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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Efficient fault diagnosis of helicopter gearboxes

Application of a diagnostic system to a helicopter gearbox is presented. The diagnostic system is a nonparametric pattern classifier that uses a multi-valued influence matrix (MVIM) as its diagnostic model and benefits from a fast learning algorithm that enables it to estimate its diagnostic model from a small number of measurement-fault data. To test this diagnostic system, vibration measurements were collected from a helicopter gearbox test stand during accelerated fatigue tests and at various fault instances. The diagnostic results indicate that the MVIM system can accurately detect and diagnose various gearbox faults so long as they are included in training.

Chin, H.↗
NASA NTRS1993

Retrieval of ice thickness from polarimetric SAR data

We describe a potential procedure for retrieving ice thickness from multi-frequency polarimetric SAR data for thin ice. This procedure includes first masking out the thicker ice types with a simple classifier and then deriving the thickness of the remaining pixels using a model-inversion technique. The technique used to derive ice thickness from polarimetric observations is provided by a numerical estimator or neural network. A three-layer perceptron implemented with the backpropagation algorithm is used in this investigation with several improved aspects for a faster convergence rate and a better accuracy of the neural network. These improvements include weight initialization, normalization of the output range, the selection of offset constant, and a heuristic learning algorithm. The performance of the neural network is demonstrated by using training data generated by a theoretical scattering model for sea ice matched to the database of interest. The training data are comprised of the polarimetric backscattering coefficients of thin ice and the corresponding input ice parameters to the scattering model. The retrieved ice thickness from the theoretical backscattering coefficients is compare with the input ice thickness to the scattering model to illustrate the accuracy of the inversion method. Results indicate that the network convergence rate and accuracy are higher when multi-frequency training sets are presented. In addition, the dominant backscattering coefficients in retrieving ice thickness are found by comparing the behavior of the network trained backscattering data at various incidence angels. After the neural network is trained with the theoretical backscattering data at various incidence anges, the interconnection weights between nodes are saved and applied to the experimental data to be investigated. In this paper, we illustrate the effectiveness of this technique using polarimetric SAR data collected by the JPL DC-8 radar over a sea ice scene.

Kwok, R.↗
NASA NTRS2000

BOREAS TE-18 Landsat TM Physical Classification Image of the SSA

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep-1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2000

BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the SSA

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2006

Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Computational tools have been developed to estimate thermal and mechanical reentry loads experienced by the Space Shuttle Orbiter as the result of cavities in the Thermal Protection System (TPS). Such cavities can be caused by impact from ice or insulating foam debris shed from the External Tank (ET) on liftoff. The reentry loads depend on cavity geometry and certain Shuttle state variables, among other factors. Certain simplifying assumptions have been made in the tool development about the cavity geometry variables. For example, the cavities are all modeled as shoeboxes , with rectangular cross-sections and planar walls. So an actual cavity is typically approximated with an idealized cavity described in terms of its length, width, and depth, as well as its entry angle, exit angle, and side angles (assumed to be the same for both sides). As part of a comprehensive assessment of the uncertainty in reentry loads estimated by the debris impact assessment tools, an effort has been initiated to quantify the component of the uncertainty that is due to imperfect geometry specifications for the debris impact cavities. The approach is to compute predicted loads for a set of geometry factor combinations sufficient to develop polynomial approximations to the complex, nonparametric underlying computational models. Such polynomial models are continuous and feature estimable, continuous derivatives, conditions that facilitate the propagation of independent variable errors. As an additional benefit, once the polynomial models have been developed, they require fewer computational resources to execute than the underlying finite element and computational fluid dynamics codes, and can generate reentry loads estimates in significantly less time. This provides a practical screening capability, in which a large number of debris impact cavities can be quickly classified either as harmless, or subject to additional analysis with the more comprehensive underlying computational tools. The polynomial models also provide useful insights into the sensitivity of reentry loads to various cavity geometry variables, and reveal complex interactions among those variables that indicate how the sensitivity of one variable depends on the level of one or more other variables. For example, the effect of cavity length on certain reentry loads depends on the depth of the cavity. Such interactions are clearly displayed in the polynomial response models.

