2. The first configuration consisted of reinforcing the facesheets with aluminum blocks (Fig. 2a). In the second configuration unreinforced specimens were tested (Fig. 2b). Climbing drum peel tests were also conducted to compare the fracture behavior observed between this test and the modified double cantilever beam. This paper outlines the test procedures and data reduction strategies used to compute fracture toughness values from the tests. The effect of specimen reinforcement on fracture toughness of the facesheet/core interface is discussed.

Nettles, Alan T.↗

DOE OSTI2025

Hydrogen and Electric Charging Infrastructure for Heavy-Duty Trucks: A Nationally Scalable Megaregion Assessment

Decarbonizing regional and long-haul freight is challenging due to the limitations of battery-electric commercial vehicles and infrastructure constraints. Hydrogen fuel cell medium- and heavy-duty vehicles (MHDVs) offer a viable alternative, aligning with the decarbonization goals of the Department of Energy and commercial entities. Historically, alternative fuels like compressed natural gas and liquefied propane gas have faced slow adoption due to barriers like infrastructure availability. To avoid similar issues, effective planning and deploying zero-emission hydrogen fueling infrastructure is crucial. This research develops deployment plans for affordable, accessible, and sustainable hydrogen refueling stations, supporting stakeholders in the decarbonized commercial vehicle freight system. It aims to benefit underserved and rural energy-stressed communities by improving air quality, reducing noise pollution, and enhancing energy resiliency. This research also provides a blueprint for replacing diesel in over-the-road Class 8 freight truck applications with hydrogen fueling solutions. The study focuses on the Texas Triangle Megaregion (I-45, I-35, and I-10), the I-10 corridor between San Antonio, TX, and Los Angeles, CA, and the I-5/CA-99 corridors between Los Angeles, CA, and San Francisco, CA. This area represents a significant portion of U.S. heavy-duty freight movement, carrying ~8.5% of the national freight volume. Using the OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport) modeling framework, the study conducts an advanced assessment of commercial vehicles, road and freight networks, and energy systems. The framework integrates data on freight mobility, traffic, weather, and energy pathways to deliver a region-specific, optimized vehicles powertrain architectures, infrastructure deployment solutions, operational logistics, and energy pathways. By considering all vehicle origin-destination pairs utilizing these corridors and all feasible fueling station location options, the framework's genetic algorithm identifies the minimum number and optimal locations of hydrogen refueling stations, ensuring no vehicle is stranded. It also determines fuel schedules and quantities at each station. A roadmap for station deployment based on multiple adoption trajectories ensures a strategic rollout of hydrogen refueling infrastructure.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗

NASA NTRSDate not supplied

Machine Learning Explainability and Transferability for Path Navigation

Deep neural networks are powerful tools for machine perception. Unfortunately their decisions are difficult to explain due to the complexity and size of the networks. Previously we have alleviated this issue by using the representational portion of a deep neural network and combining it with a k-nearest neighbor (KNN) classifier. Through inspection of the decisions made by the KNN, we can directly see the training data responsible for the decisions, allowing us to determine the quality of the overall decision and the quality of the representational layer of the deep NN. While the technique worked well, it requires tens of thousands of latent vectors to be stored for classification. In addition, it lacks the ability to show how parts of an image influence the classification decision. Here we address these issues by 1) Using a radial basis function network (RBFN) in place of the KNN allowing far fewer images to be used in deployment and 2) Using an auto encoder network for explainability. In addition to these techniques, we examine the effects of transfer learning to determine that results are robust. All results are tested on a domain where an unmanned aerial vehicle (UAV) navigates a forest trail through a single camera.

explainable machine learning↗

NASA NTRS1965

Review of the XB-70 Flight Program

Although the major NASA research effort is directed toward XB-70-2, which will not enter its flight program until the summer of 1965, a limited amount of information is available from the early flights of the XB-70-1 airplane. Initial take-off and landing performance data have generally substantiated predictions and indicate no unforeseen problems for this class of vehicle. Vertical velocities at impact are of the same order of magnitude as those being experienced by present-day subsonic jets. The XB-70 distances from brake release to lift-off graphically illustrate the advantage of the increased thrust-weight ratio of the supersonic cruise vehicle. The landing loads are well within the design limits up to the highest vertical velocities encountered to date, and recorded data show the response at the pilot station to be somewhat greater than that recorded at the center of gravity. Persistent shaking has been encountered in flight at subsonic speed. The cause of the excitation is not known at present but the oscillation does not appear to be conventional buffeting. The oscillation occurrence drops off appreciably at supersonic speeds and can be correlated with atmospheric turbulence. The stability and control characteristics at subsonic speeds appear satisfactory with stability augmentation on and off. A longitudinal trim discrepancy from predictions has been noted in the transonic region which appears to be decreasing with increasing supersonic speed. The supersonic handling qualities are considered adequate with stability augmentation off; however, sensitive lateral control has resulted in small pilot-induced oscillations.

Thomas R. Sisk↗

NASA NTRS1982

Flight testing the Rotor Systems Research Aircraft (RSRA)

The Rotor Systems Research Aircraft (RSRA) is a dedicated rotor test vehicle whose function is to fill the gap between theory, wind tunnel tests and flight verification data. Its flight test envelope has been designed to encompass the expected envelopes of future rotor systems under all flight conditions. The test configurations of the RSRA include pure helicopter and compound (winged helicopter) modes. In addition, should it become necessary to jettison an unstable rotor system in flight, the RSRA may be flown as a fixed wing aircraft. The heart of the RSRA's electronic flight control system is the TDY-43 computer, which can be programmed in numerous ways to change stability and control or force feel system gains. Computer programming changes allow the RSRA to be used as a five-degree-of-freedom inflight simulator for studying the handling qualities of research rotors.

Merrill, R. K.↗

NASA NTRS1993

Radiation considerations for interplanetary missions

Galactic cosmic radiation (GCR) poses a serious radiation hazard for long-duration missions. In designing a lunar habitat or Mars transfer vehicle, the worst-case radiation exposure determines shielding thickness and, hence, the weight of spacecraft. Using the spherically symmetric diffusion theory of the solar modulation of GCR, it was possible to use data on the differential energy spectra of hydrogen, helium, oxygen, and iron from 1954 to 1989 to show that the flux at 1 A.U. is determined by the diffusion parameter, K, which is a function of the time in the solar cycle. This analysis also showed that the solar minimum of 1976 to 1977 was the deepest minimum in the last 37 years. Using this theory, we have obtained the GCR spectra for all the nuclei and calculated the depth-dose as a function of aluminum shield thickness. Using the ICRP-26 definition of the quality factor, it is shown that the shielding required to stay below the LEO recommended annual limit of 50 cSv is 17.5 (+8, -3), g/sq cm of aluminum; if the limit is raised to 60 cSv, the required shielding is 9 (5, -1.5) g/sq cm. We also discuss the issues and shielding needs for protection against solar particle events.

Badwar, Gautam D.↗

NASA NTRSDate not supplied

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

NASA NTRSDate not supplied

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

GNSS↗