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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Automated Environment Generation for Software Model Checking

A key problem in model checking open systems is environment modeling (i.e., representing the behavior of the execution context of the system under analysis). Software systems are fundamentally open since their behavior is dependent on patterns of invocation of system components and values defined outside the system but referenced within the system. Whether reasoning about the behavior of whole programs or about program components, an abstract model of the environment can be essential in enabling sufficiently precise yet tractable verification. In this paper, we describe an approach to generating environments of Java program fragments. This approach integrates formally specified assumptions about environment behavior with sound abstractions of environment implementations to form a model of the environment. The approach is implemented in the Bandera Environment Generator (BEG) which we describe along with our experience using BEG to reason about properties of several non-trivial concurrent Java programs.

Tkachuk, Oksana↗
NASA NTRS1983

Post instability in continuous systems. II - Post-instability models of continua

New models simulating postinstability behavior of continuous systems are discussed. Multivalued velocity fields of the motion of a medium are analyzed, deriving concepts which are applied to a new model of turbulence. Postinstability models of solids are examined, emphasizing the multivaluedness of the parameters. The consequences are addressed of the simplifying assumption that in solids the rate of dissipation of energy of the pulsations is much higher than in fluids. The principal stress formulation of postinstability models is considered, including the geometry, kinematics, and dynamics of the principal stress coordinates. The fundamental properties of enlarged models of a solid are illustrated by the theory of wrinkling films. Results are presented for the statics of such films, the effects of shocks and shock waves, and the behavior of singular effects and singular thick wrinkles.

Zak, M.↗
NASA NTRS1986

Nonlinear system controller design based on domain of attaction: An application to CELSS analysis and control

Nonlinear system controller design based on the domain of attraction is presented. This is particularly suited to investigating Closed Ecological Life Support Systems (CELSS) models. In particular, the dynamic consequences of changes in the waste storage capacity and system mass, and how information is used for control in CELSS models are examined. The models' high dimensionality and nonlinear state equations make them difficult to analyze by any other technique. The domain of attraction is the region in initial conditions that tend toward an attractor and it is delineated by randomly selecting initial conditions from the region of state space being investigated. Error analysis is done by repeating the domain simulations with independent samples. A refinement of this region is the domain of performance which is the region of initial conditions meeting a performance criteria. In nonlinear systems, local stability does not insure stability over a larger region. The domain of attraction marks out this stability region; hence, it can be considered a measure of a nonlinear system's ability to recovery from state perturbations. Considering random perturbations, the minimum radius of the domain is a measure of the magnitude of perturbations for which recovery is guaranteed. Design of both linear and nonlinear controllers are shown. Three CELSS models, with 9 to 30 state variable, are presented. Measures of the domain of attraction are used to show the global behavior of these models under a variety of design and controller scenarios.

Babcock, P. S., IV↗
NASA NTRS1994

General analytic results for nonlinear waves and solitons in molecular clouds

We study nonlinear wave phenomena in self-gravitating fluid systems, with a particular emphasis on applications to molecular clouds. This paper presents analytical results for one spatial dimension. We show that a large class of physical systems can be described by theories with a 'charge density' q(rho); this quantity replaces the density on the right-hand side of the Poisson equation for the gravitational potential. We use this formulation to prove general results about nonlinear wave motions in self-gravitating systems. We show that in order for stationary waves to exist, the total charge (the integral of the charge density over the wave profile) must vanish. This 'no-charge' property for solitary waves is related to the capability of a system to be stable to gravitational perturbations for arbitrarily long wavelengths. We find necessary and sufficient conditions on the charge density for the existence of solitary waves and stationary waves. We study nonlinear wave motions for Jeans-type theories (where q(rho) = rho-rho(sub 0)) and find that nonlinear waves of large amplitude are confined to a rather narrow range of wavelengths. We also study wave motions for molecular clouds threaded by magnetic fields and show how the allowed range of wavelengths is affected by the field strength. Since the gravitational force in one spatial dimension does not fall off with distance, we consider two classes of models with more realistic gravity: Yukawa potentials and a pseudo two-dimensional treatment. We study the allowed types of wave behavior for these models. Finally, we discuss the implications of this work for molecular cloud structure. We argue that molecular clouds can support a wide variety of wave motions and suggest that stationary waves (such as those considered in this paper) may have already been observed.

