Search NASA⌕ Search

SEARCH · Search NASA

Results for “assist”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

A Time-Regularized Multiple Gravity-Assist Low-Thrust Bounded-Impulse Model for Trajectory Optimization

The multiple gravity assist low-thrust (MGALT) trajectory model combines the medium-fidelity Sims-Flanagan bounded-impulse transcription with a patched-conics flyby model and is an important tool for preliminary trajectory design. While this model features fast state propagation via Kepler's equation and provides a pleasingly accurate estimation of the total mass budget for the eventual flight-suitable integrated trajectory it does suffer from one major drawback, namely its temporal spacing of the control nodes. We introduce a variant of the MGALT transcription that utilizes the generalized anomaly from the universal formulation of Kepler's equation as a decision variable in addition to the trajectory phase propagation time. This results in two improvements over the traditional model. The first is that the maneuver locations are equally spaced in generalized anomaly about the orbit rather than time. The second is that the Kepler propagator now has the generalized anomaly as its independent variable instead of time and thus becomes an iteration-free propagation method. The new algorithm is outlined, including the impact that this has on the computation of Jacobian entries for numerical optimization, and a motivating application problem is presented that illustrates the improvements that this model has over the traditional MGALT transcription.

Optimization↗
NASA NTRS2017

A Time-Regularized, Multiple Gravity-Assist Low-Thrust, Bounded-Impulse Model for Trajectory Optimization

The multiple gravity assist low-thrust (MGALT) trajectory model combines the medium-fidelity Sims-Flanagan bounded-impulse transcription with a patched-conics flyby model and is an important tool for preliminary trajectory design. While this model features fast state propagation via Keplers equation and provides a pleasingly accurate estimation of the total mass budget for the eventual flight suitable integrated trajectory it does suffer from one major drawback, namely its temporal spacing of the control nodes. We introduce a variant of the MGALT transcription that utilizes the generalized anomaly from the universal formulation of Keplers equation as a decision variable in addition to the trajectory phase propagation time. This results in two improvements over the traditional model. The first is that the maneuver locations are equally spaced in generalized anomaly about the orbit rather than time. The second is that the Kepler propagator now has the generalized anomaly as its independent variable instead of time and thus becomes an iteration-free propagation method. The new algorithm is outlined, including the impact that this has on the computation of Jacobian entries for numerical optimization, and a motivating application problem is presented that illustrates the improvements that this model has over the traditional MGALT transcription.

Optimization↗
NASA NTRS2017

Fabrication of Lightweight Radiation Shielding Composite Materials by Field Assisted Sintering Technique (FAST)

Advances in radiation shielding technologies are needed to protect humans and electronic components from all threats of space radiation over long durations. In this paper, we report on the use of the innovative and novel fabrication technology known as Field Assisted Sintering Technology (FAST) to fabricate lightweight material with enhanced radiation shielding strength to safeguard humans and electronics suitable for next generation space exploration missions. The base materials we investigated were aluminum (Al), the current standard material for space hardware, and Ultra-High Molecular Weight Polyethylene (UHMWPE), which has high hydrogen content and resistance to nuclear reaction from neutrons, making it a good shielding material for both gamma radiation and particles. UHMWPE also has high resistance to corrosive chemicals, extremely low moisture sensitivity, very low coefficient of friction, and high resistance to abrasion. We reinforced the base materials by adding high density (ie, high atomic weight) metallic material into the composite. These filler materials included: boron carbide (B4C), tungsten (W), tungsten carbide (WC) and gadolinium (Gd).

