SEARCH · Engineering Papers

Results for “temporal”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS1986

Temporal sensitivity

Human visual temporal sensitivity is examined. The stimuli used to measure temporal sensitivity are described and the linear systems theory is reviewed in terms of temporal sensitivity. A working model which represents temporal sensitivity is proposed. The visibility of a number of temporal wave forms, sinusoids, rectangular pulses, and pulse pairs, is analyzed. The relation between spatial and temporal effects is studied. Temporal variations induced by image motion and the effects of light adaptation on temporal sensitivity are considered.

Watson, Andrew B.↗

NASA NTRS2002

Properties of the Residual Stress of the Temporally Filtered Navier-Stokes Equations

The development of a unifying framework among direct numerical simulations, large-eddy simulations, and statistically averaged formulations of the Navier-Stokes equations, is of current interest. Toward that goal, the properties of the residual (subgrid-scale) stress of the temporally filtered Navier-Stokes equations are carefully examined. Causal time-domain filters, parameterized by a temporal filter width 0 less than Delta less than infinity, are considered. For several reasons, the differential forms of such filters are preferred to their corresponding integral forms; among these, storage requirements for differential forms are typically much less than for integral forms and, for some filters, are independent of Delta. The behavior of the residual stress in the limits of both vanishing and in infinite filter widths is examined. It is shown analytically that, in the limit Delta to 0, the residual stress vanishes, in which case the Navier-Stokes equations are recovered from the temporally filtered equations. Alternately, in the limit Delta to infinity, the residual stress is equivalent to the long-time averaged stress, and the Reynolds-averaged Navier-Stokes equations are recovered from the temporally filtered equations. The predicted behavior at the asymptotic limits of filter width is further validated by numerical simulations of the temporally filtered forced, viscous Burger's equation. Finally, finite filter widths are also considered, and a priori analyses of temporal similarity and temporal approximate deconvolution models of the residual stress are conducted.

Pruett, C. D.↗

NASA NTRS2018

Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation

Recently, the makespan-minimization problem of compiling a general class of quantum algorithms into near-term quantum processors has been introduced to the AI community. The research demonstrated that temporal planning is a strong solution approach for the studied class of quantum circuit compilation (QCC) problems. In this paper, we explore the use of methods from operations research, specifically constraint programming (CP), as an alternative and complementary approach to temporal planning. We also extend previous work by introducing two new problem variations that incorporate important characteristics identified by the quantum computing community. We apply temporal planning and CP to the baseline and extended QCC problems as both stand-alone and hybrid approaches. The hybrid method uses solutions found by temporal planning to warm-start CP, leveraging the ability of temporal planning to find satisficing solutions to problems with a high degree of task optionality, an area that CP typically struggles with. These solutions are then used to seed the CP formulation which significantly benefits from inferred bounds on planning horizon and task counts provided by the warm-start. Our extensive empirical evaluation indicates that while stand-alone CP is not competitive with temporal planning, except for the smallest problems, CP in a hybrid setting is beneficial for all temporal planners in all problem classes.

quantum circuit compilation↗

NASA NTRS1983

The use of LANDSAT-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on LANDSAT 4 is, in certain performance aspects, different from those on LANDSATS 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of LANDSAT 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using LANDSAT 4 and LANDSAT 2 data (33.35 meters) and the temporal data set constructed from two LANDSAT 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗

NASA NTRS1985

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗

NASA NTRS1992

Incorporation of varying types of temporal data in a neural network

Most neural network models do not specifically deal with temporal data. Handling of these variables is complicated by the different uses to which temporal data are put, depending on the application. Even within the same application, temporal variables are often used in a number of different ways. In this paper, types of temporal data are discussed, along with their implications for approximate reasoning. Methods for integrating approximate temporal reasoning into existing neural network structures are presented. These methods are illustrated in a medical application for diagnosis of graft-versus-host disease which requires the use of several types of temporal data.