Adams, Fred C.↗
NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗
NASA NTRS2015

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

Variability↗
NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗
NASA NTRS2017

Parametric Failures in COTS Capacitors

Insertion of COTS components into hi-rel systems require extensive environmental testing of the parts that often results in parametric failures. Based on experience with commercial and hi-rel PME and BME ceramic capacitors and polymer and MnO2 cathode tantalum capacitors, this presentation discusses two major reasons for parametric failures. One is due to the marketing pressure that forces manufacturers to squeeze performance of COTS components thus leaving insufficient margin between the rated and actual characteristics. Another, and probably a more serious reason is degradation of characteristics caused by physico-chemical processes in materials under environmental stresses. Reliability assessment requires development of models to predict behavior of the parts during applications based on accelerated testing that might be outside the specified conditions and target applications. Examples of models developed to simulate and predict wear-out failures are presented. Risks associated with overstressing during HALT are discussed.

Teverovsky, Alexander↗
NASA NTRS2018

Magnetosphere Dynamics During the 14 November 2012 Storm Inferred from TWINS, AMPERE, Van Allen Probes, and BATS-R-US-CRCM

During the 14 November 2012 geomagnetic storm, the Van Allen Probes spacecraft observed a number of sharp decreases ('dropouts') in particle fluxes for ions and electrons of different energies. In this paper, we investigate the global magnetosphere dynamics and magnetosphere- ionosphere (M-I) coupling during the dropout events using multipoint measurements by Van Allen Probes, TWINS, and AMPERE together with the output of the two-way coupled global BATS-R-US-CRCM model. We find different behavior for two pairs of dropouts. For one pair, the same pattern was repeated: (1) weak nightside Region 1 and 2 Birkeland currents before and during the dropout; (2) intensification of Region 2 currents after the dropout; and (3) a particle injection detected by TWINS after the dropout. The model predicted similar behavior of Birkeland currents. TWINS low-altitude emissions demonstrated high variability during these intervals, indicating high geomagnetic activity in the near-Earth tail region. For the second pair of dropouts, the structure of both Birkeland currents and ENA emissions was relatively stable. The model also showed quasi-stationary behavior of Birkeland currents and simulated ENA emissions with gradual ring current buildup. We confirm that the first pair of dropouts was caused by large-scale motions of the OCB (open-closed boundary) during substorm activity. We show the new result that this OCB motion was associated with global changes in Birkeland (M-I coupling) currents and strong modulation of low-altitude ion precipitation. The second pair of dropouts is the result of smaller OCB disturbances not related to magnetospheric substorms. The local observations of the first pair of dropouts result from a global magnetospheric reconfiguration, which is manifested by ion injections and enhanced ion precipitation detected by TWINS and changes in the structure of Birkeland currents detected by AMPERE. This study demonstrates that multipoint measurements along with the global model results enable the reconstruction of a more complete system-level picture of the dropout events and provides insight into M-I coupling aspects that have not previously been investigated.

Buzulukova, Natalia↗
NASA NTRS2000

Structural Similitude and Scaling Laws for Plates and Shells: A Review

This paper deals with the development and use of scaled-down models in order to predict the structural behavior of large prototypes. The concept is fully described and examples are presented which demonstrate its applicability to beam-plates, plates and cylindrical shells of laminated construction. The concept is based on the use of field equations, which govern the response behavior of both the small model as well as the large prototype. The conditions under which the experimental data of a small model can be used to predict the behavior of a large prototype are called scaling laws or similarity conditions and the term that best describes the process is structural similitude. Moreover, since the term scaling is used to describe the effect of size on strength characteristics of materials, a discussion is included which should clarify the difference between "scaling law" and "size effect". Finally, a historical review of all published work in the broad area of structural similitude is presented for completeness.

Simitses, G. J.↗
NASA NTRS1979

Monitoring and decision making by people in man machine systems

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Johannsen, G.↗
NASA NTRS1984

Utilization of Historic Information in an Optimisation Task

One of the basic components of a discrete model of motor behavior and decision making, which describes tracking and supervisory control in unitary terms, is assumed to be a filtering mechanism which is tied to the representational principles of human memory for time-series information. In a series of experiments subjects used the time-series information with certain significant limitations: there is a range-effect; asymmetric distributions seem to be recognized, but it does not seem to be possible to optimize performance based on skewed distributions. Thus there is a transformation of the displayed data between the perceptual system and representation in memory involving a loss of information. This rules out a number of representational principles for time-series information in memory and fits very well into the framework of a comprehensive discrete model for control of complex systems, modelling continuous control (tracking), discrete responses, supervisory behavior and learning.