Prasad, Narasimha↗
NASA NTRS2017

GeoDash: Assisting Visual Image Interpretation in Collect Earth Online by Leveraging Big Data on Google Earth Engine

Collect Earth Online (CEO) is a free and open online implementation of the FAO Collect Earth system for collaboratively collecting environmental data through the visual interpretation of Earth observation imagery. The primary collection mechanism in CEO is human interpretation of land surface characteristics in imagery served via Web Map Services (WMS). However, interpreters may not have enough contextual information to classify samples by only viewing the imagery served via WMS, be they high resolution or otherwise. To assist in the interpretation and collection processes in CEO, SERVIR, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries, developed the GeoDash system, an embedded and critical component of CEO. GeoDash leverages Google Earth Engine (GEE) by allowing users to set up custom browser-based widgets that pull from GEE's massive public data catalog. These widgets can be quick looks of other satellite imagery, time series graphs of environmental variables, and statistics panels of the same. Users can customize widgets with any of GEE's image collections, such as the historical Landsat collection with data available since the 1970s, select date ranges, image stretch parameters, graph characteristics, and create custom layouts, all on-the-fly to support plot interpretation in CEO. This presentation focuses on the implementation and potential applications, including the back-end links to GEE and the user interface with custom widget building. GeoDash takes large data volumes and condenses them into meaningful, relevant information for interpreters. While designed initially with national and global forest resource assessments in mind, the system will complement disaster assessments, agriculture management, project monitoring and evaluation, and more.

SERVI↗
NASA NTRS2018

MMS Extended Mission Design: Evaluation of a Lunar Gravity Assist Option

This paper will describe a study that was carried out on the design of a set of maneuvers that were considered for the later stages of an extended mission of the Magnetospheric Multiscale (MMS) mission. The goal of these maneuvers was to put MMS into a significantly different orbit from those flown heretofore, so allowing science collection in a different region of the magnetosphere. This study was made feasible by the fact that the rate at which fuel is being consumed to maintain small formations on the MMS high-apogee orbit is less than expected pre-flight: the current consumption rate is only about 2 kg/yr/spacecraft. In addition, the spacecraft finished the prime mission with a significant amount of fuel remaining: this was about 1-sigma above the mean when compared with pre-launch Monte Carlo simulations. The resulting situation is similar to that of a libration orbit mission, where station-keeping requires so little fuel that any margin at all will lead to an extensive mission lifetime. In the case of MMS, the spacecraft could, if desired, perform formation flying in the current orbit for several decades. Alternatively, the spacecraft could use a significant fraction of the remaining fuel to perform major orbit modifications, while still leaving enough to conduct formation flying for on the order of a decade. The extended mission maneuvers studied here are further apogee-raises, with the goal of setting up one or more lunar gravity assists. Geometry dictates that a lunar encounter is only achievable when the MMS apogee vector lies approximately in the lunar orbit plane: this limits the possible dates to mid-2021 or early 2027.

Design↗
NASA NTRS2018

Segregation-Assisted Plasticity in Ni-Based Superalloys

Correlative high resolution transmission electron microscopy and energy dispersive X-ray spectroscopy are used to study deformation-induced planar faults in the single crystal superalloy MD2 crept at 800°C and 650 MPa. Segregation of Cr and Co at microtwins, APBs, CISFs/SISFs and CESFs/SESFs is confirmed and quantified. The extent of this is found to depend upon the fault type, being most pronounced for the APB. The CESF/SESF is studied in detail due to its role as a precursor of the microtwins causing the majority of plasticity under these conditions. Quantitative modelling is carried out to rationalize the findings; the experimental results are consistent with a greater predicted velocity for the lengthening of the CESF/SESF { compared with the other types of fault { and hence confirm its role in the diffusion-assisted plasticity needed for the microtwinning mechanism to be operative.

Barba, D.↗
NASA NTRSDate not supplied

High dimensional similarity search with quantum assisted variational autoencoder

Recent progress in quantum algorithms and hardware is indicator of the potential importance of quantum computing in the next future. However, finding suitable application areas remains an active area of research. Quantum machine learning [1] is touted as a potential approach to demonstrate quantum advantage within both the gate-model [2,3] and the adiabatic [4,5] schemes. For instance, the Quantum-assisted Variational Autoencoder (QVAE) [6] has been proposed as a quantum enhancement to the discrete VAE [7]. We extend on previous work and study the real-world applicability of a QVAE, specifically, for similarity search in large-scale high dimensional datasets. While similarity search algorithms are available for low dimensional datasets, scaling to billion-scale datasets with thousands of dimensions is non-trivial. We show how the latent-space representation of a QVAE can be used to construct a space-efficient search index. We back up our claims by experimental results which show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset. Further, we show real-world speedups compared to linear search and demonstrate memory efficient scaling to large-scale datasets.

