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NASA NTRS1992

Advanced Transport Operating System (ATOPS) color displays software description microprocessor system

This document describes the software created for the Sperry Microprocessor Color Display System used for the Advanced Transport Operating Systems (ATOPS) project on the Transport Systems Research Vehicle (TSRV). The software delivery known as the 'baseline display system', is the one described in this document. Throughout this publication, module descriptions are presented in a standardized format which contains module purpose, calling sequence, detailed description, and global references. The global reference section includes procedures and common variables referenced by a particular module. The system described supports the Research Flight Deck (RFD) of the TSRV. The RFD contains eight cathode ray tubes (CRTs) which depict a Primary Flight Display, Navigation Display, System Warning Display, Takeoff Performance Monitoring System Display, and Engine Display.

Slominski, Christopher J.↗

NASA NTRS2001

The Use of Eccentric and Circular Orbits in the Design of a Mars Network Constellation

This study examined different constellation configurations to determine their suitability for the Mars Network. Some variations on the baseline case of four circular orbits were initially studied. Eccentric orbits were then used to determine their effects on several figures of merit that were selected as representative of the design goals. It was eventually found that the use of eccentric orbits in combination with circular orbits can improve aspects of some navigation and communication figures of merit. The ability to use orbits at different inclinations helps smooth coverage over the middle and upper latitudes for these figures of merit. This configuration has more variability than one consisting of circular orbits, so the occurrence of unfavorable arrangements also results in degradation of some figures of merit. Some cases were used which improved different figures of merit, so a solution could be chosen depending on specified requirements.

Anderson, Rodney↗

NASA NTRS2004

Titan Ballute Aerocapture Using a Perturbed TitanGRAM Model

Aerocapture using a towed, inflatable ballute system has been shown to provide significant performance advantages compared to traditional technologies, including lower heating rates and accommodation of larger navigational uncertainties. This paper extends previous results by designing a ballute aerocapture separation algorithm that can operate in a more realistic Titan atmospheric model based on TitanGRAM. This model incorporates both latitudinal variability as well as noisiness in the density profile.

Ballute↗

DOE OSTI2019

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1990

The Meteorological Measurement System on the NASA ER-2 aircraft

A Meteorological Measurement System (MMS) was designed and installed on one of the NASA high-altitude ER-2 aircraft (NASA 706). The MMS provides in situ measurements of free-stream pressure (+ or - 0.3 mb), temperature (+ or - 0.3 C), and wind vector (+ or - 1 m/s). It incorporates a high-resolution inertial navigation system specially configured for scientific applications, a radome differential pressure system for measurements of the airflow angles, and a compact, computer-controlled data acquisition system to sample, process and store 45 variables on tape and on disk. The MMS hardware and software development is described, and resolution and accuracy of the instrumentation discussed. Custom software facilitates preflight system checkout, inflight data acquisition, and fast postflight data download. It accommodates various modes of MMS data: analog and digital, serial and parallel, and synchronous and asynchronous. Flight results are presented to demonstrate the capability of the system.

Scott, Stan G.↗

NASA NTRS1992

Advanced Transport Operating System (ATOPS) control display unit software description

The software created for the Control Display Units (CDUs), used for the Advanced Transport Operating Systems (ATOPS) project, on the Transport Systems Research Vehicle (TSRV) is described. Module descriptions are presented in a standardized format which contains module purpose, calling sequence, a detailed description, and global references. The global reference section includes subroutines, functions, and common variables referenced by a particular module. The CDUs, one for the pilot and one for the copilot, are used for flight management purposes. Operations performed with the CDU affects the aircraft's guidance, navigation, and display software.

Slominski, Christopher J.↗

NASA NTRS2019

Definition of a Technology Validation Mission for P-band Reflectometry using Signals of Opportunity

