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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Airborne Measurements of Western U.S. Wildfire Emissions: Comparison with Prescribed Burning and Air Quality Implications

Wildfires emit significant amounts of pollutants that degrade air quality. Plumes from three wildfires in the western U.S. were measured from aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), both in summer 2013. This study reports an extensive set of emission factors (EFs) for over 80 gases and 5 components of submicron particulate matter (PM1) from these temperate wildfires. These include rarely, or never before, measured oxygenated volatile organic compounds and multifunctional organic nitrates. The observed EFs are compared with previous measurements of temperate wildfires, boreal forest fires, and temperate prescribed fires. The wildfires emitted high amounts of PM1 (with organic aerosol (OA) dominating the mass) with an average EF that is more than 2 times the EFs for prescribed fires. The measured EFs were used to estimate the annual wildfire emissions of carbon monoxide, nitrogen oxides, total non methane organic compounds, and PM1 from 11 western U.S. states. The estimated gas emissions are generally comparable with the 2011 National Emissions Inventory (NEI). However, our PM1 emission estimate (1530 +/- 570 Gg/yr) is over 3 times that of the NEI PM2.5 estimate and is also higher than the PM2.5 emitted from all other sources in these states in the NEI. This study indicates that the source of OA from biomass burning in the western states is significantly underestimated. In addition, our results indicate that prescribed burning may be an effective method to reduce fine particle emissions.

measured oxygenated volatile organic compounds↗
NASA NTRS1975

The LANDSAT-1 multispectral scanner as a tool in the classification of inland lakes

Relationships between LANDSAT-1 multispectral scanner (MSS) data and the trophic status of a group of lakes in the north-northeastern part of the United States were studied by predicting the magnitudes of two trophic state indicators, estimating lake position on a multivariate trophic scale, and automatically classifying lakes according to their trophic state. Initially, the principal component ordination was employed with 100 lakes. MSS data for some 20 lakes was then extracted from computer-compatible tapes (CCT) using a binary marking technique. The output was in the form of descriptive statistics and photographic concatenations. Color ratios were incorporated into regression models for the prediction of Secchi disc transparency, chlorophyll a, and lake position on the tropic scale. Results indicate that the LANDSAT-1 system, although handicapped by low spectral and spatial resolutions as well as excessive cloud cover, can be used as a supplemental data source in lake survey programs.

Boland, D. H. P.↗
NASA NTRS1993

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗
NASA NTRS1995

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗
NASA NTRS1996

Satellite Angular Rate Estimation From Vector Measurements

This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

Azor, Ruth↗
NASA NTRS1992

Performance and state-space analyses of systems using Petri nets

The goal of any modeling methodology is to develop a mathematical description of a system that is accurate in its representation and also permits analysis of structural and/or performance properties. Inherently, trade-offs exist between the level detail in the model and the ease with which analysis can be performed. Petri nets (PN's), a highly graphical modeling methodology for Discrete Event Dynamic Systems, permit representation of shared resources, finite capacities, conflict, synchronization, concurrency, and timing between state changes. By restricting the state transition time delays to the family of exponential density functions, Markov chain analysis of performance problems is possible. One major drawback of PN's is the tendency for the state-space to grow rapidly (exponential complexity) compared to increases in the PN constructs. It is the state space, or the Markov chain obtained from it, that is needed in the solution of many problems. The theory of state-space size estimation for PN's is introduced. The problem of state-space size estimation is defined, its complexities are examined, and estimation algorithms are developed. Both top-down and bottom-up approaches are pursued, and the advantages and disadvantages of each are described. Additionally, the author's research in non-exponential transition modeling for PN's is discussed. An algorithm for approximating non-exponential transitions is developed. Since only basic PN constructs are used in the approximation, theory already developed for PN's remains applicable. Comparison to results from entropy theory show the transition performance is close to the theoretic optimum. Inclusion of non-exponential transition approximations improves performance results at the expense of increased state-space size. The state-space size estimation theory provides insight and algorithms for evaluating this trade-off.