Nicholas D Gao↗
NASA NTRS2020

Heatshields for Aerogravity Assist Vehicles Whose Deceleration at Titan Saves Mass for Future Flagship Class Exploration of Enceladus

This paper reports the feasibility of using mature heatshield materials for an aerogravity assist (AGA) vehicle whose deceleration in Titan’s atmosphere is a mass-saving enabler for nine different Enceladus missions (T. Spilker et al. 2009). A geometry for the Titan AGA vehicle is recommended as are high-fidelity flow computations on that shape.

James O. Arnold↗
NASA NTRSDate not supplied

A Tool For Identifying Key Gravity-Assist Trajectories From Broad Search Results

A tool is presented that identifies desirable trajectory candidates from among tens of thousands of gravity-assist trajectories. A broad trajectory search technique creates an exhaustive set of possible trajectories to a given planet. From this dataset, our tool reveals candidate trajectories with user-defined characteristics. Typical discriminating characteristics are launch V-infinity, time-of-flight, and delivered mass. Mission planners evaluate and plot interesting trajectories from within the tool. Our tool generates catalogs of selected trajectories for further evaluation with higher-fidelity trajectory solvers. This paper outlines the key features of the tool and gives examples of typical analyses.

uranus, interplanetary↗
NASA NTRS1993

Operations Automation Using the Link Monitor and Control Operator Assistant

The Link Monitor & Control Operator Assistant (LMC OA) is a knowledge-based prototype system which uses Artificial Intelligence (AI) techniques to provide semi-automated monitor and control functions to support operations of the Deep Space Network (DSN) 70-Meter antenna at the Goldstone Deep Space Communications Camplex (DSCC).

Goldstone↗
NASA NTRSDate not supplied

Heat Shields for Aerogravity Assist Vehicles Whose Deceleration at Titan Saves Mass for Future Flagship Class Exploration of Enceladus

A mission of great Astrobiological interest is one that would search for life signatures associated with the oceans and geysers of Enceladus [1]. Spilker et al., [2] have shown in a 2009 paper that use of an Aerogravity Assist (AGA) maneuver with a blunt body in Titan’s atmosphere could enable a Flagship Class Mission to Enceladus within reasonable cost ($3 B) and mission duration (14 years). This paper will summarize the 2023 Decadal Survey (DS) Whitepaper by Arnold, et al. [3] that estimated heat shield masses for an AGA vehicle whose deceleration in Titan’s atmosphere saves mass for future missions to explore Enceladus. This study focused on Titan AGA for an Enceladus lander corresponding to mission “E” in the Spilker, et al. paper [2]. The analysis is the first reported for heat shield requirements for an AGA aeroshell that accounts for the convective and radiation heating arising from flight in Titan’s atmosphere.

James O. Arnold↗
NASA NTRS2020

Assistive Relative Pose Estimation for On-orbit Assembly using Convolutional Neural Networks

Accurate real-time pose estimation of spacecraft or object in space is a key capability necessary for on orbit spacecraft servicing and assembly tasks. Pose estimation of objects in space is more challenging than for objects on Earth due to space images containing widely varying illumination conditions, high contrast, and poor resolution in addition to power and mass constraints. In this paper, a convolutional neural network is leveraged to uniquely determine the translation and rotation of an object of interest relative to the camera. The main idea of using CNN model is to assist object tracker used in on space assembly tasks where only feature based method is always not sufficient. The simulation framework designed for assembly task is used to generate dataset for training the modified CNN models and, then results of different models are compared with measure of how accurately models are predicting the pose. Unlike many current approaches for spacecraft or object in space pose estimation, the model does not rely on hand-crafted object-specific features which makes this model more robust and easier to apply to other types of spacecraft. It is shown that the model performs comparable to the current feature-selection methods and can therefore be used in conjunction with them to provide more reliable estimates.

Sonawani, Shubham↗
NASA NTRS2020

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗
NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗
NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modelling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) group at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