Results for “data fidelity” — Page 64

NASA NTRSDate not supplied

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was designed for a cruise Mach of 1.7 and 40 passengers. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, was generated using computational fluid dynamics (CFD) based sonic boom analysis at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) and modeled as a flow-through nacelle for CFD analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned using an aeropropulsive CFD simulation. A process is developed for approximation of the NPSS engine at SOC by a CFD engine for aeropropulsive CFD simulation. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the configuration with the CFD engines is optimized to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept. Finally, the CFD simulation data for the optimized concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of low-boom supersonic transports.

Low-boom supersonic transport↗

NASA NTRSDate not supplied

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was designed for a cruise Mach of 1.7 and 40 passengers. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, was generated using computational fluid dynamics (CFD) based sonic boom analysis at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) and modeled as a flow-through nacelle for CFD analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned using an aeropropulsive CFD simulation. A process for approximation of the NPSS engine at SOC by a CFD engine is developed. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the configuration with the CFD engines is optimized to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept. Finally, the CFD simulation data for the optimized concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of low-boom supersonic transports.

Low-boom supersonic transport↗

DOE OSTI2026

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗

DOE OSTI2022

Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework

Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Creation of a prototype biomimetic fish to better understand impact trauma caused by hydropower turbine blade strikes

Biomimetic model organisms could be useful surrogates for live animals in many applications if the models have sufficient biofidelity. One such application is for use in field and laboratory tests of fish mortality associated with passage through hydropower turbines. Laboratory trials suggest that blade strikes are especially injurious and often causes mortality when fish are struck by thinner blades moving at higher velocities. Dose-response relationships have been created from these data, but the exact relationship between fish mortality and the actual forces enacted on fish during simulated blade strike testing remains unknown. Here, we describe the methods used to create a prototype biomimetic model fish composed of ballistic gelatin and covered with a surrogate skin to better approximate the biomechanical properties of a fish body. Frozen fish were scanned with high-fidelity laser scanners, and a 3D-printed, reusable mold was created from which to cast our gelatin model. Computed tomography scan data, imaged directly or taken from online data repositories, were also successfully used to create CAD models for use in additive manufacturing of molds. One 3-axis accelerometer was embedded into the gelatin to compare accelerometer data to dose-response data from previous laboratory research on live fish. The resulting model ( i.e. , Gelfish) had a statistically indistinguishable tissue durometer to that of real fish tissue and preliminary blade strike impact testing suggested its overall flexibility was similar to that of live fish. Gelfish was designed with biofidelity as its guiding principle and our results suggest initial experimentation was successful. Future research will include replication of initial Gelfish test results, quantitative measurement of model flexibility relative to real fish, and inclusion of surrogate skeletal structures to enhance biofidelity. Use of more sophisticated sensors would also better quantify the physical forces of blade strike impact and help determine how said forces correlate with rates of mortality observed during tests on live fish.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2018

A Case for High-Fidelity Material Response Modeling

Material response modeling of heatshields for planetary entry vehicles has remained largely unchanged since Aerotherm Corp. introduced the CMA program in 1967. Modern models, like FIAT, have tread the same path, introducing efficiencies and better material property data along the way, but otherwise following the same underlying model paradigm. The CMA approach has worked well for heatshield design up to this point. However, there are three motivations for the material response community to pursue higher fidelity beyond simplified, CMA-derived models. The first motivation is that missions are becoming increasingly demanding and complex and, as they do, confidence in simplified models naturally decreases. Second, reliability of materials is now as much or more of a driving concern for mission designers than thermal response. Third, NASA and other agencies are increasingly interested in flight instrumentation for engineering science. This latter motivation places far stricter requirements on model accuracy in order to meet requirements for flight environment reconstruction.

Barnhardt, Michael D.↗

NASA NTRSDate not supplied

Advanced Modeling of Control-Structure Interaction in Thrust Vector Control Systems

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.

Launch Vehicles↗

NASA NTRSDate not supplied

Advanced Modeling of Control-Structure Interaction in Thrust Vector Control Systems

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.

Launch Vehicles↗

DOE OSTI2021

Updates to Improve the Evaluated Nuclear Data of Copper Isotopes in the Resolved and Unresolved Resonance Regions

The evaluated nuclear data of the 63,65 Cu isotopes have been updated in the resolved and unresolved resonance energy regions with the goal of improving the fidelity between calculated and measured critical benchmarks. Particular focus was devoted to the 63 Cu(n, γ) cross sections because of their large sensitivity to the reactivity in the benchmark calculations. By focusing on these cross sections, the set of parameters in both resolved and unresolved resonance regions were fitted to available experimental data. The newly updated evaluations were compared to the currently available ENDF/B-VIII.0 evaluations in reactivity calculations for copper-sensitive integral benchmarks. An initial study of the sensitivity of the benchmarks to the angular distributions was performed, finding it necessary to describe the angular distributions more accurately above 100 keV. This investigation uncovered the need for more accurate data for the 63 Cu(n, γ) cross section above 100 keV. An increase in the capture cross section was found to improve agreement for the considered benchmarks.

