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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 NTRS1999

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗

NASA NTRS1998

Trans-Pacific HDR Satellite Communications Experiment Phase-2: Experimental Network and Demonstration Plan

The trans-Pacific high data rate (TP-HDR) satellite communications experiment was proposed at the Japan-U.S. Cooperation in Space (JUCS) Program Workshop held in Hawaii in 1993 and remote high definition video post-production was demonstrated as the first phase trial. Following the first phase, the second phase experiment is currently prepared. This paper describes the experimental network configuration, application demonstration, and performance evaluation plan of the second phase experiment.

Kadowaki, Naoto↗

NASA NTRS1997

Scientific Visualization in High Speed Network Environments

In several cases, new visualization techniques have vastly increased the researcher's ability to analyze and comprehend data. Similarly, the role of networks in providing an efficient supercomputing environment have become more critical and continue to grow at a faster rate than the increase in the processing capabilities of supercomputers. A close relationship between scientific visualization and high-speed networks in providing an important link to support efficient supercomputing is identified. The two technologies are driven by the increasing complexities and volume of supercomputer data. The interaction of scientific visualization and high-speed networks in a Computational Fluid Dynamics simulation/visualization environment are given. Current capabilities supported by high speed networks, supercomputers, and high-performance graphics workstations at the Numerical Aerodynamic Simulation Facility (NAS) at NASA Ames Research Center are described. Applied research in providing a supercomputer visualization environment to support future computational requirements are summarized.

Vaziri, Arsi↗

NASA NTRS2004

Addressing Control Research Issues Leading to Piloted Simulations in Support of the IFCS F-15

This report summarizes the research effort by a team of researchers at West Virginia University in support of the NASA Intelligent Flight Control System (IFCS) F-15 program. In particular, WVU researchers assisted NASA Dryden researchers in the following technical tasks leading to piloted simulation of the 'Gen_2' IFCS control laws. Task #1- Performance comparison of different neural network (NN) augmentation for the Dynamic Inversion (DI) -based VCAS 'Gen_2' control laws. Task #2- Development of safety monitor criteria for transition to research control laws with and without failure during flight test. Task #3- Fine-tuning of the 'Gen_2' control laws for cross-coupling reduction at post-failure conditions. Matlab/Simulink-based simulation codes were provided to the technical monitor on a regular basis throughout the duration of the project. Additional deliverables for the project were Power Point-based slides prepared for different project meetings. This document provides a description of the methodology and discusses the general conclusions from the simulation results.

Napolitano, Marcello↗

NASA NTRS2001

Achieving QoS for TCP Traffic in Satellite Networks with Differentiated Services

Satellite networks play an indispensable role in providing global Internet access and electronic connectivity. To achieve such a global communications, provisioning of quality of service (QoS) within the advanced satellite systems is the main requirement. One of the key mechanisms of implementing the quality of service is traffic management. Traffic management becomes a crucial factor in the case of satellite network because of the limited availability of their resources. Currently, Internet Protocol (IP) only has minimal traffic management capabilities and provides best effort services. In this paper, we presented a broadband satellite network QoS model and simulated performance results. In particular, we discussed the TCP flow aggregates performance for their good behavior in the presence of competing UDP flow aggregates in the same assured forwarding. We identified several factors that affect the performance in the mixed environments and quantified their effects using a full factorial design of experiment methodology.

Durresi, Arjan↗

NASA NTRS2005

Flight Test Implementation of a Second Generation Intelligent Flight Control System

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team was to develop and flight-test control systems that use neural network technology, to optimize the performance of the aircraft under nominal conditions, and to stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. The Intelligent Flight Control System team is currently in the process of implementing a second generation control scheme, collectively known as Generation 2 or Gen 2, for flight testing on the NASA F-15 aircraft. This report describes the Gen 2 system as implemented by the team for flight test evaluation. Simulation results are shown which describe the experiment to be performed in flight and highlight the ways in which the Gen 2 system meets the defined objectives.

Williams-Hayes, Peggy S.↗

NASA NTRS2004

Spitzer Orbit Determination During In-orbit Checkout Phase

The Spitzer Space Telescope was injected into heliocentric orbit on August 25, 2003 to observe and study astrophysical phenomena in the infrared range of frequencies. The initial 60 days was dedicated to Spitzer's "In-Orbit Checkout (IOC)" efforts. During this time high levels of Helium venting were used to cool down the telescope. Attitude control was done using reaction wheels, which in turn were de-saturated using cold gas Nitrogen thrusting. Dense tracking data (nearly continuous) by the Deep Space network (DSN) were used to perform orbit determination and to assess any possible venting imbalance. Only Doppler data were available for navigation. This paper deals with navigation efforts during the IOC phase. It includes Dust Cover Ejection (DCE) monitoring, orbit determination strategy validation and results and assessment of non-gravitational accelerations acting on Spitzer including that due to possible imbalance in Helium venting.

helium venting↗

NASA NTRS2008

F-15 IFCS Intelligent Flight Control System

This viewgraph presentation gives a detailed description of the F-15 aircraft, flight tests, aircraft performance and overall advanced neural network based flight control technologies for aerospace systems designs.