Cohen, M. E.↗

NASA NTRS1995

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗

NASA NTRS1996

Theory and ontology for sharing temporal knowledge

Using current technology, the sharing or re-using of knowledge-bases is very difficult, if not impossible. ARPA has correctly recognized the problem and funded a knowledge sharing initiative. One of the outcomes of this project is a formal language called Knowledge Interchange Format (KIF) for representing knowledge that could be translated into other languages. Capturing and representing design knowledge and reasoning with them have become very important for NASA who is a pioneer of innovative design of unique products. For upgrading an existing design for changing technology, needs, or requirements, it is essential to understand the design rationale, design choices, options and other relevant information associated with the design. Capturing such information and presenting them in the appropriate form are part of the ongoing Design Knowledge Capture project of NASA. The behavior of an object and various other aspects related to time are captured by the appropriate temporal knowledge. The captured design knowledge will be represented in such a way that various groups of NASA who are interested in various aspects of the design cycle should be able to access and use the design knowledge effectively. To facilitate knowledge sharing among these groups, one has to develop a very well defined ontology. Ontology is a specification of conceptualization. In the literature several specific domains were studied and some well defined ontologies were developed for such domains. However, very little, or no work has been done in the area of representing temporal knowledge to facilitate sharing. During the ASEE summer program, I have investigated several temporal models and have proposed a theory for time that is flexible to accommodate the time elements, such as, points and intervals, and is capable of handling the qualitative and quantitative temporal constraints. I have also proposed a primitive temporal ontology using which other relevant temporal ontologies can be built. I have investigated various issues of sharing knowledge and have proposed a formal framework for modeling the concept of knowledge sharing. This work may be implemented and tested in the software environment supplied by Knowledge Based System, Inc.

Loganantharaj, Rasiah↗

NASA NTRSDate not supplied

Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow

Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the trade-offs to spatial, spectral and temporal resolutions of observations. In weather tracking, high-frequency temporal observations are critical and used to improve forecasts, study severe events, and extract atmospheric motion, among others. However, while the current generation of geostationary satellites have hemispheric coverage at 10-15 minute intervals, higher temporal frequency observations are ideal for studying mesoscale severe weather events. In this work, we apply a task specific optical flow approach to temporal up-sampling using deep convolutional neural networks. We apply this technique to 16-bands of GOES-R/Advanced Baseline Imager mesoscale dataset to temporally enhance full disk hemispheric snapshots of different spatial resolutions from 15 minutes to 1 minute. Experiments show the effectiveness of task specific optical flow and multi-scale blocks for interpolating high-frequency severe weather events relative to bilinear and global optical flow baselines. Lastly, we demonstrate strong performance in capturing variability during convective precipitation events.

Optical flow, temporal interpolation, geostationar↗

NASA NTRSDate not supplied

Seeing is Believing: Monitoring Future Time Temporal Logic

Runtime monitors for future-time unbounded temporal logics like RVLTL, LTL 3 and FLTL, have double-exponential (2^2^n) worst-case space complexity bounds in size of the input formula. The semantics of these logics require monitors to perform general satisfiability solving for LTL expressions, a well-studied problem whose computational complexity is NP-hard and PSPACE-complete. This paper introduces an unbounded future-time linear temporal logic defined over a lattice. We call our logic an incremental temporal logic as it can be viewed as incrementally constructing proofs about the trace. On this account, we view online runtime monitoring as a decision procedure for proofs systems about incrementally growing traces. We demonstrate that our incremental temporal logic allows monitor construction to void satisfiability solving while still soundly detecting when the property is violated in an online fashion. This enables asymptotic improvements in space complexity. As proof, we provide a procedure to construct monitors that utilize linear space and time in the size of the input formula, while remaining constant in the size of the input stream and suitable for online monitoring. We further demonstrate, through several examples, that our incremental temporal logic is straightforward to adopt and practical for runtime verification.

temporal logic↗

NASA NTRS1987

The mechanisms of temporal inference

The properties of a temporal language are determined by its constituent elements: the temporal objects which it can represent, the attributes of those objects, the relationships between them, the axioms which define the default relationships, and the rules which define the statements that can be formulated. The methods of inference which can be applied to a temporal language are derived in part from a small number of axioms which define the meaning of equality and order and how those relationships can be propagated. More complex inferences involve detailed analysis of the stated relationships. Perhaps the most challenging area of temporal inference is reasoning over disjunctive temporal constraints. Simple forms of disjunction do not sufficiently increase the expressive power of a language while unrestricted use of disjunction makes the analysis NP-hard. In many cases a set of disjunctive constraints can be converted to disjunctive normal form and familiar methods of inference can be applied to the conjunctive sub-expressions. This process itself is NP-hard but it is made more tractable by careful expansion of a tree-structured search space.