07 ISOTOPE AND RADIATION SOURCES↗

NASA NTRS2002

From Monolithics to Tethers to Freeflyers: The Spectrum of Large Aperture Sensing from Space

As part of NASA's endeavor to push the envelope and go where we have never been before, the Space Science Enterprise has laid out a vision which includes several missions that revolutionize the collection of scientific data from space. Many of the missions designed to meet the objectives of these programs depend heavily on the ability to perform space-based interferometry, which has recently become a rapidly growing field of investigation for both the scientific and engineering communities. While scientists are faced with the challenges of designing high fidelity optical systems capable of making detailed observations, engineers wrestle with the problem of providing s-pace-based platforms that can permit this data gathering to occur. Observational data gathering is desired at's variety of spectral wavelengths and resolutions, calling for interferometers with a range of baseline requirements. Approaches to configuration design are as varied as the missions themselves from large monolithic spacecraft to multiple free-flying small spacecraft and everything in between. As will be discussed, no one approach provides a 'panacea' of solutions rather each has its place in terms of the mission requirements. The purpose here is to identify the advantages and disadvantages of the various approaches, to discuss the driving factors in design selection and determine the relative range of applicability of each design approach.

Leitner, Jesse↗

NASA NTRSDate not supplied

Developing Fast and Accurate Radiative Transfer Models to Meet the Needs of Modern Satellite Remote Sensing Applications

Modern hyperspectral satellite remote sensors provide highly accurate measurements the Earth’s Top-of-Atmosphere (TOA) radiance, reflectance, or polarized spectra with hundreds to thousands of spectral channels and with millions of observations per day. The large data volume and high spectral dimensionality of the data pose challenges for retrieval algorithms. To process the satellite Level-1 data (e.g. calibrated TOA spectra) into Level-2 products (e.g. atmospheric and surface properties) using physical-based retrieval algorithms, accurate and fast Radiative Transfer Models (RTMs) are needed. RTMs are usually the limiting factor in determining the speed of a level-2 algorithm. For example, more than one million Line-by-Line (LBL) radiative transfer (RT) calculations are needed in order to properly capture the spectral contributions of important atmospheric molecules for an IR hyperspectral sensor with a spectral coverage from 3.5 m to 15 m or a solar hyperspectral sensor with spectral coverage from 0.25 m to 2.5 m. In this presentation, we will discuss advantages and disadvantages of different ways (e.g. correlated k and effective transmittance) to accelerate the speed of a fast RTM. We finally describe a Principal Component-based Radiative Transfer Model (PCRTM), which can calculate TOA radiance or reflectance spectra from 50 cm-1 to 40,000 cm-1 (200 m to 0.25 m). It has demonstrated very good accuracy relative to reference LBL RTMs and saves orders of magnitude in computational time. The PCRTM has been used in many satellite remote sensing applications. Examples include forward modeling in Level-2 and Level-3 retrieval algorithms, high fidelity satellite instrument simulators and instrument performance trade studies, spectral and radiometric accuracy characterizations of satellite Level-1 data, tools for inter-satellite calibrations, tools for satellite RTM lookup table generations, and tools for generating physically based training datasets for Artificial Intelligence (AI) algorithms.

climate data record↗

NASA NTRSDate not supplied

An Approach to Shape Parameterization Using Laboratory Hypervelocity Impact Experiments

NASA’s Orbital Debris Program Office relies on laboratory-based impact tests to supplement the measurement data of on-orbit events that defines the orbital debris environment. These experiments provide information that is essential to interpreting the radar and optical measurements of orbital fragmentation events into useful metrics, such as characteristic size of the debris, and to providing a better understanding of the distributions of fragment populations in terms of their masses, material constituents, fragment densities, cross-sectional areas, area-to-mass ratios, shapes, etc. The Satellite Orbital Debris Characterization Impact Test (SOCIT) was a notable laboratory impact experiment conducted in 1992 using a surplus U.S. Navy Transit navigation satellite of the 1960s. The data from this ground-based experiment were combined with on-orbit measurements to develop the NASA Standard Satellite Breakup Model (SSBM). To account for advancements in satellite design and construction since, a new impact test series – DebriSat – was conducted in 2014. This test utilized a high-fidelity mock-up spacecraft that better represents the materials and construction techniques used to design and manufacture modern spacecraft. Together, these tests offer valuable data to model an orbital debris environment composed of legacy and modern spacecraft. This paper presents an overview of the two laboratory impact tests, comparing their fragment parameter distributions with each other and with relevant distributions from the NASA SSBM. The categorization and descriptions of fragment shapes are of significant interest for future work, yet there are marked differences in the definitions of shape categories between each dataset. The categorizations of constituent materials, and the measurement techniques employed to populate these two datasets, are also different. New rubrics simplify and equate the categorizations between datasets to aid comparative analyses and to facilitate the potential use of both datasets in tandem with future environmental debris models. A preferred approach to classifying shape across disparate datasets uses the characteristic-length dimensions, and a simplified shape classification based on physical, solid-body dimensions, to mathematically construct an encapsulating right-circular cylinder that represents the fragment. The ratio of cylinder length-to-diameter (L:D) then provides a single continuum value for shape that is strongly correlated with its designated shape and size. This metric can then be used to further assess the distribution of shape with populations of other fragment characteristics within these datasets. The shape parameterization using the L:D ratios of right-circular cylinders is discussed.

