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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A review of European applications of artificial intelligence to space

The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

Drummond, Mark↗
NASA NTRS1994

Communications and control for electric power systems: Power system stability applications of artificial neural networks

This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

Toomarian, N.↗
NASA NTRS1994

Effect of artificial viscosity on three-dimensional flow solutions

Artificial viscosity is added either implicity or explicitly in practically every numerical scheme for suppressing spurious oscillations in the solution of fluid-dynamics equations. In the present central-difference scheme, artificial viscosity is added explicitly for suppressing high-frequency oscillations and achieving good convergence properties. The amount of artificial viscosity added is controlled through the use of preselected coefficients. In the standard scheme, scalar coefficients based on the spectral radii of the Jacobian of the convective fluxes are used. However, this can add too much viscosity to the slower waves. Hence, the use of matrix-valued coefficients, which give appropriate viscosity for each wave component, is suggested. With the matrix-valued coefficients, the central-difference scheme produces more accurate solutions on a given grid, particularly in the vicinity of shocks and boundary layers, while still maintaining good convergence properties.

Turkel, Eli↗
NASA NTRS1996

Automation of Some Operations of a Wind Tunnel Using Artificial Neural Networks

Artificial neural networks were used successfully to sequence operations in a small, recently modernized, supersonic wind tunnel at NASA-Lewis Research Center. The neural nets generated correct estimates of shadowgraph patterns, pressure sensor readings and mach numbers for conditions occurring shortly after startup and extending to fully developed flow. Artificial neural networks were trained and tested for estimating: sensor readings from shadowgraph patterns, shadowgraph patterns from shadowgraph patterns and sensor readings from sensor readings. The 3.81 by 10 in. (0.0968 by 0.254 m) tunnel was operated with its mach 2.0 nozzle, and shadowgraph was recorded near the nozzle exit. These results support the thesis that artificial neural networks can be combined with current workstation technology to automate wind tunnel operations.

Decker, Arthur J.↗
NASA NTRS1998

Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults With Amputations

The first single function myoelectric prosthetic hand was introduced in the 1960's. This hand was controlled by the electric fields generated by muscle contractions in the residual limb of the amputee user. Electrodes and amplifiers, embedded in the prosthetic socket, measured these electric fields across the skin, which increase in amplitude as the individual contracts their muscle. When the myoelectric signal reached a certain threshold amplitude, the control unit activated a motor which opened or closed a hand-like prosthetic terminal device with a pincher grip. Late in the 1990's, little has changed. Most current myoelectric prostheses still operate in this same, single-function way. To better understand the limitations of the current single-function myoelectric hand and the needs of those who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (NUH), surveyed approximately 2,500 individuals with upper limb loss [1]. When asked to identify specific features of their current myoelectric prostheses that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement, as well as poor control capability. However, simply building a mechanism with individual finger and wrist motion is not enough. In the 1960's and 1970's, engineers built a number of more dexterous prosthetic hands. Unfortunately, these were rejected during clinical trials due to a difficult and distracting control interface. The goal of this project, "Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults with Amputations," was to lay the foundation for a multi-function, intuitive myoelectric control system which requires no conscious thought to move the hand. We built an extensive myoelectric signal database for six motions from ten amputee volunteers, We also tested a control system based on new artificial intelligence techniques on the data from two of these subjects. This data is available to anyone doing myoelectric control research. Its availability is an important contribution to the prosthetics research community, as many researchers do not have access to amputee subjects. Since we collected myoelectric data from subjects' sound arms as well as their residual arms, this database will also prove useful to virtual reality and robotics researchers who want to explore myoelectric-based interfaces between any user and a machine. Currently, one small company (Intelligenta, Inc.) and one university (University of New Brunswick, Canada) are using this myoelectric database under other funding to develop multifunction control systems for prostheses. A prosthetics manufacturer (Liberty Technology, Inc.) is making plans to incorporate the results of their work into an artificial hand capable of several different movements to provide functionality only dreamed of by current myoelectric users. Methods Six adults and four children, all with unilateral, below-elbow amputations served as subjects. Five of the adults (3 male, 2 female, average age 34 years) had amputations due to traumatic injury, while one adult (female, age 32 years) and the four children (3 male, 1 female, average age 13 years) had congenital (i.e. from birth) limb deficiencies.

