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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Galvanic Liquid Applied Coating System For Protection of Embedded Steel Surfaces from Corrosion

Corrosion of reinforcing steel in concrete is an insidious problem facing Kennedy Space Center (KSC), other Government Agencies, and the general public. These problems include KSC launch support structures, highway bridge infrastructure, and building structures such as condominium balconies. Due to these problems, the development of a Galvanic Liquid Applied Coating System would be a breakthrough technology having great commercial value for the following industries: Transportation, Infrastructure, Marine Infrastructure, Civil Engineering, and the Construction Industry. This sacrificial coating system consists of a paint matrix that may include metallic components, conducting agents, and moisture attractors. Similar systems have been used in the past with varying degrees of success. These systems have no proven history of effectiveness over the long term. In addition, these types of systems have had limited success overcoming the initial resistance between the concrete/coating interface. The coating developed at KSC incorporates methods proven to overcome the barriers that previous systems could not achieve. Successful development and continued optimization of this breakthrough system would produce great interest in NASA/KSC for corrosion engineering technology and problem solutions. Commercial patents on this technology would enhance KSC's ability to attract industry partners for similar corrosion control applications.

Curran, Joseph↗
NASA NTRS2002

Single and Double ITCZ in Aqua-Planet Models with Globally and Temporally Uniform Sea Surface Temperature and Solar Insolation: An Interpretation

Previous studies (Chao 2000, Chao and Chen 2001, Kirtman and Schneider 2000, Sumi 1992) have shown that, by means of one of several model design changes, the structure of the ITCZ in an aqua-planet model with globally uniform SST and solar angle (U-SST-SA) can change between a single ITCZ at the equator and a double ITCZ straddling the equator. These model design changes include switching to a different cumulus parameterization scheme (e.g., from relaxed Arakawa Schubert scheme (RAS) to moist convective adjustment scheme (MCA)), changes within the cumulus parameterization scheme, and changes in other aspects of the model, such as horizontal resolution. Sometimes only one component of the double ITCZ shows up; but still this is an ITCZ away from the equator, quite distinct from a single ITCZ over the equator. Since these model results were obtained by different investigators using different models which have yielded reasonable general circulation, they are considered as reliable. Chao and Chen (2001; hereafter CC01) have made an initial attempt to interpret these findings based on the concept of rotational ITCZ attractors that they introduced. The purpose of this paper is to offer a more complete interpretation.

Chao, Winston C.↗
NASA NTRS2003

CIZA: The First Systematic X-Ray Search for Clusters of Galaxies Behind the Milky Way

The aim of the CIZA project (Clusters In the Zone of Avoidance) was to take the first step toward a complete X-ray census of clusters of galaxies behind the plane of the Galaxy (the absolute value of b less than or equal to 20 degrees), the historical Zone of Avoidance of optical extragalactic surveys. Finding these heavily obscured clusters in ROSAT All-Sky Survey data would allow us to: 1. Construct the first truly all-sky, statistically complete, X-ray flux limited sample of galaxy clusters; 2. Use this sample to obtain an improved measurement of the cluster dipole (both amplitude and direction); 3. Chart large-scale structure across the plane of the Milky Way as traced by galaxy clusters; 4. Identify potential massive galaxy clusters contributing to the observed large-scale flow pattern in the local universe, specifically in the region around the Great Attractor; and 5. Use least-action modelling to deduce the gravitational fields created by galaxy clusters and compare this reconstruction with the one obtained from local galaxy surveys. Our project was highly successful in demonstrating the feasibility of this undertaking and allowed substantial progress toward achieving the stated science goals.