DeLoach, R.↗
NASA NTRS1981

Earth feature identification for onboard multispectral data editing: Computational experiments

A computational model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing smart sensors which can process, edit, and classify the data that they acquire. An evaluation of sensor system performance and design tradeoffs involves classification rates and errors as a function of number and location of spectral channels, radiometric sensitivity and calibration accuracy, target discrimination assignments, and accuracy and frequency of compensation for imaging conditions. This model provides a link between the radiometric and statistical properties of the signals to be classified and the performance characteristics of electro-optical sensors and data processing devices. Preliminary computational results are presented which illustrate the editing performance of several remote sensing approaches.

Aherron, R. M.↗
NASA NTRS2001

Continuous Measurements and Quantitative Constraints: Challenge Problems for Discrete Modeling Techniques

We present some diagnosis and control problems that are difficult to solve with discrete or purely qualitative techniques. We analyze the nature of the problems, classify them and explain why they are frequently encountered in systems with closed loop control. This paper illustrates the problem with several examples drawn from industrial and aerospace applications and presents detailed information on one important application: In-Situ Resource Utilization (ISRU) on Mars. The model for an ISRU plant is analyzed showing where qualitative techniques are inadequate to identify certain failure modes and to maintain control of the system in degraded environments. We show why the solution to the problem will result in significantly more robust and reliable control systems. Finally, we illustrate requirements for a solution to the problem by means of examples.

Goodrich, Charles H.↗
NASA NTRS1995

Ultraviolet extinction to 10.8 inverse microns

UV extinction curves that represent observed variations i diffuse clouds (Zeta Oph, Xi Per, and Sigma Sco) have been derived by combining IUE and Voyager data and have been modeled by a multicomponent size distribution of silicate and carbonaceous giants. We have used theoretical model atmospheres as our reddening-free standards, and, in the case of Zeta Oph, also compare with the use of a stellar standard. An attempt was made to classify the UV spectra via theoretical spectral indices, but still missing line opacity appears to limit the use of this method at the present. The modeling includes five possible grain ingrediants, largge (0.015-0.25 micrometers) and small (0.005 micrometers) silicate grains, similarly large and small carbonaceous grains, and polycyclic aromatic hydrocarbons (PAHs). The observed extinction curves are fitted by the model via nonlinear Chi-square-minimization, varying the fractional amount of cosmic Si and C that are locked up in each igredient. The observed variation from 'steep' to 'flat' UV extinction curves is found to correspond to a modest model variation in the lower limit of the power-law size distribution of the large grains. Graphite is found to be necessary grain ingredient that cannot be replaced by the laboratory amorphous carbon materials. Carbonaceous mantles on the larger silicate grains provide no good fits to the observed curves. Using absorption properties of neutral laboratory PAHs limits PAHs to a few percent of the cosmic C abundance for acceptable fits that also give values for R(sub V) close to the observed values.

Aannestad, Per A.↗
NASA NTRS2006

Paradigm Shift in Data Content and Informatics Infrastructure Required for Generalized Constitutive Modeling of Materials Behavior

Materials property information such as composition and thermophysical/mechanical properties abound in the literature. Oftentimes, however, the corresponding response curves from which these data are determined are missing or at the very least difficult to retrieve. Further, the paradigm for collecting materials property information has historically centered on (1) properties for materials comparison/selection purposes and (2) input requirements for conventional design/analysis methods. However, just as not all materials are alike or equal, neither are all constitutive models (and thus design/ analysis methods) equal; each model typically has its own specific and often unique required materials parameters, some directly measurable and others indirectly measurable. Therefore, the type and extent of materials information routinely collected is not always sufficient to meet the current, much less future, needs of the materials modeling community. Informatics has been defined as the science concerned with gathering, manipulating, storing, retrieving, and classifying recorded information. A key aspect of informatics is its focus on understanding problems and applying information technology as needed to address those problems. The primary objective of this article is to highlight the need for a paradigm shift in materials data collection, analysis, and dissemination so as to maximize the impact on both practitioners and researchers. Our hope is to identify and articulate what constitutes "sufficient" data content (i.e., quality and quantity) for developing, characterizing, and validating sophisticated nonlinear time- and history-dependent (hereditary) constitutive models. Likewise, the informatics infrastructure required for handling the potentially massive amounts of materials data will be discussed.