Atkins, Diane J.↗
NASA NTRS1998

An Assessment of Artificial Compressibility and Pressure Projection Methods for Incompressible Flow Simulations

Performance of the two commonly used numerical procedures, one based on artificial compressibility method and the other pressure projection method, are compared. These formulations are selected primarily because they are designed for three-dimensional applications. The computational procedures are compared by obtaining steady state solutions of a wake vortex and unsteady solutions of a curved duct flow. For steady computations, artificial compressibility was very efficient in terms of computing time and robustness. For an unsteady flow which requires small physical time step, pressure projection method was found to be computationally more efficient than an artificial compressibility method. This comparison is intended to give some basis for selecting a method or a flow solution code for large three-dimensional applications where computing resources become a critical issue.

Kwak, Dochan↗
NASA NTRS2002

Microbial identification by immunohybridization assay of artificial RNA labels

Ribosomal RNA (rRNA) and engineered stable artificial RNAs (aRNAs) are frequently used to monitor bacteria in complex ecosystems. In this work, we describe a solid-phase immunocapture hybridization assay that can be used with low molecular weight RNA targets. A biotinylated DNA probe is efficiently hybridized in solution with the target RNA, and the DNA-RNA hybrids are captured on streptavidin-coated plates and quantified using a DNA-RNA heteroduplex-specific antibody conjugated to alkaline phosphatase. The assay was shown to be specific for both 5S rRNA and low molecular weight (LMW) artificial RNAs and highly sensitive, allowing detection of as little as 5.2 ng (0.15 pmol) in the case of 5S rRNA. Target RNAs were readily detected even in the presence of excess nontarget RNA. Detection using DNA probes as small as 17 bases targeting a repetitive artificial RNA sequence in an engineered RNA was more efficient than the detection of a unique sequence.

Non-NASA Center↗
NASA NTRS2006

Artificial Gravity as a Multi-System Countermeasure to Bed Rest Deconditioning: Preliminary Results

Artificial gravity paradigms may offer effective, efficient, multi-system protection from the untoward effects of adaptation to the microgravity of space or the hypogravity of planetary surfaces. Intermittent artificial gravity (AG) produced by a horizontal short-radius centrifuge (SRC) has recently been utilized on human test subjects deconditioned by bed rest. This presentation will review preliminary results of a 41 day study conducted at the University of Texas Medical Branch, Galveston, TX bed rest facility. During the first eleven days of the protocol, subjects were ambulatory, but confined to the facility. They began a carefully controlled diet, and participated in multiple baseline tests of bone, muscle, cardiovascular, sensory-motor, immunological, and psychological function. On the twelfth day, subjects entered the bed rest phase of the study, during which they were confined to strict 6deg head down tilt bed rest for 21 days. Beginning 24 hrs into this period, treatment subjects received one hour daily exposures to artificial gravity which was produced by spinning the subjects on a 3.0 m radius SRC. They were oriented radially in the supine position so that the centrifugal force was aligned with their long body axis, and while spinning, they "stood" on a force plate, supporting the centrifugal loading (2.5 g at the feet, 1.0 g at the heart). The subject station allowed free translation over approximately 10 cm to ensure full loading of the lower extremities and to allow for anti-orthostatic muscle contractions. Control subjects were positioned on the centrifuge but did not spin. Following the bed rest phase, subjects were allowed to ambulate again, but remained within the facility for an additional 9 days and participated in multiple follow-up tests of physiological function.

Warren, L. E.↗
NASA NTRS2006

History of Artificial Gravity

This chapter reviews the past and current projects on artificial gravity during space missions. The idea of a rotating wheel-like space station providing artificial gravity goes back in the writings of Tsiolkovsky, Noordung, and Wernher von Braun. Its most famous fictional representation is in the film 2001: A Space Odyssey, which also depicts spin-generated artificial gravity aboard a space station and a spaceship bound for Jupiter. The O Neill-type space colony provides another classic illustration of this technique. A more realistic approach to rotating the space station is to provide astronauts with a smaller centrifuge contained within a spacecraft. The astronauts would go into it for a workout, and get their gravity therapeutic dose for a certain period of time, daily or a few times a week. This simpler concept is current being tested during ground-based studies in several laboratories around the world.