John H. Seago↗

NASA NTRSDate not supplied

An Approach to Shape Parameterization Using Laboratory Hypervelocity Impact Experiments

NASA’s Orbital Debris Program Office relies on laboratory-based impact tests to supplement the measurement data of on-orbit events that defines the orbital debris environment. These experiments provide information that is essential to interpreting the radar and optical measurements of orbital fragmentation events into useful metrics, such as characteristic size of the debris, and to providing a better understanding of the distributions of fragment populations in terms of their masses, material constituents, fragment densities, cross-sectional areas, area-to-mass ratios, shapes, etc. The Satellite Orbital Debris Characterization Impact Test (SOCIT) was a notable laboratory impact experiment conducted in 1992 using a surplus U.S. Navy Transit navigation satellite of the 1960s. The data from this ground-based experiment were combined with on-orbit measurements to develop the NASA Standard Satellite Breakup Model (SSBM). To account for advancements in satellite design and construction since, a new impact test series – DebriSat – was conducted in 2014. This test utilized a high-fidelity mock-up spacecraft that better represents the materials and construction techniques used to design and manufacture modern spacecraft. Together, these tests offer valuable data to model an orbital debris environment composed of legacy and modern spacecraft. This paper presents an overview of the two laboratory impact tests, comparing their fragment parameter distributions with each other and with relevant distributions from the NASA SSBM. The categorization and descriptions of fragment shapes are of significant interest for future work, yet there are marked differences in the definitions of shape categories between each dataset. The categorizations of constituent materials, and the measurement techniques employed to populate these two datasets, are also different. New rubrics simplify and equate the categorizations between datasets to aid comparative analyses and to facilitate the potential use of both datasets in tandem with future environmental debris models. A preferred approach to classifying shape across disparate datasets uses the characteristic-length dimensions, and a simplified shape classification based on physical, solid-body dimensions, to mathematically construct an encapsulating right-circular cylinder that represents the fragment. The ratio of cylinder length-to-diameter (L:D) then provides a single continuum value for shape that is strongly correlated with its designated shape and size. This metric can then be used to further assess the distribution of shape with populations of other fragment characteristics within these datasets. The shape parameterization using the L:D ratios of right-circular cylinders is discussed.

John H Seago↗

NASA NTRSDate not supplied

Acoustics and Performance Characteristics of an Ideally Twisted Rotor in Hover

A series of experiments were conducted in an anechoic chamber to investigate the noise and performance of an ideally twisted rotor design, leading to validation of a low-fidelity aerodynamic performance and acoustic modeling tool chain. An "ideally twisted" rotor was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor design was then fabricated using state-of-the-art rapid prototyping and tested in an anechoic chamber facility. Aerodynamic load and acoustic data were acquired across a range of rotation rates (RPM) and rotor collective settings in order to ascertain the accuracy of the low-fidelity modeling codes. Emphasis was placed on modeling of the broadband self-noise generated by the rotor system due to the fact that it was found to be a prominent contributor to the overall rotor system noise.

Nicole A. Pettingill↗

DOE OSTI2025

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗

NASA NTRS2016

NEEMO 18-20: Analog Testing for Mitigation of Communication Latency During Human Space Exploration

NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission-like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014-2015, NEEMO's 18-20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of communication latencies on operations concepts, timelines, and tasks were studied. METHODS: Twelve subjects (4 per mission) were weighed out to simulate near-zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth-based science team (ST) to provide input and direction during exploration activities. Exploration traverses were preplanned based on precursor data. Subjects completed science-related tasks including pre-sampling surveys, geologic-based sampling, and marine-based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were designed to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One-way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, ST assimilation time (defined as time available for ST to discuss data/imagery after data acquisition). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high-fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for pre-sampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across communication latencies and can be done with minimal crew idle time. Imagery and contextual information from the EVA crew that is transmitted real-time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide meaningful feedback and instruction to the crew regarding sampling priorities, additional tasks, and changes to the EVA timeline. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency.

Chappell, Steven P.↗

NASA NTRS1990

A high-fidelity satellite ephemeris program for Earth satellites in eccentric orbits

A program for mission planning called the Analytic Satellite Ephemeris Program (ASEP), produces projected data for orbits that remain fairly close to the Earth. ASEP does not take into account lunar and solar perturbations. These perturbations are accounted for in another program called GRAVE, which incorporates more flexible means of input for initial data, provides additional kinds of output information, and makes use of structural programming techniques to make the program more understandable and reliable. GRAVE was revised, and a new program called ORBIT was developed. It is divided into three major phases: initialization, integration, and output. Results of the program development are presented.

Simmons, David R.↗