Bosworth, John T.↗

NASA NTRS2009

Service Management Database for DSN Equipment

This data- and event-driven persistent storage system leverages the use of commercial software provided by Oracle for portability, ease of maintenance, scalability, and ease of integration with embedded, client-server, and multi-tiered applications. In this role, the Service Management Database (SMDB) is a key component of the overall end-to-end process involved in the scheduling, preparation, and configuration of the Deep Space Network (DSN) equipment needed to perform the various telecommunication services the DSN provides to its customers worldwide. SMDB makes efficient use of triggers, stored procedures, queuing functions, e-mail capabilities, data management, and Java integration features provided by the Oracle relational database management system. SMDB uses a third normal form schema design that allows for simple data maintenance procedures and thin layers of integration with client applications. The software provides an integrated event logging system with ability to publish events to a JMS messaging system for synchronous and asynchronous delivery to subscribed applications. It provides a structured classification of events and application-level messages stored in database tables that are accessible by monitoring applications for real-time monitoring or for troubleshooting and analysis over historical archives.

Zendejas, Silvino↗

NASA NTRS2012

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗

NASA NTRS2012

Evaluating the Efficacy of the Cloud for Cluster Computation

Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

Cloud Computing↗

NASA NTRS2018

Preliminary Results for Retrievals Using GFS Forecast as First Guess

Four days of retrievals in different years were performed using both a Neural Network first guess and also using the GFS forecast temperature profile, water vapor profile, and surface temperature as the first guess.Yield and temperature and water profile plots for days early and late in the AIRS mission follow.Yield is higher near the surface for forecast based retrievals.Statistical comparisons show that forecast based retrieval temperature RMS differences from ECMWF are smaller than those of the Neural Net based system. AIRS retrievals improve over the Neural Net but degrade the forecast.Statistical comparisons with ECMWF show that the bias structure of the forecast guess retrievals varies with time during the AIRS mission much more than those of the Neural Network based retrievals for both temperature and water vapor profiles.

Susskind, Joel↗

NASA NTRS2019

GPS Based Autonomous Navigation Study for the Lunar Gateway

This paper describes and predicts the performance of a conceptual autonomous GPS-based navigation system for NASA's planned lunar Gateway. This system is based on the flight-proven Magnetospheric Multiscale (MMS) GPS navigation system, augmented with an earth-pointed high-gain antenna and with an option for an atomic clock. High-fidelity simulations, calibrated against MMS flight data and making use of GPS transmitter patterns from the GPS Antenna Characterization Experiment (ACE) project are developed for operation of the system in the Gateway Near-Rectilinear Halo Orbit (NRHO). The results indicate that GPS can provide an autonomous, realtime navigation capability with comparable, or superior, performance to traditional Deep Space Network approach with eight hours of tracking per day.

Winternitz, Luke B.↗

NASA NTRSDate not supplied

Distributed Pressure Sensing for Enabling Self-Aware Autonomous Aerial Vehicles

Autonomous aerial transportation will be a fixture of future robotic societies, simultaneously requiring more stringent safety requirements and fewer resources for characterization than current commercial air transportation. More robust, adaptable, self-state estimation will be necessary to create such autonomous systems. We present a modular, scalable, distributed pressure sensing skin for aerodynamic state estimation of a large, flexible aerostructure. This skin used a network of 22 nodes that performed in-situ computation and communication of data collected from 74 pressure sensors, which were embedded into the skin panels of an ultra-lightweight 14-foot wingspan made from commutable, lattice-based subcomponents, and tested at NASA Langley Research Center's 14X22 wind tunnel. The density of the pressure sensors allowed for the use of a novel distributed algorithm to generate estimates of the wing lift contribution that were more accurate than the direct integration of the pressure distribution over the wing surface.

Daniel Cellucci↗

NASA NTRSDate not supplied

Comparison of Prediction Modeling Methodologies for Aeroacoustic Characterization of Hovering sUAS Rotors

This work compared artificial neural network and multivariate orthogonal function modeling methodologies for the prediction and characterization of isolated hovering sUAS rotor aerodynamics and aeroacoustics. Design of Experiments was used to create input feature spaces over 9 input features: the number of rotor blades, rotor size, rotor speed, the amount of blade twist, blade taper ratio, tip chord length, collective pitch, airfoil camber, and airfoil thickness. CAMRAD~II and AARON were executed at the points defined by the input feature space to predict aerodynamic and aeroacoustic quantities. These predicted aerodynamic and aeroacoustic data were then used to generate artificial neural networks and polynomial response surface models. The two prediction model methodologies were evaluated over test data previously unseen by the models, which showed good prediction capabilities for both model types, with slightly lower prediction error for the artificial neural networks. A characterization study was performed, which showed that input features correspondent to the spanwise sectional blade lift and drag were the most significant factors to the aerodynamic thrust and power, respectively. It was also shown that the aeroacoustic quantities were highly dependent on variations in rotor speed and size, which affect the Doppler factor for tonal noise and the spanwise Reynolds number for broadband noise.