Fox, B. R.↗

NASA NTRS1991

Spatio-temporal contextual classification based on Markov random field model

A contextural classifier based on a Markov random field model, which can utilize both spatial and temporal contexts, is investigated. Spatial and temporal neighbors are defined, and the class assignment of each pixel is assumed to be dependent only on the measurement vectors of itself and those of its spatial and temporal neighbors according to the Markov random field property. Only interpixel class dependency context is used in the classification. The joint prior probability of the classes of each pixel and its spatial and temporal neighbors are modeled by a Gibbs random field. The classification is performed in a recursive manner. Experiments with multi-temporal Thematic Mapper data show promising results.

Jeon, Byeungwoo↗

NASA NTRS2001

General Temporal Knowledge for Planning and Data Mining

We consider the architecture of systems that combine temporal planning and plan execution and introduce a layer of temporal reasoning that potential1y improves both the communication between humans and such systems, and the performance of the temporal planner itself. In particular, this additional layer simultaneously supports more flexibility in specifying and maintaining temporal constraints on plans within an uncertain and changing execution environment, and the ability to understand and trace the progress of plan execution. It is shown how a representation based on single set of abstractions of temporal information can be used to characterize the reasoning underlying plan generation and execution interpretation. The complexity of such reasoning is discussed.

Morris, Robert↗

NASA NTRS1997

Calibration of a Spatial-Temporal Discrimination Model from Forward, Simultaneous, and Backward Masking

We have been developing a simplified spatial-temporal discrimination model similar to our simplified spatial model in that masking is assumed to be a function of the local visible contrast energy. The overall spatial-temporal sensitivity of the model is calibrated to predict the detectability of targets on a uniform background. To calibrate the spatial-temporal integration functions that define local visible contrast energy, spatial-temporal masking data are required. Observer thresholds were measured (2IFC) for the detection of a 12 msec target stimulus in the presence of a 700 msec mask. Targets were 1, 3 or 9 c/deg sine wave gratings. Masks were either one of these gratings or two of them combined. The target was presented in 17 temporal positions with respect to the mask, including positions before, during and after the mask. Peak masking was found near mask onset and offset for 1 and 3 c/deg targets, while masking effects were more nearly uniform during the mask for the 9 c/deg target. As in the purely spatial case, the simplified model can not predict all the details of masking as a function of masking component spatial frequencies, but overall the prediction errors are small.

Ahumada, Albert J.↗

NASA NTRS2005

Constraint-based Temporal Reasoning with Preferences

Often we need to work in scenarios where events happen over time and preferences are associated to event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems require exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solvable. In this paper we identify one of such subclasses giving tractability results. Moreover, we describe two solvers for this class of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and robustness. Sometimes, however, temporal local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preferences, we show that machine learning techniques can be useful in this respect. In particular, we present a learning module based on a gradient descent technique which induces local temporal preferences from global ones. We also show the behavior of the learning module on randomly-generated examples.

Khatib, Lina↗

NASA NTRS2006

A Structural Characterization of Temporal Dynamic Controllability

An important issue for temporal planners is the ability to handle temporal uncertainty. Recent papers have addressed the question of how to tell whether a temporal network is Dynamically Controllable, i.e., whether the temporal requirements are feasible in the light of uncertain durations of some processes. Previous work has presented an O(N5) algorithm for testing this property. Here, we introduce a new analysis of temporal cycles that leads to an O(N4) algorithm.

Morris, Paul↗

NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

NASA NTRS2019

New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process.

Tuli, Fatima Tuz Zafrin↗