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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29

Root Cause Analysis of the Data Refinement Process – Medical Conditions Capability Resource Tables

The medical system for spaceflight thus far has been designed to support missions in low earth orbit (LEO). Crew capabilities are limited and heavily dependent on the team of medical support staff at Mission Control Center (MCC) to guide diagnosis and management. However, missions to the Moon and Mars will suffer from several constraints that will make this ground support focused approach to care ineffective. In order to update and modify medical system design, NASA has relied on Probabilistic Risk Assessment (PRA) modeling to mitigate medical risk through trade space analysis. Specifically, capability resource tables (CRT’s) were developed to create a dataset of resources required to manage a list of accepted medical conditions significant in exploration spaceflight. With 120 conditions, this dataset contained hundreds of capabilities and thousands of resources with tens of thousands of cells of data. Initially these tables were built in excel for high throughput during development, but ultimately had to be transferred, managed, and modified into the Evidence Library database for modeling purposes. The process of collating and reviewing the Evidence Library revealed numerous errors in the dataset that had to be corrected through iterative changes. Several error types emerged during this process and can be broken into specific classifications defined as “input”, “transcription”, “structural”, “branching”, and “information”. In reviewing these error types through the root cause analysis (RCA) approach, we were able to identify the contributors to these errors which included single data review points, changing product end goals, limited software selection, time constraints and several others. By reviewing and evaluating the underlying causes we can provide possible system improvements that can be implemented for current and future data management in PRA model inputs.

A. Anderson↗

Refinement of Transition-Edge Sensor Dimensions for the X-ray Integral Field Unit on ATHENA

At NASA Goddard Space Flight Center, we have previously demonstrated a kilo-pixel array of transition-edge sensor (TES) microcalorimeters capable of meeting the energy resolution requirements of the future X-ray Integral Field Unit (X-IFU) instrument that is being developed for the Advanced Telescope for High ENergy Astrophysics (ATHENA) observatory satellite. The TES design in this array was a square device with side length of 50 μm. Here, we describe studies of TES designs with small variations of the dimensions, exploring lengths, parallel to the current direction, ranging from 75μm to 50μm and widths, perpendicular to the current direction, ranging from 50μm to 15 μm. We describe how these changes impact transition properties, thermal conductance and magnetic field sensitivity. In particular, we show that using a TES with a length of 50μm and width of 30μm may be a promising route to reduce the maximum time-derivative of the TES current in an X-ray pulse and reduce the sensitivity of the TES to magnetic field.

N A Wakeham↗

Refinement of the Transition-edge Sensor Design for ATHENA X-IFU

The X-ray Integral Field Unit (X-IFU) instrument on the Advanced Telescope for High ENergy Astrophysics (ATHENA) is baselined to have 2376 transition-edge sensor (TES) microcalorimeter pixels in a single array. The required performance for X-IFU has been demonstrated on a kilo-pixel array of square TES’s with 50 m side length, and this is considered the baseline pixel design. However, over the last few years we have explored small modifications to this design in search of a globally optimized instrument performance. We have previously reported on investigations of extending the length of the TES’s and variations in the number of X-ray absorber support stems. Here we report on investigations of TES designs with a length of 50 m but narrower width. We will discuss the consequence of this on magnetic field sensitivity, resistive transition parameters, spectral performance, and ease of multiplexing. We will also discuss how the number and position of the absorber attachments influences the vibrational modes of the pixels, and the impact this may have on performance. Finally, we will present measurements of more substantial change options of our TES design, including more extreme TES geometries, the use of metal islands or etched holes in the silicon nitride membranes, and the position of wiring to minimize current-induced magnetic field effects. The exploration of all these changes to the design are not only useful for optimizing performance on X-IFU, but also guide our fundamental understanding of the key physics of TES microcalorimeters.

Nick Wakeham↗

Landing Site Selection with a Variable-Resolution SLAM-Refined Map

In many scenarios it is desirable for planetary landers to select or modify their landing sites autonomously during descent. We present a landing site selection algorithm which is optimized to work in conjunction with a Simultaneous Localization and Mapping system. Our algorithm selects landing sites based on site slope, roughness, and operator-defined interest. In addition, we generate guidance commands and approximate fuel consumption for the highest ranked sites. We validate our algorithm with LiDAR and inertial data gathered by a vertical take-off and landing vehicle.

Chen, Po-Ting↗

High Fidelity Adaptively Refined CFD and Reduced Order Models of a High Aspect Ratio Aeroelastic Wing Wind-Tunnel Model

The NASA Advanced Air Transport Technology (AATT) goal of reduced fuel burn for transport aircraft has led to the NASA N+3 High Aspect Ratio Wing (HARW) subproject. This project requires identifying, developing, and demonstrating key technologies and integrated multidisciplinary solutions to enable a safe, high performance, aeroelastic wing. Since this aircraft will have a high aspect ratio wing, aeroelasticity is expected to be a major issue in the design. In this paper high fidelity computational fluid dynamics (CFD) is performed with flow adapted meshes. A system identification of the aerodynamics is developed using both a multi-modal multi-sine time-marching and a multi-mode linear frequency domain method. GLA, MLA and flutter suppression simulations will be performed.

Robert Bartels↗

Standalone Hazard Evaluation and Refinement From Instrument Findings (S.H.E.R.I.F)

SHERIF is a novel algorithm which defines a unique, non-iterative method for the combination of LiDAR scans into a Digital Elevation Map (DEM) and the simultaneous evaluation of that DEM for Safe Site Selection (SSL) and Hazard Detection (HD). This creates a sensor independent method for a spacecraft conducting Entry Descent and Landing (EDL) operations to synthesize terrain scans and generate a more complete and evolving understanding of the landing site topography as well as the associated hazards. SHERIF aims to increase safety and mission success probability by more effectively using the data from a single sensor to increase situational awareness, knowledge of the landing site and its hazards, as well as informing a more streamlined transition from Terrain Relative Navigation (TRN) to Hazard Relative Navigation (HRN) during descent.

Hazard Detection↗

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗

Scoping, Tailoring, and Abstraction Refinement in Hazard Assessment Processes

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM)operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts under pinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

aviation safety↗

Scoping, Tailoring, and Abstraction Refinement in the Hazard Assessment Process

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM) operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts underpinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

Aviation Safety↗

Refined Predictions Compared with the Propulsion Airframe Aeroacoustics and Aircraft System Noise Flight Research Test Data

In a collaboration between NASA and The Boeing Company, the Propulsion Airframe Aeroacoustics and Aircraft System Noise Flight Research Test was executed by the Boeing ecoDemonstrator Program in 2020 with an Etihad Airways Boeing 787-10 aircraft. This ambitious flight research successfully accomplished many objectives and constitutes the most comprehensive and highest quality acoustic flight data available to NASA for a modern commercial subsonic transport aircraft. One purpose of these data is to be the measure of accuracy for the aircraft system noise prediction capabilities of NASA. This research reviews the impact of the major improvements in prediction methods implemented up to this point and tested in the Research version of the NASA Aircraft Noise Prediction Program. The improvements have been to the prediction of jet source and jet-flap interaction, to both fan broadband and tone source prediction, and to the prediction of propulsion airframe aeroacoustic scattering effects. In general, over the engine power range, comparisons between prediction and flight data are within 2 EPNdB including for the intentional sideline-to-sideline asymmetries as implemented in the flight test by flying the aircraft with only one engine at power. Considerable progress has been shown here in the continuing effort to advance the fidelity of NASA aircraft noise prediction capabilities for subsonic aircraft flight acoustics, modern transport aircraft and future aircraft concepts.

aircraft system noise prediction↗