Ebeling, Harald↗
NASA NTRS2002

Factors Affecting the Latitudinal Location of the Intertropical Convergence Zone in a GCM

The dominant role of the latitudinal peak of the sea surface temperature (SST) in determining the latitudinal location of the intertropical convergence zone (ITCZ) is well-known. However, the roles of the other factors are less well-known and are the topic of this study. These other factors include the inertial stability, the interaction between convection and surface fluxes and the interaction between convection and radiation. Since these interactions involve convection, in a model they involve the cumulus parameterization scheme. These factors are studied with a general circulation model with uniform SST and solar angle. Under the aforementioned model settings, the latitudinal location of the ITCZ is the latitude where the balance of two types of attraction on the ITCZ, both due to earth's rotation, exists. Directly related to the Coriolis parameter, the first type pulls the ITCZ toward the equator and is not sensitive to model design changes. Related to the convective circulation, the second type pulls the ITCZ poleward and is sensitive to model design changes. Due to the shape and the magnitude of the attractors, the balance of the two types of attractions is reached either at the equator or more than 10 degrees away from the equator. The former case results in a single ITCZ over the equator and the latter case a double ITCZ straddling the equator.

Chao, Winston C.↗
NASA NTRS1996

Consumption, supply and transport: self-organization without direct communication

Swimming bacteria of the species Bacillus subtilis require and consume oxygen. In static liquid cultures the cells' swimming behaviour leads them to accumulate up oxygen concentration gradients generated by consumption and supply. Since the density of bacterial cells exceeds that of the fluid in which they live, fluid regions where cells have accumulated are denser than depleted regions. These density variations cause convection. The fluid motion is dynamically maintained by the swimming of the cells toward regions of attraction: the air-fluid interface and the fluctuating advecting attractors, gradients of oxygen concentration that are embedded in the convecting fluid. Because of the fluid dynamical conservation laws, these complex physical and biological factors generate patterns ordered over distances > 10000 bacterial cell diameters. The convection enhances long-range transport and mixing of oxygen, cells and extracellular products by orders of magnitude. Thus, through the interplay of physical and biological factors, a population of undifferentiated selfish cells creates functional dynamic patterns. Populations of bacteria that have organised themselves into regularly patterned regions of vigorous convection and varying cell concentration interact with their environment as if they were one purposeful, coherent multicellular individual. The mathematical and experimental ingredients of these remarkable phenomena are presented here.

Non-NASA Center↗
NASA NTRS2001

Dynamical networks with topological self-organization

Coupled evolution of state and topology of dynamical networks is introduced. Due to the well organized tensor structure, the governing equations are presented in a canonical form, and required attractors as well as their basins can be easily implanted and controlled.

neural net architecture self organizing feature ma↗
NASA NTRS2006

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Estes, Maurice G., Jr.↗
NASA NTRS2009

Complexity for Survival of Living Systems

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Zak, Michail↗
NASA NTRS2010

Turbulence and the Stabilization Principle

Further results of research, reported in several previous NASA Tech Briefs articles, were obtained on a mathematical formalism for postinstability motions of a dynamical system characterized by exponential divergences of trajectories leading to chaos (including turbulence). To recapitulate: Fictitious control forces are introduced to couple the dynamical equations with a Liouville equation that describes the evolution of the probability density of errors in initial conditions. These forces create a powerful terminal attractor in probability space that corresponds to occurrence of a target trajectory with probability one. The effect in ordinary perceived three-dimensional space is to suppress exponential divergences of neighboring trajectories without affecting the target trajectory. Con sequently, the postinstability motion is represented by a set of functions describing the evolution of such statistical quantities as expectations and higher moments, and this representation is stable. The previously reported findings are analyzed from the perspective of the authors Stabilization Principle, according to which (1) stability is recognized as an attribute of mathematical formalism rather than of underlying physics and (2) a dynamical system that appears unstable when modeled by differentiable functions only can be rendered stable by modifying the dynamical equations to incorporate intrinsic stochasticity.