Watson, James Francis, III↗
NASA NTRS2006

Using Correlation to Compute Better Probability Estimates in Plan Graphs

Plan graphs are commonly used in planning to help compute heuristic "distance" estimates between states and goals. A few authors have also attempted to use plan graphs in probabilistic planning to compute estimates of the probability that propositions can be achieved and actions can be performed. This is done by propagating probability information forward through the plan graph from the initial conditions through each possible action to the action effects, and hence to the propositions at the next layer of the plan graph. The problem with these calculations is that they make very strong independence assumptions - in particular, they usually assume that the preconditions for each action are independent of each other. This can lead to gross overestimates in probability when the plans for those preconditions interfere with each other. It can also lead to gross underestimates of probability when there is synergy between the plans for two or more preconditions. In this paper we introduce a notion of the binary correlation between two propositions and actions within a plan graph, show how to propagate this information within a plan graph, and show how this improves probability estimates for planning. This notion of correlation can be thought of as a continuous generalization of the notion of mutual exclusion (mutex) often used in plan graphs. At one extreme (correlation=0) two propositions or actions are completely mutex. With correlation = 1, two propositions or actions are independent, and with correlation > 1, two propositions or actions are synergistic. Intermediate values can and do occur indicating different degrees to which propositions and action interfere or are synergistic. We compare this approach with another recent approach by Bryce that computes probability estimates using Monte Carlo simulation of possible worlds in plan graphs.

Bryce, Daniel↗
NASA NTRS1988

Estimating the seasonal carbon source-sink geography of a natural, steady-state terrestrial biosphere

The estimation of the seasonal dynamics of biospheric-carbon sources and sinks to be used as an input to global atmospheric CO2 studies and models is discussed. An ecological biosphere model is given and the advantages of the model are examined. Monthly maps of estimated biospheric carbon source and sink regions and estimates of total carbon fluxes are presented for an equilibrium terrestrial biosphere. The results are compared with those from other models. It is suggested that, despite maximum variations of atmospheric CO2 in boreal latitudes, the enormous contributions of tropical wet-dry regions to global atmospheric CO2 seasonality can not be ignored.

Box, Elgene O.↗
NASA NTRS1979

Formulations and applications of large structure actuator and sensor placements

A new approach based on the steady-state solutions of the optimal control and estimation problems is presented to study respectively the actuator and sensor locations for large flexible structures. A simple and computer-implementable formulation for minimizing the steady state optimal cost function and the state estimation error inherent in the estimation process is given. In conjunction with the new approach, two criteria are established relating the actuator and the sensor placement optimalities respectively to the minimums of the optimal cost function and the state estimation error. To illustrate the concepts of this paper, we present the results of some numerical and analytical studies on the actuator and the sensor locations of several simple flexible beam modes.

Juang, J.-N.↗
NASA NTRS2017

Filter Tuning Using the Chi-Squared Statistic

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

Covariance Analysis↗
NASA NTRS1984

Yaw Attitude Estimation for the Tracking and Data Relay Satellite System

The Tracking and Data Relay Satellite System (TDRSS) uses a groundbased attitude determination algorithm to open loop point the satellite's high data rate antennas. The spacecraft is able to measure its pitch and roll attitude, but its yaw attitude is periodically unobservable. The ground software uses a state-space estimator, an adaptation of a Luenberger observer, to predict the spacecraft yaw angle during these unobservable periods. It contains states associated with the roll/yaw dynamics and the on-board control law. The accuracy is limited by the modeling fidelity of the disturbance torques acting on the spacecraft. After initial operating problems were cleared up, the operation of the estimator has converged to predicted performance.