Root-Zone Soil Moisture (RZSM) (moisture profile in the top meter of soil) and Snow Water Equivalent (SWE) (total snow pack water content) are identified as priority target variables in the ESAS 2017 decadal survey [1] with critical roles in hydrology and water management. RZSM estimates are vital for understanding multiple Earth system processes and forecasting (for example, droughts [2]). Simultaneous knowledge of surface and RZSM could enable a breakthrough in estimating key unobserved hydrologic fluxes and reduce uncertainty in net ecosystem exchange (NEE), carbon balance [3] discharge estimates, and crop yield forecasts [4] .With the high albedo and insulating properties of snow, monitoring, SWE accumulation would provide a key constraint on the potential runoff during spring ablation while monitoring SWE disappearance rates would provide a key constraint on SWE partition into runoff vs. infiltration/recharge. [5] demonstrated that knowledge of early-spring SWE generally contributes most to streamflow forecast skill in the Western U.S. SWE is also a source of water storage that provides the water resources during spring snowmelt. Despite such potentially transformative contributions, accurate RZSM and SWE measurements are unattainable with current technology. While active/passive L-band methods (e.g. SMAP, SMOS) can reliably retrieve surface soil moisture in the top 5 cm of soil [6], [7]. RZSM estimates are only available through model assimilation of brightness temperatures with a radiative transfer and land surface models [8]. SWE estimation uses multi-frequency passive microwave techniques (e.g. [9]-[11]), which have significant problems with deeper snow and in forested and mountainous environments [12]. Signals of opportunity (SoOp) in P-band (200-400 MHz) is a new remote sensing technique with the capability of estimating both essential hydrologic variables, RZSM and SWE, circumventing many of the aforementioned limitations under all weather conditions day and night. SoOp is the re-utilization of existing powerful satellite transmissions within bands allocated for communications or navigation. P-band SoOp sensitivity to soil moisture has been demonstrated in an airborne experiment over Oklahoma in 2016 [13]. Recent theory [14] and experiments [15] have also confirmed that the reflection coefficient phase is proportional to SWE.

Garrison, J. L.↗

NASA NTRS2021

Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions

We propose a framework for resilient autonomous navigation in perceptuallychallenging unknown environments with mobility-stressing elements such asuneven surfaces with rocks and boulders, steep slopes, negative obstacles like cliffsand holes, and narrow passages. Environments are GPS-denied and perceptuallydegradedwith variable lighting from dark to lit and obscurants (dust, fog, smoke).Lack of prior maps and degraded communication eliminates the possibility of prioror off-board computation or operator intervention. This necessitates real-time onboardcomputation using noisy sensor data. To address these challenges, we proposea resilient architecture that exploits redundancy and heterogeneity in sensing modalities.Further resilience is achieved by triggering recovery behaviors upon failure.We propose a fast settling algorithm to generate robust multi-fidelity traversabilityestimates in real-time. The proposed approach was deployed on multiple physicalsystems including skid-steer and tracked robots, high-speed RC car and legged robotsand as a part of Team CoSTAR’s effort to theDARPASubterranean Challenge, wherethe team won 2nd and 1st place in the Tunnel and Urban Circuit, respectively.

Agha-mohammadi, Ali-akbar↗

DOE OSTI2024

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗

NASA NTRS1980

An application of extremal field guidance in statistical low thrust guidance analysis

The subject of this paper is the application of extremal field guidance to the covariance analysis of low thrust retargeting guidance. The general procedure for low thrust navigation analysis is briefly reviewed. The basic equations of trajectory optimization and extremal field guidance are presented with emphasis on the low thrust problem. The adopted formulation includes thruster on-off times as control variables and accounts for the effects of model parameter variations. A method of solution of the guidance equations is outlined; and the application of the solution in a covariance analysis, including a procedure for the treatment of model parameter variations as either biases or first order Gauss-Markov stochastic processes, is discussed.

Jacobson, R. A.↗

NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

NASA NTRS1983

Flight path design issues for the TOPEX mission

The proposed Ocean Topography Experiment (TOPEX) is an earth satellite mission currently under consideration by NASA. The primary purpose of the experiment is to determine the general circulation of the oceans and its variability. High precision, space based altimeter measurements will be combined with surface measurements and ocean models to accomplish the mission objectives. The paper will discuss mission requirements on orbit design, orbit selection space, derived requirements on navigation and satellite design issues which impact orbit selection. Unique aspects of the TOPEX orbit design are highlighted, such as high precision repeating orbits, 'frozen orbit' values of eccentricity and periapses, precise maneuver and orbit determination requirements and insuring crossing arcs over a calibration-site.