Zak, Michail↗
NASA NTRS2006

NASA Tech Briefs, May 2006

T-Shaped Emitter Metal Structures for HBTs Rigorous Estimation of SNR of a PSK Communication Link Advanced Ka-Band Transceiver With Monopulse Tracking EMI Filters for Low-Temperature Applications Lightweight Electronic Camera for Research on Clouds Pilot Weather Advisor System Waveguide Power-Amplifier Module for 80 to 150 GHz Better Back Contacts for Solar Cells on Flexible Substrates Topics covered include:Tunable, Highly Stable Lasers for Coherent Lidar; Improved Photon-Emission-Microscope System; Program Synthesizes UML Sequence Diagrams; Aspect-Oriented Subprogram Synthesizes UML Sequence Diagrams; Updated Computational Model of Cosmic Rays Near Earth; Software for Alignment of Segments of a Telescope Mirror; Simulation of Dropping of Cargo With Parachutes; DAVE-ML Utility Program; Robust Control for the Mercury Laser Altimeter; Thermally Stable Piezoelectric and Pyroelectric Polymers; Combustion Synthesis of Ca3(PO4)2 Net-Shape Surgical Implants; Stochastic Representation of Chaos Using Terminal Attractors; Two High-Temperature Foil Journal Bearings; Using Plates To Represent Fillets in Finite-Element Modeling; Repairing Chipped Silicide Coatings on Refractory Metal Substrates; Simplified Fabrication of Helical Copper Antennas; Graded-Index "Whispering-Gallery" Optical Microresonators; Optical Profilometers Using Adaptive Signal Processing; Manufacture of Sparse-Spectrum Optical Microresonators; Exact Tuning of High-Q Optical Microresonators by Use of UV; Automation for "Direct-to" Clearances in Air-Traffic Control; Improved Traps for Removing Gases From Coolant Liquids; and Lunar Constellation of Frozen Elliptical Inclined Orbits.

Source record↗
NASA NTRS2003

Self-Supervised Dynamical Systems

Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and metal aspects of a monad is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. This feedback is what makes the evolution of probability densities nonlinear. The deviation from linear evolution can be characterized, in a sense, as an expression of free will. It has been demonstrated that probability densities can approach prescribed attractors while exhibiting such patterns as shock waves, solitons, and chaos in probability space. The concept of self-supervised dynamical systems has been considered for application to diverse phenomena, including information-based neural networks, cooperation, competition, deception, games, and control of chaos. In addition, a formal similarity between the mathematical structures of self-supervised dynamical systems and of quantum-mechanical systems has been investigated.

Zak, Michail↗
NASA NTRS2010

Coarse, Intermediate and High Resolution Numerical Simulations of the Transition of a Tropical Wave Critical Layer to a Tropical Storm

Recent work has hypothesized that tropical cyclones in the deep Atlantic and eastern Pacific basins develop from within the cyclonic Kelvin cat's eye of a tropical easterly wave critical layer located equatorward of the easterly jet axis. The cyclonic critical layer is thought to be important to tropical cyclogenesis because its cat's eye provides (i) a region of cyclonic vorticity and weak deformation by the resolved flow, (ii) containment of moisture entrained by the developing flow and/or lofted by deep convection therein, (iii) confinement of mesoscale vortex aggregation, (iv) a predominantly convective type of heating profile, and (v) maintenance or enhancement of the parent wave until the developing proto-vortex becomes a self-sustaining entity and emerges from the wave as a tropical depression. This genesis sequence and the overarching framework for describing how such hybrid wave-vortex structures become tropical depressions/storms is likened to the development of a marsupial infant in its mother's pouch, and for this reason has been dubbed the "marsupial paradigm". Here we conduct the first multi-scale test of the marsupial paradigm in an idealized setting by revisiting the Kurihara and Tuleya problem examining the transformation of an easterly wave-like disturbance into a tropical storm vortex using the WRF model. An analysis of the evolving winds, equivalent potential temperature, and relative vertical vorticity is presented from coarse (28 km), intermediate (9 km) and high resolution (3.1 km) simulations. The results are found to support key elements of the marsupial paradigm by demonstrating the existence of rotationally dominant region with minimal strain/shear deformation near the center of the critical layer pouch that contains strong cyclonic vorticity and high saturation fraction. This localized region within the pouch serves as the "attractor" for an upscale "bottom up" development process while the wave pouch and proto-vortex move together.