Clement, Gilles↗
NASA NTRS2007

Preliminary Assessment of Artificial Gravity Impacts to Deep-Space Vehicle Design

Even after more than thirty years of scientific investigation, serious concerns regarding human physiological effects of long-duration microgravity exposure remain. These include loss of bone mineral density, skeletal muscle atrophy, and orthostatic hypertension, among others. In particular, "Safe Passage: Astronaut Care for Exploration Missions," states "loss of bone density, which apparently occurs at a rate of 1% per month in microgravity, is relatively manageable on the short-duration missions of the space shuttle, but it becomes problematic on the ISS [International Space Station]. ...If this loss is not mitigated, interplanetary missions will be impossible." While extensive investigations into potential countermeasures are planned on the ISS, the delay in attaining full crew complement and onboard facilities, and the potential for extending crews tours of duty threaten the timely (< 20 years!) accumulation of sufficient data for countermeasures formulation. Indeed, there is no guarantee that even with the data, a practical or sufficiently robust set of countermeasures will be forthcoming. Providing an artificial gravity (AG) environment by crew centrifugation aboard deep-space human exploration vehicles, long a staple technique of science fiction, has received surprisingly limited engineering assessment. This is most likely due to a number of factors: the lack of definitive design requirements, especially acceptable artificial gravity levels and rotation rates, the perception of high vehicle mass and performance penalties, the incompatibility of resulting vehicle configurations with space propulsion options (i.e., aerocapture), the perception of complications associated with de-spun components such as antennae and photovoltaic arrays, and the expectation of effective crew micro-gravity countermeasures. These perception and concerns may have been overstated, or may be acceptable alternatives to countermeasures of limited efficacy. This study was undertaken as an initial step to try to understand the implications of and potential solutions to incorporating artificial gravity in the design of human deep-space exploration vehicles. Of prime interest will be the mass penalties incurred by incorporating AG, along with any mission performance degradation.

Joosten, B. Kent↗
NASA NTRS2008

Flying by Ear: Blind Flight with a Music-Based Artificial Horizon

Two experiments were conducted in actual flight operations to evaluate an audio artificial horizon display that imposed aircraft attitude information on pilot-selected music. The first experiment examined a pilot's ability to identify, with vision obscured, a change in aircraft roll or pitch, with and without the audio artificial horizon display. The results suggest that the audio horizon display improves the accuracy of attitude identification overall, but differentially affects response time across conditions. In the second experiment, subject pilots performed recoveries from displaced aircraft attitudes using either standard visual instruments, or, with vision obscured, the audio artificial horizon display. The results suggest that subjects were able to maneuver the aircraft to within its safety envelope. Overall, pilots were able to benefit from the display, suggesting that such a display could help to improve overall safety in general aviation.

Simpson, Brian D.↗
NASA NTRS2015

Computational Analysis of Artificial Gravity as a Possible Countermeasure to Spaceflight Induced Bone Loss

During exploration class missions, such as to asteroids and Mars, astronauts will be exposed to reduced gravity for extended periods. Data has shown that astronauts lose bone mass at a rate of 1% to 2% a month in microgravity, particularly in lower extremities such as the proximal femur. Exercise countermeasures have not completely eliminated bone loss from long duration spaceflight missions, which leaves astronauts susceptible to early onset osteoporosis and greater risk of fracture. Introduction of the Advanced Resistive Exercise Device and other large exercise devices on the International Space Station (ISS), coupled with improved nutrition, has further minimized bone loss. However, unlike the ISS, exploration vehicles will have very limited volume and power available to accommodate such capabilities. Therefore, novel concepts like artificial gravity systems are being explored as a means to provide sufficient load stimulus to the musculoskeletal system to mitigate bone changes that may lead to early onset osteoporosis and increased risk of fracture. Currently, there is minimal data available to drive further research and development efforts to appropriately explore such options. Computational modeling can be leveraged to gain insight on the level of osteoprotection that may be achieved using artificial gravity produced by a spinning spacecraft or centrifuge. With this in mind, NASA's Digital Astronaut Project (DAP) has developed a bone remodeling model that has been validated for predicting volumetric bone mineral density (vBMD) changes of trabecular and cortical bone both for gravitational unloading condition and the equivalent of 1g daily load stimulus. Using this model, it is possible to simulate vBMD changes in trabecular and cortical bone under different gravity conditions. In this presentation, we will discuss our preliminary findings regarding if and how artificial gravity may be used to mitigate spaceflight induced bone loss.