Frautnick, J. C.↗

NASA NTRS1992

Flight-determined benefits of integrated flight-propulsion control systems

Over the last two decades, NASA has conducted several experiments in integrated flight-propulsion control. Benefits have included improved maneuverability; increased thrust, range, and survivability; reduced fuel consumption; and reduced maintenance. This paper presents the basic concepts for control integration, examples of implementation, and benefits. The F-111E experiment integrated the engine and inlet control systems. The YF-12C incorporated an integral control system involving the inlet, autopilot, autothrottle, airdata, navigation, and stability augmentation systems. The F-15 research involved integration of the engine, flight, and inlet control systems. Further extension of the integration included real-time, onboard optimization of engine, inlet, and flight control variables; a self-repairing flight control system; and an engines-only control concept for emergency control. The F-18A aircraft incorporated thrust vectoring integrated with the flight control system to provide enhanced maneuvering at high angles of attack. The flight research programs and the resulting benefits of each program are described.

James F Stewart↗

NASA NTRS2017

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗

NASA NTRS1993

Calibration, navigation, and registration of MAMS data for FIFE

The International Satellite Land Surface Climatology Project (ISLSCP) was conducted to study the interaction of the atmosphere with the land surface and the research problems associated with the interpretation of satellite data over the Earth's land surface. The experimental objectives of the First ISLSCP Field Experiment (FIFE) were the simultaneous acquisition of satellite, atmospheric, and surface data and to use these data to understand the processes controlling energy/mass exchange at the surface. The experiment site is a 15 x 15 km area southeast of Manhattan, Kansas, intersected by Interstate 70 and Kansas highway 177. The Konza Prairie portion is 5 x 5 km and is a controlled experiment site consisting primarily of native tall grass prairie vegetation. The remainder of the site is grazing and farm land with trees along creek beds that are scattered over the area. Airborne multispectral imagery from the Multispectral Atmospheric Mapping Sensor (MAMS) was collected over this region on two days during Intensive Field Campaign-1 (1FC-1) to study the time and space variability of remotely-sensed geophysical parameters. These datasets consist of multiple overflights covering about a 60-min period during late morning on June 4, 1987 and shortly after dark on the following day. Image data from each overpass were calibrated and Earth located with respect to each other using aircraft inertial navigation system parameters and ground control points. These were the first MAMS flights made with 10-bit thermal data.

Jedlovec, G. J.↗

NASA NTRS1996

Development of a real-time transport performance optimization methodology

The practical application of real-time performance optimization is addressed (using a wide-body transport simulation) based on real-time measurements and calculation of incremental drag from forced response maneuvers. Various controller combinations can be envisioned although this study used symmetric outboard aileron and stabilizer. The approach is based on navigation instrumentation and other measurements found on state-of-the-art transports. This information is used to calculate winds and angle of attack. Thrust is estimated from a representative engine model as a function of measured variables. The lift and drag equations are then used to calculate lift and drag coefficients. An expression for drag coefficient, which is a function of parasite drag, induced drag, and aileron drag, is solved from forced excitation response data. Estimates of the parasite drag, curvature of the aileron drag variation, and minimum drag aileron position are produced. Minimum drag is then obtained by repositioning the symmetric aileron. Simulation results are also presented which evaluate the affects of measurement bias and resolution.

Gilyard, Glenn↗

NASA NTRS2015

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

DOE OSTI2024

Integrating an Ensemble Reward System into an Off-Policy Reinforcement Learning Algorithm for the Economic Dispatch of Small Modular Reactor-Based Energy Systems

Nuclear Integrated Energy Systems (NIES) have emerged as a comprehensive solution for navigating the changing energy landscape. They combine nuclear power plants with renewable energy sources, storage systems, and smart grid technologies to optimize energy production, distribution, and consumption across sectors, improving efficiency, reliability, and sustainability while addressing challenges associated with variability. The integration of Small Modular Reactors (SMRs) in NIES offers significant benefits over traditional nuclear facilities, although transferring involves overcoming legal and operational barriers, particularly in economic dispatch. This study proposes a novel off-policy Reinforcement Learning (RL) approach with an ensemble reward system to optimize economic dispatch for nuclear-powered generation companies equipped with an SMR, demonstrating superior accuracy and efficiency when compared to conventional methods and emphasizing RL’s potential to improve NIES profitability and sustainability. Finally, the research attempts to demonstrate the viability of implementing the proposed integrated RL approach in spot energy markets to maximize profits for nuclear-driven generation companies, establishing NIES’ profitability over competitors that rely on fossil fuel-based generation units to meet baseload requirements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