Montgomery, M. T.↗
NASA NTRS2013

Unifying Human Centered Design and Systems Engineering for Human Systems Integration

Despite the holistic approach of systems engineering (SE), systems still fail, and sometimes spectacularly. Requirements, solutions and the world constantly evolve and are very difficult to keep current. SE requires more flexibility and new approaches to SE have to be developed to include creativity as an integral part and where the functions of people and technology are appropriately allocated within our highly interconnected complex organizations. Instead of disregarding complexity because it is too difficult to handle, we should take advantage of it, discovering behavioral attractors and the emerging properties that it generates. Human-centered design (HCD) provides the creativity factor that SE lacks. It promotes modeling and simulation from the early stages of design and throughout the life cycle of a product. Unifying HCD and SE will shape appropriate human-systems integration (HSI) and produce successful systems.

Boy, Guy A.↗
NASA NTRS2015

Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

STOM attention allocation model validation↗
NASA NTRS2020

On the Use of Complexity Algorithms: a Cautionary Lesson from Climate Research

Complexity algorithms provide information about datasets which is radically different from classical moment statistics. Instead of focusing on the divergences from central values, they quantify other characteristics such as order, pattern repetitions, or the existence of attractors. However, those analyses must be done with the proper statistical treatment, which is, unfortunately, not always the case. In this contribution, I provide an example of the hazards of applying complexity measures without sufficient care by correcting a previously published analysis that aimed to quantify the complexity of climate. I clarify some misconceptions about the use of Sample Entropy and revise the incorrect assessments and conclusions drawn from the previous misapplication of the methods.

Delgado-Bonal, Alfonso↗
NASA NTRS2018

A Persistent Simulation Environment for Autonomous Systems

The age of Autonomous Unmanned Aircraft Systems (AUAS) is creating new challenges for the accreditation and certification requiring new standards, policies and procedures that sanction whether a UAS is safe to fly. Establishing a basis for certification of autonomous systems via research into trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautics Solution (CAS) project. Simulation Environments to test and evaluate AUAS decision making may be a low-cost solution to help certify that various AUAS systems are trustworthy enough to be allowed to fly in current general and commercial aviation airspace. NASA is working to build a peer-to-peer persistent simulation (P3 Sim) environment. The P3 Sim will be a Massively Multiplayer Online (MMO) environment were AUAS avatars can interact with a complex dynamic environment and each other. The focus of the effort is to provide AUAS researchers a low-cost intuitive testing environment that will aid training for and assessment of decisions made by autonomous systems such as AUAS. This presentation focuses on the design approach and challenges faced in development of the P3 Sim Environment is support of investigating trustworthiness of autonomous systems.

Kelley, Benjamin N.↗
NASA NTRSDate not supplied

Exploring Multimodal Interactions in Human-Autonomy Teaming Using a Natural User Interface

The creation of a multimodal, natural user interface to facilitate multi-agent interaction is essential to establishing trust among human and machine teammates in multi-agent systems. Trust is being researched, along with trustworthiness, as a path to certification of autonomous systems by the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project at NASA. The Autonomous Mission Experimental Logistics Interactive Assistant (AMELIA) is a natural user interface that enables multimodal interaction and is designed for rapid mission planning. AMELIA is an intelligent system that considers the user’s preferred communication strategies, as well as the time-critical aspect of the multi-agent system decision-making process. Twenty-four participants planned a multi-agent search and rescue mission, with the aid of an intelligent assistant. The results show that while the combined use of touch and speech was faster than speech alone, the single modality, touch, was still the most efficient. Future research should investigate additional input technologies.

Lisa R Le Vie↗
NASA NTRS2021

Anomaly Detection, Active Learning, Precursor Identification,and Human Knowledge for Autonomous System Safety

The project Autonomy Teaming and TRajectories for ComplexTrusted Operational Reliability (ATTRACTOR) researched and developed Artificial Intelligence with application to multi-Unmanned Aerial Systems (UAS) missions. Such missions, like other complex systems-of-systems, are likely to have previously-unknown, safety relevant anomalies occur due to many possible factors including system failures or degradations, emergent behavior, changes in the environment in which the systems operate, changes in the way the systems are operated. We discuss the application of anomaly detection, active learning, and precursor identification to identify such anomalies and the conditions under which they are more likely to appear. We demonstrate results on simulated multi-UAS missions that show promise to be applied to real missions.

machine learning↗