Staich, S.↗
NASA NTRS2012

Wavefront Compensation Segmented Mirror Sensing and Control

The primary mirror of very large submillimeter-wave telescopes will necessarily be segmented into many separate mirror panels. These panels must be continuously co-phased to keep the telescope wavefront error less than a small fraction of a wavelength, to ten microns RMS (root mean square) or less. This performance must be maintained continuously across the full aperture of the telescope, in all pointing conditions, and in a variable thermal environment. A wavefront compensation segmented mirror sensing and control system, consisting of optical edge sensors, Wavefront Compensation Estimator/Controller Soft ware, and segment position actuators is proposed. Optical edge sensors are placed two per each segment-to-segment edge to continuously measure changes in segment state. Segment position actuators (three per segment) are used to move the panels. A computer control system uses the edge sensor measurements to estimate the state of all of the segments and to predict the wavefront error; segment actuator commands are computed that minimize the wavefront error. Translational or rotational motions of one segment relative to the other cause lateral displacement of the light beam, which is measured by the imaging sensor. For high accuracy, the collimator uses a shaped mask, such as one or more slits, so that the light beam forms a pattern on the sensor that permits sensing accuracy of better than 0.1 micron in two axes: in the z or local surface normal direction, and in the y direction parallel to the mirror surface and perpendicular to the beam direction. Using a co-aligned pair of sensors, with the location of the detector and collimated light source interchanged, four degrees of freedom can be sensed: transverse x and y displacements, as well as two bending angles (pitch and yaw). In this approach, each optical edge sensor head has a collimator and an imager, placing one sensor head on each side of a segment gap, with two parallel light beams crossing the gap. Two sets of optical edge sensors are used per segment-to-segment edge, separated by a finite distance along the segment edge, for four optical heads, each with an imager and a collimator. By orienting the beam direction of one edge sensor pair to be +45 away from the segment edge direction, and the other sensor pair to be oriented -45 away from the segment edge direction, all six degrees of freedom of relative motion between the segments can be measured with some redundancy. The software resides in a computer that receives each of the optical edge sensor signals, as well as telescope pointing commands. It feeds back the edge sensor signals to keep the primary mirror figure within specification. It uses a feed-forward control to compensate for global effects such as decollimation of the primary and secondary mirrors due to gravity sag as the telescope pointing changes to track science objects. Three segment position actuators will be provided per segment to enable controlled motions in the piston, tip, and tilt degrees of freedom. These actuators are driven by the software, providing the optical changes needed to keep the telescope phased.

Redding, David C.↗
NASA NTRS1972

The thermodynamic properties of oxygen and nitrogen. Part 2: Thermodynamic properties of oxygen from 100 R to 600 R with pressure to 5000 psia

An equation of state is presented for liquid and gaseous oxygen for temperatures from 100 R to 600 R and pressures to 5000 psia. The pressure-density-temperature data available from the published literature have been reviewed, and appropriate corrections have been applied to bring experimental temperatures into accord with the International Practical Temperature Scale of 1968. Representative comparisons of property values calculated from the equation of state to measured values are included to illustrate the accuracy of the equation of state. The coefficients of the equation of state were determined by a weighted least squares fit to selected published data, and simultaneously to isochoric heat capacity data, and to data which define the phase equilibrium for the saturated liquid and saturated vapor. The equation of state is estimated to be accurate for the liquid to within 0.1 percent in density, to within 0.2 percent for the vapor below the critical temperature and for states above the critical temperatures to 250 K, and within 0.1 percent for supercritical states at temperatures from 250 K to 300 K. The vapor pressure equation is accurate to within + or - 0.01 K between the triple point and the critical point.

Stewart, R. B.↗
NASA NTRS1991

Relative-Error-Covariance Algorithms

Two algorithms compute error covariance of difference between optimal estimates, based on data acquired during overlapping or disjoint intervals, of state of discrete linear system. Provides quantitative measure of mutual consistency or inconsistency of estimates of states. Relative-error-covariance concept applied, to determine degree of correlation between trajectories calculated from two overlapping sets of measurements and construct real-time test of consistency of state estimates based upon recently acquired data.

