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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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NASA NTRS1987

A prototype 4800 bps voice terminal for the mobile satellite experiment

The authors report the final stage of a research project for the NASA mobile satellite experiment (MSAT-X). The work has resulted in two alternative coding techniques which have achieved good communications quality at 4.8 kb/s while tolerating vehicle noise, fading, and a fairly high-error-rate, bursty channel. The authors have constructed a circuit board based on three AT&T 32-bit floating-point DSP32 digital signal processors (DSP) and providing both excess processing power and considerable flexibility for handling different variations of the algorithms. A Motorola 68HC11 microcomputer chip serves as the board controller and interface handler. Mounted on a wirewrapped card, the prototype's circuit footprint amounts to only 225 cm2 and consumes about 13 W of power. A description is given of the architecture, signal processing and communication functions, circuitry, and firmware of the prototype. Issues such as synchronization, framing, error control, and modem interface are also addressed.

Chan, Wai-Yip↗

NASA NTRS1992

Modified optimal control pilot model for computer-aided design and analysis

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

Davidson, John B.↗

NASA NTRS1991

Relating the microwave radar cross section to the sea surface stress - Physics and algorithms

The FASINEX (Frontal Air-Sea Interaction Experiment) provided a unique data set with coincident airborne measurements of the ocean surface radar cross section (at Ku-band) and surface windstress. It is being analyzed to create new algorithms and to better understand the air-sea variables that can have a strong influence on the RCS (radar cross section). Several studies of portions of data from the FASINEX indicate that the RCS is more dependent on the surface stress than on the wind speed. Radar data have been acquired by the JPL and NRL groups. The data span 12 different flight days. Stress measurements can be inferred from ship-board instruments and from aircraft closely following the scatterometers.

Weissman, David E.↗

NASA NTRS2001

Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft

Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.

Davidson, John B.↗

NASA NTRS1990

Aircraft/island/ship/satellite intercomparison: Preliminary results from July 16, 1987

The First ISCCP Regional Experiment (FIRE) objective of validating and improving satellite algorithms for inferring cloud properties from satellite radiances was one of the central motivating factors in the design of the specific field experimental strategies used in the July, 1987 marine stratocumulus intensive field observations (IFO). The in situ measuring platforms were deployed to take maximum advantage of redundant measurements (for intercomparison of the in situ sensors) and to provide optimal coverage within satellite images. One of the most ambitious of these strategies was the attempt to coordinate measurements from San Nicolas Island (SNI), the R/V Pt. Sur, the meteorological aircraft, and the satellites. For the most part, this attempt was frustrated by flight restrictions in the vicinity of SNI. The exception was the mission of July 16, 1987, which achieved remarkable success in the coordination of the platforms. This presentation concerns operations conducted by the National Center for Atmospheric Research (NCAR) Electra and how data from the Electra can be integrated with and compared to data from the Pt. Sur, SNI, and the satellites. The focus is on the large-scale, integrated picture of the conditions on July 16 from the perspective of the Electra's flight operations.

Hanson, Howard P.↗

NASA NTRS2004

Advanced Health Management System for the Space Shuttle Main Engine

Boeing-Canoga Park (BCP) and NASA-Marshall Space Flight Center (NASA-MSFC) are developing an Advanced Health Management System (AHMS) for use on the Space Shuttle Main Engine (SSME) that will improve Shuttle safety by reducing the probability of catastrophic engine failures during the powered ascent phase of a Shuttle mission. This is a phased approach that consists of an upgrade to the current Space Shuttle Main Engine Controller (SSMEC) to add turbomachinery synchronous vibration protection and addition of a separate Health Management Computer (HMC) that will utilize advanced algorithms to detect and mitigate predefined engine anomalies. The purpose of the Shuttle AHMS is twofold; one is to increase the probability of successfully placing the Orbiter into the intended orbit, and the other is to increase the probability of being able to safely execute an abort of a Space Transportation System (STS) launch. Both objectives are achieved by increasing the useful work envelope of a Space Shuttle Main Engine after it has developed anomalous performance during launch and the ascent phase of the mission. This increase in work envelope will be the result of two new anomaly mitigation options, in addition to existing engine shutdown, that were previously unavailable. The added anomaly mitigation options include engine throttle-down and performance correction (adjustment of engine oxidizer to fuel ratio), as well as enhanced sensor disqualification capability. The HMC is intended to provide the computing power necessary to diagnose selected anomalous engine behaviors and for making recommendations to the engine controller for anomaly mitigation. Independent auditors have assessed the reduction in Shuttle ascent risk to be on the order of 40% with the combined system and a three times improvement in mission success.

Davidson, Matt↗

DOE OSTI2025

Automated Hybrid Variance Reduction on Advanced Architectures in the Shift Monte Carlo Code

Monte Carlo transport methods are the most accurate schemes for solving problems with complex energy and spatial features, but they come with a high computational cost. Although hybrid methods have enabled the use of Monte Carlo transport for a large class of problems, they still require significant computing resources. Modern multicore CPUs with large numbers of compute cores and graphical processing units (GPUs) provide opportunities to optimize the memory and run-time costs of hybrid Monte Carlo methods. This paper documents the development and analysis of three Monte Carlo transport algorithms that support hybrid transport using the consistent adjoint-driven importance sampling (CADIS) and forward-weighted CADIS methods in the Shift Monte Carlo code: history-based transport using static and dynamic threading on multicore CPUs and event-based transport enabling weight window tracking on GPUs. The results are shown for two challenging hybrid problems on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. The results show that all three methods yield good performance and enable solutions of difficult fixed-source transport problems in less than 2 min on 20 nodes of Frontier. Dynamic threading was observed to give up to 20% better scaling behavior than static threading. Moreover, the AMD Instinct 250X GPU was found to give 9 to 11 times greater throughput per graphics compute die than the best CPU performance. In conclusion, additional opportunities for optimization of hybrid transport on GPUs are discussed.

Denovo↗

NASA NTRS2018

NASA's Black Marble Nighttime Lights Product Suite

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 meters resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF (Bidirectional Reflectance Distribution Function) effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

Suomi-NPP↗

DOE OSTI2025

Surrogate optimization of variational quantum circuits

Variational quantum eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has not yet been realized, with few claims of quantum advantage and high resource estimates, especially due to the need for optimization in the presence of noise. Finding algorithms and methods to improve convergence is important to accelerate the capabilities of near-term hardware for VQE or more broad applications of hybrid methods in which optimization is required. To this goal, we look to use modern approaches developed in circuit simulations and stochastic classical optimization, which can be combined to form a surrogate optimization approach to quantum circuits. Using an approximate (classical CPU/GPU) state vector simulator as a surrogate model, we efficiently calculate an approximate Hessian, passed as an input for a quantum processing unit or exact circuit simulator. This method will lend itself well to parallelization across quantum processing units. We demonstrate the capabilities of such an approach with and without sampling noise and a proof-of-principle demonstration on a quantum processing unit utilizing 40 qubits.

Gustafson, Erik J. [RIACS, Mtn. View] (ORCID:00000↗

NASA NTRS2006

Exploration of OMI Products for Air Quality Applications Through Comparisons with Models and Observations

The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.

Pickering, K. E.↗

NASA NTRS2003

Flight Test of an Intelligent Flight-Control System

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

Davidson, Ron↗