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At least 325 records · Page 18

NDARC - NASA Design and Analysis of Rotorcraft Validation and Demonstration

Validation and demonstration results from the development of the conceptual design tool NDARC (NASA Design and Analysis of Rotorcraft) are presented. The principal tasks of NDARC are to design a rotorcraft to satisfy specified design conditions and missions, and then analyze the performance of the aircraft for a set of off-design missions and point operating conditions. The aircraft chosen as NDARC development test cases are the UH-60A single main-rotor and tail-rotor helicopter, the CH-47D tandem helicopter, the XH-59A coaxial lift-offset helicopter, and the XV-15 tiltrotor. These aircraft were selected because flight performance data, a weight statement, detailed geometry information, and a correlated comprehensive analysis model are available for each. Validation consists of developing the NDARC models for these aircraft by using geometry and weight information, airframe wind tunnel test data, engine decks, rotor performance tests, and comprehensive analysis results; and then comparing the NDARC results for aircraft and component performance with flight test data. Based on the calibrated models, the capability of the code to size rotorcraft is explored.

Johnson, Wayne↗

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

DeBaca, Richard C.↗

Thermal Analysis Data Exchange Between ESA and NASA with Step

Two years ago at ICES 97, a paper was presented describing the status of two companion open standards for electronic exchange and archival of space engineering data based on STEP (ISO-10303) technology. This paper presents background information on STEP and demonstrate the thermal model exchange between ESA and NASA.

thermal↗

Free-jet Testing of a REST Scramjet at Off-Design Conditions

Scramjet flowpaths employing elliptical combustors have the potential to improve structural efficiency and performance relative to those using planar geometries. NASA Langley has developed a scramjet flowpath integrated into a lifting body vehicle, while transitioning from a rectangular capture area to both an elliptical throat and combustor. This Rectangular-to-Elliptical Shape Transition (REST) scramjet, has a design point of Mach 7.1, and is intended to operate with fixed-geometry between Mach 4.5 and 8.0. This paper describes initial free-jet testing of the heat-sink REST scramjet engine model at conditions simulating Mach 5.3 flight. Combustion of gaseous hydrogen fuel at equivalence ratios between 0.5 and 1.5 generated robust performance after ignition with a silane-hydrogen pilot. Facility model interactions were experienced for fuel equivalence ratios above 1.1, yet despite this, the flowpath was not unstarted by fuel addition at the Mach 5.3 test condition. Combustion tests at reduced stagnation enthalpy indicated that the engine self-started following termination of the fuel injection. Engine data is presented for the largest fuel equivalence ratio tested without facility interaction. These results indicate that this class of three-dimensional scramjet engine operates successfully at off-design conditions.

Smart, Michael K.↗

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources

Michael von Pohle↗

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources.

deep learning↗

Multimission Telemetry Visualization (MTV) system: A mission applications project from JPL's Multimedia Communications Laboratory

This paper describes the Multimission Telemetry Visualization (MTV) data acquisition/distribution system. MTV was developed by JPL's Multimedia Communications Laboratory (MCL) and designed to process and display digital, real-time, science and engineering data from JPL's Mission Control Center. The MTV system can be accessed using UNIX workstations and PC's over common datacom and telecom networks from worldwide locations. It is designed to lower data distribution costs while increasing data analysis functionality by integrating low-cost, off-the-shelf desktop hardware and software. MTV is expected to significantly lower the cost of real-time data display, processing, distribution, and allow for greater spacecraft safety and mission data access.

Koeberlein, Ernest, III↗

Airborne Visible Laser Optical Communications (AVLOC) experiment

A series of optical communication experiments between a high altitude aircraft at 18.3 km (60,000 ft) and a ground station were conducted by NASA from summer 1972 through winter 1973. The basic system was an optical tracker and transmitter located in each terminal. The aircraft transceiver consisted of a 5-mW HeNe laser transmitter with a 30-megabit modulator. The ground station beacon was an argon laser operating at 488 nm. A separate pulsed laser radar was used for initial acquisition. The objective of the experiment was to obtain engineering data on the precision tracking and communication system performance at both terminals. Atmospheric effects on the system performance was also an experiment objective. The system description, engineering analysis, testing, and flight results are discussed.

Source record↗

Space Telescope Antenna Pointing System analysis and test

The Space Telescope (ST), carrying five astronomy instruments, is a long-life spacecraft designed to achieve and maintain ultrafine stabilization jitter performance. The rms jitter specification for pointing performance is 7 marcsec (1sigma) during periods of scientific observation. Spacecraft attitude control is achieved by onboard computer processing of attitude and rate sensor data to generate reaction-wheel torque commands. The ST Antenna Pointing System is used to position a high-gain antenna for relaying science and engineering data from the spacecraft to the ground station.