Bierman, Gerald J.↗
NASA NTRS1973

Stochastic estimates of gradient from laser measurements for an autonomous Martian Roving Vehicle

The general problem presented in this paper is one of estimating the state vector x from the state equation h = Ax, where h, A, and x are all stochastic. Specifically, the problem is for an autonomous Martian Roving Vehicle to utilize laser measurements in estimating the gradient of the terrain. Error exists due to two factors - surface roughness and instrumental measurements. The errors in slope depend on the standard deviations of these noise factors. Numerically, the error in gradient is expressed as a function of instrumental inaccuracies. Certain guidelines for the accuracy of permissable gradient must be set. It is found that present technology can meet these guidelines.-

Shen, C. N.↗
NASA NTRS1991

Theoretical study of the low-lying bound states of O2

It is demonstrated that a complete-active-space self-consistent-field (CASSCF) (2p)/MRCI + Q (multireference configuration interaction with a Davidson correction) description in a (13s8p6d 4f2g)/((5s4p3d 2f1g) atomic natural orbits (ANO) basis set supplemented with diffuse functions provides a quantitative description of the six lowest states of O2. The calculated potentials are within 0.05 eV (1.2 kilocal/mol) of accurate experimental results. The importance of substantially expanding the primitive basis set has been investigated, and it is demonstrated that such expansions yield insignificant improvement in the spectroscopic constants. Potential energy curves have also been reported for the weakly bound states of O2. The 5Pi(g) state is estimated to have a D(e) of 0.16 +/- 0.03 eV. The upper bound of D(e) is found to be sufficiently large that the importance of this state as a precursor for the formation of O2 (b 1Sigma(t)(+)) and O(1S) should be reconsidered.

Partridge, Harry↗
NASA NTRS2000

Interactive Soil Dust Aerosol Model in the GISS GCM: Sensitivity of the Soil Dust Cycle to Radiative Properties of Soil Dust Aerosols - Part 1

The sensitivity of the soil dust aerosol cycle to the radiative forcing by soil dust aerosols is studied. Four experiments with the NASA/GISS atmospheric general circulation model, which includes a soil dust aerosol model, are compared, all using a prescribed climatological sea surface temperature as lower boundary condition. In one experiment, dust is included as dynamic tracer only (without interacting with radiation), whereas dust interacts with radiation in the other simulations. Although the single scattering albedo of dust particles is prescribed to be globally uniform in the experiments with radiatively active dust, a different single scattering albedo is used in those experiments to estimate whether regional variations in dust optical properties, corresponding to variations in mineralogical composition among different source regions, are important for the soil dust cycle and the climate state. On a global scale, the radiative forcing by dust generally causes a reduction in the atmospheric dust load corresponding to a decreased dust source flux. That is, there is a negative feedback in the climate system due to the radiative effect of dust. The dust source flux and its changes were analyzed in more detail for the main dust source regions. This analysis shows that the reduction varies both with the season and with the single scattering albedo of the dust particles. By examining the correlation with the surface wind, it was found that the dust emission from the Saharan/Sahelian source region and from the Arabian peninsula, along with the sensitivity of the emission to the single scattering albedo of dust particles, are related to large scale circulation patterns, in particular to the trade winds during Northern Hemisphere winter and to the Indian monsoon circulation during summer. In the other regions, such relations to the large scale circulation were not found. There, the dependence of dust deflation to radiative forcing by dust particles is probably dominated by physical processes with short time scales. The experiments show that dust radiative forcing can lead to significant changes both in the soil dust cycle and in the climate state. To estimate dust concentration and radiative forcing by dust more accurately, dust size distributions and dust single scattering albedo in the model should be a function of the source region, because dust concentration and climate response to dust radiative forcing are sensitive to dust radiative parameters.

Perlwitz, Jan↗