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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Monitoring the Microgravity Environment Quality On-board the International Space Station Using Soft Computing Techniques: Preliminary System Performance Results - Part 2

This paper presents the preliminary performance results of the artificial intelligence monitoring system in full operational mode using near real time acceleration data downlinked from the International Space Station. Preliminary microgravity environment characterization analysis result for the International Space Station (Increment-2), using the monitoring system is presented. Also, comparison between the system predicted performance based on ground test data for the US laboratory "Destiny" module and actual on-orbit performance, using measured acceleration data from the U.S. laboratory module of the International Space Station is presented. Finally, preliminary on-orbit disturbance magnitude levels are presented for the Experiment of Physics of Colloids in Space, which are compared with on ground test data. The ground test data for the Experiment of Physics of Colloids in Space were acquired from the Microgravity Emission Laboratory, located at the NASA Glenn Research Center, Cleveland, Ohio. The artificial intelligence was developed by the NASA Glenn Principal Investigator Microgravity Services Project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment of time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a dynamic graphical display, implemented in Java, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, structural modes, etc., and decide whether or not to run their experiments, whenever that is an option, based on the acceleration magnitude and frequency sensitivity associated with that experiment. This monitoring system detects primarily the vibratory disturbance sources. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗
DOE OSTI2010

Soft Computing Application in Fault Detection of Induction Motor

The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Characterizing Fractures in Geysers Geothermal Field by Micro-seismic Data, Using Soft Computing, Fractals, and Shear Wave Anisotropy

The ultimate objective of the project was to develop new methodologies to characterize the northwestern part of The Geysers geothermal reservoir (Sonoma County, California). The goal is to gain a better knowledge of the reservoir porosity, permeability, fracture size, fracture spacing, reservoir discontinuities (leaky barriers) and impermeable boundaries.

15 GEOTHERMAL ENERGY↗
NASA NTRS1999

Development of Fuzzy Logic and Soft Computing Methodologies

Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be, driven by a quest to progress from perceptions to measurements. Pursuit of this aim has led to brilliant successes. But alongside the successes stand problems whose solutions are not in sight. Representative of such problems is the problem of automation of driving in city traffic. In this case, as in many others, what can be done with ease by humans - without any measurements and a computations - is an intractable task for machines.

Zadeh, L. A.↗
NASA NTRS2001

Implementation of a General Real-Time Visual Anomaly Detection System Via Soft Computing

The intelligent visual system detects anomalies or defects in real time under normal lighting operating conditions. The application is basically a learning machine that integrates fuzzy logic (FL), artificial neural network (ANN), and generic algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation to separate the object being tested from the background, preprocesses the image using fuzzy reasoning, performs the final segmentation using fuzzy reasoning techniques to retrieve regions with potential anomalies or defects, and finally retrieves them using a learning model built via ANN and GA techniques. FL provides a powerful framework for knowledge representation and overcomes uncertainty and vagueness typically found in image analysis. ANN provides learning capabilities, and GA leads to robust learning results. An application prototype currently runs on a regular PC under Windows NT, and preliminary work has been performed to build an embedded version with multiple image processors. The application prototype is being tested at the Kennedy Space Center (KSC), Florida, to visually detect anomalies along slide basket cables utilized by the astronauts to evacuate the NASA Shuttle launch pad in an emergency. The potential applications of this anomaly detection system in an open environment are quite wide. Another current, potentially viable application at NASA is in detecting anomalies of the NASA Space Shuttle Orbiter's radiator panels.

Dominguez, Jesus A.↗
NASA NTRS2001

Determining flexor-tendon repair techniques via soft computing

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

Therapy, Computer-Assisted/methods↗
NASA NTRS2005

Training Software in Artificial-Intelligence Computing Techniques

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Howard, Ayanna↗
DOE OSTI2016

Mutual capacitance of liquid conductors in deformable tactile sensing arrays

Advances in highly deformable electronics are needed in order to enable emerging categories of soft computing devices ranging from wearable electronics, to medical devices, and soft robotic components. The combination of highly elastic substrates with intrinsically stretchable conductors holds the promise of enabling electronic sensors that can conform to curved objects, reconfigurable displays, or soft biological tissues, including the skin. Here, we contribute sensing principles for tactile (mechanical image) sensors based on very low modulus polymer substrates with embedded liquid metal microfluidic arrays. The sensors are fabricated using a single-step casting method that utilizes fine nylon filaments to produce arrays of cylindrical channels on two layers. The liquid metal (gallium indium alloy) conductors that fill these channels readily adopt the shape of the embedding membrane, yielding levels of deformability greater than 400%, due to the use of soft polymer substrates. We modeled the sensor performance using electrostatic theory and continuum mechanics, yielding excellent agreement with experiments. Using a matrix-addressed capacitance measurement technique, we are able to resolve strain distributions with millimeter resolution over areas of several square centimeters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Advanced control strategies for heating, ventilation, air-conditioning, and refrigeration systems—An overview: Part I: Hard control