Dodder, R.↗

An observation on tone cut-off in static test data from jet engine fans

The far-field acoustic data for eight full-scale fans tested at a NASA-Lewis outdoor facility were analyzed for the effect of a cut-off design feature where the number of rotor and stator blades are proportioned so that the blade-passage tone will not propagate. Inlet flow distortions, prevalent during static testing, interact with the rotor to generate tones that generally mask this cut-off phenomenon. Distortion tone properties previously evaluated are used to analyze the tones propagating from the aft fan duct. The analyzed data clearly differentiated the fans that are and are not cut-off.

Heidmann, M. F.↗

Operating characteristics of the Langley Mach 7 Scramjet Test Facility

Operating characteristics of the Langley Mach 7 Scramjet Test Facility are described. The facility is designed for testing airframe integrated scramjet (supersonic combustion ramjet) engine models. Features include duplication of the flight Mach number total enthalpy, flight altitude simulation, and simulation of engine airframe integration effects such a bow shock wave precompression and boundary layer ingestion by the engine. Data obtained from facility calibration and from tests of a hydrogen burning, airframe integrated scramjet are discussed. An adverse interaction between the facility flow and the scramjet engine flow during combustion of the fuel is described.

Guy, R. W.↗

User's Manual for the Naval Interactive Data Analysis System-Climatologies (NIDAS-C), Version 2.0

This technical note provides the user's manual for the NIDAS-C system developed for the naval oceanographic office. NIDAS-C operates using numerous oceanographic data categories stored in an installed version of the Naval Environmental Operational Nowcast System (NEONS), a relational database management system (rdbms) which employs the ORACLE proprietary rdbms engine. Data management, configuration, and control functions for the supporting rdbms are performed externally. NIDAS-C stores and retrieves data to/from the rdbms but exercises no direct internal control over the rdbms or its configuration. Data is also ingested into the rdbms, for use by NIDAS-C, by external data acquisition processes. The data categories employed by NIDAS-C are as follows: Bathymetry - ocean depth at

USER M ANUALS↗

DELTA: An Open-Source Framework to Simplify Deep Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA for deep learning on satellite imagery based on tensorflow. It helps simplify data engineering and preprocessing steps and reduces the need for a lot of the boilerplate code that needs written to make datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the grunt work. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping.

Michael von Pohle↗

NASA's Responsible AI Plan

Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.

Artificial Intelligence↗

Improvements to a Response Surface Thermal Model for Orion

A study was performed to determine if a Design of Experiments (DOE)/Response Surface Methodology could be applied to on-orbit thermal analysis and produce a set of Response Surface Equations (RSE) that predict Orion vehicle temperatures within 10 F. The study used the Orion Outer Mold Line model. Five separate factors were identified for study: yaw, pitch, roll, beta angle, and the environmental parameters. Twenty-three external Orion components were selected and their minimum and maximum temperatures captured over a period of two orbits. Thus, there are 46 responses. A DOE case matrix of 145 runs was developed. The data from these cases were analyzed to produce a fifth order RSE for each of the temperature responses. For the 145 cases in the DOE matrix, the agreement between the engineering data and the RSE predictions was encouraging with 40 of the 46 RSEs predicting temperatures within the goal band. However, the verification cases showed most responses did not meet the 10 F goal. After reframing the focus of the study to better align the RSE development with the purposes of the model, a set of RSEs for both the minimum and maximum radiator temperatures was produced which predicted the engineering model output within +/-4 F. Therefore, with the correct application of the DOE/RSE methodology, RSEs can be developed that provide analysts a fast and easy way to screen large numbers of environments and assess proposed changes to the RSE factors.

Miller, Stephen W.↗

Evaluation of various thrust calculation techniques on an F404 engine

In support of performance testing of the X-29A aircraft at the NASA-Ames, various thrust calculation techniques were developed and evaluated for use on the F404-GE-400 engine. The engine was thrust calibrated at NASA-Lewis. Results from these tests were used to correct the manufacturer's in-flight thrust program to more accurately calculate thrust for the specific test engine. Data from these tests were also used to develop an independent, simplified thrust calculation technique for real-time thrust calculation. Comparisons were also made to thrust values predicted by the engine specification model. Results indicate uninstalled gross thrust accuracies on the order of 1 to 4 percent for the various in-flight thrust methods. The various thrust calculations are described and their usage, uncertainty, and measured accuracies are explained. In addition, the advantages of a real-time thrust algorithm for flight test use and the importance of an accurate thrust calculation to the aircraft performance analysis are described. Finally, actual data obtained from flight test are presented.

Ray, Ronald J.↗

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