Arnold, S. M.↗
NASA NTRS1976

Failure rate analysis of Goddard Space Flight Center spacecraft performance during orbital life

Space life performance data on 57 Goddard Space Flight Center spacecraft are analyzed from the standpoint of determining an appropriate reliability model and the associated reliability parameters. Data from published NASA reports, which cover the space performance of GSFC spacecraft launched in the 1960-1970 decade, form the basis of the analyses. The results of the analyses show that the time distribution of 449 malfunctions, of which 248 were classified as failures (not necessarily catastrophic), follow a reliability growth pattern that can be described with either the Duane model or a Weibull distribution. The advantages of both mathematical models are used in order to: identify space failure rates, observe chronological trends, and compare failure rates with those experienced during the prelaunch environmental tests of the flight model spacecraft.

Norris, H. P.↗
NASA NTRS1995

Shapes and stability of algebraic nuclear models

A generalization of the procedure to study shapes and stability of algebraic nuclear models introduced by Gilmore is presented. One calculates the expectation value of the Hamiltonian with respect to the coherent states of the algebraic structure of the system. Then equilibrium configurations of the resulting energy surface, which depends in general on state variables and a set of parameters, are classified through the Catastrophe theory. For one- and two-body interactions in the Hamiltonian of the interacting Boson model-1, the critical points are organized through the Cusp catastrophe. As an example, we apply this Separatrix to describe the energy surfaces associated to the Rutenium and Samarium isotopes.

Lopez-Moreno, Enrique↗
NASA NTRS2011

Magnetic Field-Line Lengths in Interplanetary Coronal Mass Ejections Inferred from Energetic Electron Events

About one quarter of the observed interplanetary coronal mass ejections (ICMEs) are characterized by enhanced magnetic fields that smoothly rotate in direction over timescales of about 10-50 hr. These ICMEs have the appearance of magnetic flux ropes and are known as "magnetic clouds" (MCs). The total lengths of MC field lines can be determined using solar energetic particles of known speeds when the solar release times and the I AU onset times of the particles are known. A recent examination of about 30 near-relativistic (NR) electron events in and near 8 MCs showed no obvious indication that the field-line lengths were longest near the MC boundaries and shortest at the MC axes or outside the MCs, contrary to the expectations for a flux rope. Here we use the impulsive beamed NR electron events observed with the Electron Proton and Alpha Monitor instrument on the Advanced Composition Explorer spacecraft and type III radio bursts observed on the Wind spacecraft to determine the field-line lengths inside ICMEs included in the catalog of Richardson & Cane. In particular, we extend this technique to ICMEs that are not MCs and compare the field-line lengths inside MCs and non-MC ICMEs with those in the ambient solar wind outside the ICMEs. No significant differences of field-line lengths are found among MCs, ICMEs, and the ambient solar wind. The estimated number of ICME field-line turns is generally smaller than those deduced for flux-rope model fits to MCs. We also find cases in which the electron injections occur in solar active regions CARs) distant from the source ARs of the ICMEs, supporting CME models that require extensive coronal magnetic reconnection with surrounding fields. The field-line lengths are found to be statistically longer for the NR electron events classified as ramps and interpreted as shock injections somewhat delayed from the type III bursts. The path lengths of the remaining spike and pulse electron events are compared with model calculations of solar wind field-line lengths resulting from turbulence and found to be in good agreement.

Kahler, S. W.↗
NASA NTRS1988

A model of the photosynthetically available and usable irradiance in the sea

A theoretical model describing the depth dependence of the solar irradiance available to phytoplankton for photosynthesis is developed for waters classified as Case I by Jerlov (1976). The techniques used to account for the effects of incident solar irradiance, pigment concentration, and the spectral diffuse attentuation coefficient are described; an expression for the photosynthetically usable irradiance is derived; and particular attention is given to the specific diffuse absorption coefficient for chlorophyll (Morel, 1978). The relationships among the primary model parameters are shown in graphs.