Mulugeta, L.↗
NASA NTRS2018

Combustion Stability Evaluation of Artificial Disturbance Dynamic Response

General guidelines are provided in CPIA Publication 6551 for evaluation of the response due to an artificial disturbance, however the guideline also allows for ambiguous interpretation. Stability rating devices that produce an artificial disturbance are traditionally explosive bombs and pulse guns. This paper reviews a recently developed objective process that can be applied consistently in the reduction of artificial disturbance dynamic data. It also examines three methods of response evaluation. The first method examines the response of a specific mode of interest and requires data filtering encompassing that mode. The second method examines the response of a specific mode of interest and its nonlinear components and requires a more complex filtering scheme. The third method examines the response of the entire dynamic system and consists of examining a wide bandwidth consisting of multiple modes of interest. The evaluation process is described and the advantages and disadvantages of the evaluation methods are discussed. Signal processing is used as a tool in quantifying the assessment, clearly as an improvement from the subjective heritage approach consisting primarily of engineering judgement. Data for several engines and components have been compiled and evaluated using these methods. A summary of these combustion devices is provided and observations are discussed.

Casiano, M. J.↗
NASA NTRS2019

Characterization and Application of Artificial Light Sources for Nighttime Aerosol Optical Depth Retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band

Using nighttime observations from Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals using VIIRS DNB data on a regional scale. We find that the standard deviation of instantaneous radiance for a given artificial light source is strongly dependent upon the satellite viewing angle but is weakly dependent on lunar fraction and lunar angle. Retrieval of nighttime aerosol optical thickness (AOT) based on the novel use of these artificial light sources is demonstrated for three selected regions (United States, Middle East and India) during 2015. Reason-able agreement is found between nighttime AOTs from the VIIRS DNB and temporally adjacent daytime AOTs from the AErosol RObotic NETwork (AERONET) as well as from coincident nighttime AOT retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), indicating the potential of this method to begin filling critical gaps in diurnal AOT information at both regional and global scales. Issues related to cloud, snow and ice contamination during the winter season, as well as data loss due to the misclassification of thick aerosol plumes as clouds, must be addressed to make the algorithm operationally robust.

Jianglong Zhang↗
DOE OSTI2022

Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm

The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.

D estefani, André↗
DOE OSTI2024

Systems and methods for disassembling two-dimensional van der Waals crystals into macroscopic monolayers and reassembling into artificial lattices

Systems and methods for generating one or more single crystal monolayers from two-dimensional van der Waals crystals are disclosed herein. Example methods include providing a bulk material including a plurality of van der Waals crystal layers, and exfoliating one or more single crystal monolayers of van der Waals crystal from the bulk material by applying a flexible and flat metal tape to a surface of the bulk material. In certain embodiments, the one or more single crystal monolayers can be assembled into an artificial lattice. The present disclosure also provides techniques for manufacturing flexible and flat metal tape for generating one or more single crystal monolayers from two-dimensional van der Waals crystals. The present disclosure also provides compositions for creating a macroscopic artificial lattice. In certain embodiments, the composition can include two or more macroscopic single crystal monolayers adapted from a bulk van der Waals crystal, where the single crystal monolayers are configured for assembly into an artificial lattice based on one or more properties.

Source record↗
DOE OSTI2025

Applications of explainable artificial intelligence in renewable energy research

Researchers in renewable energy are applying deep learning (DL) to a variety of problems from diverse renewable energy domains, such as biofuels, wind, solar, power systems, buildings, vehicles, and transportation systems. Improvements in accuracy may be demonstrated using DL in laboratory settings. However, the lack of interpretability of DL models poses a practical limitation to their utility in advancing scientific knowledge and in the deployment of DL models in safety-critical energy systems. In this article, we discuss explainable artificial intelligence (XAI) as one pathway toward more interpretable DL models. We explore a brief timeline of U.S. national laboratory interest in XAI, an overview and taxonomy of methods in the field of XAI, and a selection of applications across renewable energy research domains. We conclude by highlighting pivotal areas where XAI can accelerate innovation in artificial intelligence for renewable energy research and other essential future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