Christopher S Thurman↗

NASA NTRSDate not supplied

U.S. IMERG Status

The U.S. Science Team’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) product provides estimates of surface precipitation rate and related information on a global 0.1° half-hour grid. It is run three times at increasingly longer latency and higher information input to serve different communities. This presentation will briefly summarize the major upgrades included in Version 07. The Goddard Profiling (GPROF) algorithm (applied to passive microwave sensor data from the GPM virtual constellation) and the Combined Radar-Radiometer Algorithm (CORRA) that provide input to IMERG V07 are both improved, and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm is being applied to infrared data, which employs an additional, warmer infrared temperature threshold than the previous infrared scheme and a deep neural network. V07 has improved bias performance as a result of calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager precipitation estimates. As well, time continuity in precipitation features is improved as a result of changes to the Kalman filter that approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and that better account for differences in sensor performance. A long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and a renewed effort to implement climatological gauge adjustment to the near-real-time Runs. Early evaluations of V07 IMERG show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory.

GPM↗

NASA NTRSDate not supplied

Production and Characterization of Additively Manufactured Radiator Panels with Integral Branching Heat Pipes for High-Temperature Heat Rejection

Emerging concepts for fission surface power and nuclear electric propulsion necessitate lightweight, mechanically robust, and thermally efficient heat rejection radiators. State-of-the-art intermediate-temperature (~400 K) composite radiator assemblies have been developed based on titanium-water heat pipes bonded to metal, graphite, and carbon-fiber-based panels. NASA has identified a need for new radiator concepts that can operate at even higher temperatures (500 – 600 K), minimize thermal resistances and thermal stress failures at bond interfaces, and approach areal densities of 2 – 3 kg m -2 . To meet these needs, our team is developing additively manufactured (AM) radiator panels with integral branching wicking heat pipe networks. Water is selected as the working fluid for this temperature range. Based on simulations and thermal vacuum experiments, these branching embedded heat pipe networks can efficiently distribute heat over panels for finned surface efficiencies of η f >70% at T H = 500 K input heat. This paper first presents laser powder-bed fusion AM strategies to produce embedded porous structures for wicking heat pipes in Inconel 718 and titanium alloys (commercially pure and Ti-6Al-4V alloys). Post-build chemical and thermal treatments are described that yield hydrophilic wicking surfaces for operation with water. Transient rate-of-rise experiments with water and acetone are reported that yield estimates for AM wick porosity (ϵ), permeability (K), and effective pore radius (r pore ). Based on the wick characterization results, small prototype radiator panels (75 × 125 mm) with integrated heat pipe networks were manufactured. Heat rejection performance data are presented from cold thermal vacuum testing, with heat input temperatures up to ~510 K. Future efforts will focus on improving heat pipe performance, optimizing radiator mass, and evaluating larger panels to assess scalability.

thermal management↗

NASA NTRS2024

Production and Characterization of Additively Manufactured Radiator Panels With Integral Branching Heat Pipes for High-Temperature Heat Rejection

Emerging concepts for fission surface power and nuclear electric propulsion necessitate lightweight, mechanically robust, and thermally efficient heat rejection radiators. State-of-the-art intermediate-temperature (~400 K) composite radiator assemblies have been developed based on titanium-water heat pipes bonded to metal, graphite, and carbon-fiber-based panels. NASA has identified a need for new radiator concepts that can operate at even higher temperatures (500 – 600 K), minimize thermal resistances and thermal stress failures at bond interfaces, and approach areal densities of 2 – 3 kg m -2 . To meet these needs, our team is developing additively manufactured (AM) radiator panels with integral branching wicking heat pipe networks. Water is selected as the working fluid for this temperature range. Based on simulations and thermal vacuum experiments, these branching embedded heat pipe networks can efficiently distribute heat over panels for finned surface efficiencies of η f >70% at T H = 500 K input heat. This paper first presents laser powder-bed fusion AM strategies to produce embedded porous structures for wicking heat pipes in Inconel 718 and titanium alloys (commercially pure and Ti-6Al-4V alloys). Post-build chemical and thermal treatments are described that yield hydrophilic wicking surfaces for operation with water. Transient rate-of-rise experiments with water and acetone are reported that yield estimates for AM wick porosity (ϵ), permeability (K), and effective pore radius ( r pore ). Based on the wick characterization results, small prototype radiator panels (75 × 125 mm) with integrated heat pipe networks were manufactured. Heat rejection performance data are presented from cold thermal vacuum testing, with heat input temperatures up to ~510 K. Future efforts will focus on improving heat pipe performance, optimizing radiator mass, and evaluating larger panels to assess scalability.

nuclear electric propulsion↗