Collins, Donald J.↗
NASA NTRS1999

Priority in Process Algebras

This paper surveys the semantic ramifications of extending traditional process algebras with notions of priority that allow for some transitions to be given precedence over others. These enriched formalisms allow one to model system features such as interrupts, prioritized choice, or real-time behavior. Approaches to priority in process algebras can be classified according to whether the induced notion of preemption on transitions is global or local and whether priorities are static or dynamic. Early work in the area concentrated on global pre-emption and static priorities and led to formalisms for modeling interrupts and aspects of real-time, such as maximal progress, in centralized computing environments. More recent research has investigated localized notions of pre-emption in which the distribution of systems is taken into account, as well as dynamic priority approaches, i.e., those where priority values may change as systems evolve. The latter allows one to model behavioral phenomena such as scheduling algorithms and also enables the efficient encoding of real-time semantics. Technically, this paper studies the different models of priorities by presenting extensions of Milner's Calculus of Communicating Systems (CCS) with static and dynamic priority as well as with notions of global and local pre- emption. In each case the operational semantics of CCS is modified appropriately, behavioral theories based on strong and weak bisimulation are given, and related approaches for different process-algebraic settings are discussed.

Cleaveland, Rance↗
NASA NTRS2008

From Informal Safety-Critical Requirements to Property-Driven Formal Validation

Most of the efforts in formal methods have historically been devoted to comparing a design against a set of requirements. The validation of the requirements themselves, however, has often been disregarded, and it can be considered a largely open problem, which poses several challenges. The first challenge is given by the fact that requirements are often written in natural language, and may thus contain a high degree of ambiguity. Despite the progresses in Natural Language Processing techniques, the task of understanding a set of requirements cannot be automatized, and must be carried out by domain experts, who are typically not familiar with formal languages. Furthermore, in order to retain a direct connection with the informal requirements, the formalization cannot follow standard model-based approaches. The second challenge lies in the formal validation of requirements. On one hand, it is not even clear which are the correctness criteria or the high-level properties that the requirements must fulfill. On the other hand, the expressivity of the language used in the formalization may go beyond the theoretical and/or practical capacity of state-of-the-art formal verification. In order to solve these issues, we propose a new methodology that comprises of a chain of steps, each supported by a specific tool. The main steps are the following. First, the informal requirements are split into basic fragments, which are classified into categories, and dependency and generalization relationships among them are identified. Second, the fragments are modeled using a visual language such as UML. The UML diagrams are both syntactically restricted (in order to guarantee a formal semantics), and enriched with a highly controlled natural language (to allow for modeling static and temporal constraints). Third, an automatic formal analysis phase iterates over the modeled requirements, by combining several, complementary techniques: checking consistency; verifying whether the requirements entail some desirable properties; verify whether the requirements are consistent with selected scenarios; diagnosing inconsistencies by identifying inconsistent cores; identifying vacuous requirements; constructing multiple explanations by enabling the fault-tree analysis related to particular fault models; verifying whether the specification is realizable.

Cimatti, Alessandro↗
NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗
NASA NTRS1991

A two-dimensional numerical investigation of the interaction between sea breezes and deep convection over the Florida peninsula

The Colorado State University Regional Atmospheric Modeling System is used to investigate the interaction between sea breezes and deep convection over the Florida peninsula, and it is shown that this model can simulate the broad features of the three characteristic types of convection systems classified by Blanchard and Lopez (1985). In sensitivity tests performed for a variety of wind and thermodynamic profiles and for different soil-moisture contents, it was found that increases in the low-level temperature and in moisture content speeded up the development of convection. It was found that the dry-soil simulation produced rapidly developing sea breezes that moved inland quickly, while the moist soil case produced a much more slowly developing sea breeze. The total rainfall over the peninsula for the dry-soil case was greater than for the moist soil; it is suggested that the enhanced surface heat fluxes for the dry soil case create stronger low-level convergence over the peninsula (than in the moist-soil case) to force the convection.

Nicholls, Melville E.↗
NASA NTRS1994

Cognitive representations of flight-deck information attributes

A large number of aviation issues are generically being called fligh-deck information management issues, underscoring the need for an organization or classification structure. One objective of this study was to empirically determine how pilots organize flight-deck information attributes and -- based upon that data -- develop a useful taxonomy (in terms of better understanding the problems and directing solutions) for classifying flight-deck information management issues. This study also empirically determined how pilots model the importance of flight-deck information attributes for managing information. The results of this analysis suggest areas in which flight-deck researchers and designers may wish to consider focusing their efforts.

Ricks, Wendell R.↗