Boesser, T.↗
NASA NTRS1974

The nature of the residual Martian polar caps

A model of the behavior of the Martian polar caps is described which incorporates the heating effects of the atmosphere, as well as insolation and conduction. This model is used to try to match the observed regression curves of the polar caps, and it predicts that all the seasonally condensed CO2 will be lost by around the summer solstice. The implication is that the residual caps are composed of water ice which, it is found by further modeling, should be stable during the Martian summers. However, it is also argued that this model may be too simplistic, and that the effects of wind in redistributing the seasonal condensate may lead to sufficient thicknesses of CO2 in the central polar region to allow the year-long existence of CO2 without significantly changing the retreat characteristics of the cap, and it is, therefore, concluded that at the present, the nature of the residual caps cannot be reliably determined.

Briggs, G. A.↗
NASA NTRS1991

Markov reward processes

Numerous applications in the area of computer system analysis can be effectively studied with Markov reward models. These models describe the behavior of the system with a continuous-time Markov chain, where a reward rate is associated with each state. In a reliability/availability model, upstates may have reward rate 1 and down states may have reward rate zero associated with them. In a queueing model, the number of jobs of certain type in a given state may be the reward rate attached to that state. In a combined model of performance and reliability, the reward rate of a state may be the computational capacity, or a related performance measure. Expected steady-state reward rate and expected instantaneous reward rate are clearly useful measures of the Markov reward model. More generally, the distribution of accumulated reward or time-averaged reward over a finite time interval may be determined from the solution of the Markov reward model. This information is of great practical significance in situations where the workload can be well characterized (deterministically, or by continuous functions e.g., distributions). The design process in the development of a computer system is an expensive and long term endeavor. For aerospace applications the reliability of the computer system is essential, as is the ability to complete critical workloads in a well defined real time interval. Consequently, effective modeling of such systems must take into account both performance and reliability. This fact motivates our use of Markov reward models to aid in the development and evaluation of fault tolerant computer systems.

Smith, R. M.↗
NASA NTRS2004

Core Formation in the Earth: Constraints from Ni and Co

Due to their metal-loving nature, Ni and Co were strongly partitioned into the metallic core and were left depleted in the silicate mantle during core formation in the Earth. Based on experimental liquid metal- liquid silicate partition coefficients (D), studies have suggested that core formation in an early magma Ocean can explain the observed mantle depletions of Ni and Co [l-51. However, the conditions proposed by the magma ocean models have ranged from pressures of 24 to 59 GPa and temperatures of 2200 to < 4000 K. Furthermore, the proposed magma Ocean oxygen fugacities have differed by nearly two orders of magnitude.Chabot and Agee noted that the different models predicted contradictory behaviors for D(Ni) and D(Co) as a function of temperature. With the hope of resolving the discrepancies between the magma ocean models, we conducted a systematic experimental study to constrain the effects of temperature on D(Ni) and D(Co).

Chabot, N. L.↗
NASA NTRS1948

Ditching Tests of a 1/18-Scale Model of the Lockheed Constellation Airplane

Tests were made of a 1/18-scale dynamically similar model of the Lockheed Constellation airplane to investigate its ditching characteristics and proper ditching technique. Scale-strength bottoms were used to reproduce probable damage to the fuselage. The model was landed in calm water at the Langley tank no. 2 monorail. Various landing attitudes, speeds, and fuselage configuration were simulated. The behavior of the model was determined from visual observations, by recording the longitudinal decelerations, and by taking motion pictures of the ditchings. Data are presented in tabular form, sequence photographs, and time-history deceleration curves. It was concluded that the airplane should be ditched at a medium nose-high landing attitude with the landing flaps full down. The airplane will probably make a deep run with heavy spray and may even dive slightly. The fuselage will be damaged and leak substantially but in calm water probably will not flood rapidly. Maximum longitudinal decelerations in a calm-water ditching will be about 4g.

Fisher, Lloyd J.↗
NASA NTRS2012

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Hutto, Clayton↗