A chronological overview of the advanced control strategies for heating, ventilation, air-conditioning, and refrigeration (HVAC&R) is presented in this article. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and on the fusion or hybrid of hard- and soft-control techniques. Thus, it is to be noted that the terminology “hard” and “soft” computing/control has nothing to do with the “hardware” and “software” that is being generally used. Part I of a two-part series focuses on hard-control strategies, and Part II focuses on softand fusion-control in addition to some future directions in HVAC&R research. This overview is not intended to be an exhaustive survey on this topic, and any omission of other works is purely unintentional.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1979

Simulation of cosmic-ray induced soft errors and latchup in integrated-circuit computer memories

Soft errors have been induced in solid-state static RAM's by iron nuclei from the Lawrence Berkeley Laboratory (LBL) Bevalac, in experiments designed to prove the ability of iron-group cosmic rays to generate such errors. Subsequently, various delidded device types were tested in beams of argon and krypton ions from the LBL 88-inch Cyclotron, at energies near 2 MeV/nucleon. The latter tests showed that some devices are essentially immune to bit error while others are quite susceptible. Good agreement was obtained with model predictions in cases where the latter exist. Latchup, whose cause is attributed to individual heavy ions, was also observed in some device types.

Kolasinski, W. A.↗
DOE OSTI2013

DETERMINING HEATING RATES IN RECONNECTION FORMED FLARE LOOPS OF THE M8.0 FLARE ON 2005 MAY 13

We analyze and model an M8.0 flare on 2005 May 13 observed by the Transition Region and Coronal Explorer and the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) to determine the energy release rate from magnetic reconnection that forms and heats numerous flare loops. The flare exhibits two ribbons in UV 1600 A emission. Analysis shows that the UV light curve at each flaring pixel rises impulsively within a few minutes, and decays slowly with a timescale longer than 10 minutes. Since the lower atmosphere (the transition region and chromosphere) responds to energy deposit nearly instantaneously, the rapid UV brightening is thought to reflect the energy release process in the newly formed flare loop rooted at the footpoint. In this paper, we utilize the spatially resolved (down to 1'') UV light curves and the thick-target hard X-ray emission to construct heating functions of a few thousand flare loops anchored at the UV footpoints, and compute plasma evolution in these loops using the enthalpy-based thermal evolution of loops model. The modeled coronal temperatures and densities of these flare loops are then used to calculate coronal radiation. The computed soft X-ray spectra and light curves compare favorably with those observed by RHESSI and by the Geostationary Operational Environmental Satellite X-ray Sensor. The time-dependent transition region differential emission measure for each loop during its decay phase is also computed with a simplified model and used to calculate the optically thin C IV line emission, which dominates the UV 1600 A bandpass during the flare. The computed C IV line emission decays at the same rate as observed. This study presents a method to constrain heating of reconnection-formed flare loops using all available observables independently, and provides insight into the physics of energy release and plasma heating during the flare. With this method, the lower limit of the total energy used to heat the flare loops in this event is estimated to be 1.22 Multiplication-Sign 10{sup 31} erg, of which only 1.9 Multiplication-Sign 10{sup 30} erg is carried by beam-driven upflows during the impulsive phase, suggesting that the coronal plasmas are predominantly heated in situ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Geometrically frustrated interactions drive structural complexity in amorphous calcium carbonate

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca∙∙∙Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca 2+ -ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca 2+ ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Examining the role of fluctuations in the early stages of homogenous polymer crystallization with simulation and statistical learning

Here, we propose a relationship between the dynamics in the amorphous and crystalline domains during polymer crystallization: the fluctuations of ordering-rate about a material-specific value in the amorphous phase drive those fluctuations associated with the increase in percent crystallinity. This suggests a differential equation that satisfies the three experimentally observed time regimes for the rate of crystal growth. To test this postulated expression, we applied a suite of statistical learning tools to molecular dynamics simulations to extract the relevant phenomenology. This study shows that the proposed relationship holds in the early time regime. It illustrates the effectiveness of soft computing tools in the analysis of coarse-grained simulations in which patterns exist, but may not easily yield to strict quantitative evaluation. This ability assists us in characterizing the critical early time molecular arrangement during the primary nucleation phase of polymer melt crystallization. In addition to supporting the validity of the proposed kinetics expression, the simulations show that (i) the classical nucleation and growth mechanism is active in the early stages of ordering; (ii) the number of nuclei and their masses grow linearly during this early time regime; and (iii) a fixed inter-nuclei distance is established.

36 MATERIALS SCIENCE↗
NASA NTRS1998

[Research on the Application of Fuzzy Logic to Systems Analysis and Control]

Research conducted with the support of NASA Grant NCC2-275 has been focused in the main on the development of fuzzy logic and soft computing methodologies and their applications to systems analysis and control. with emphasis 011 problem areas which are of relevance to NASA's missions. One of the principal results of our research has been the development of a new methodology called Computing with Words (CW). Basically, in CW words drawn from a natural language are employed in place of numbers for computing and reasoning. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW.

Source record↗