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At least 739 records · Page 41

Automatic microseismic event picking via unsupervised machine learning

SUMMARY Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Chen, Yangkang↗

Solubility data are compiled for metals in liquid zinc

Available data is compiled on the solubilities of various metals in liquid zinc. The temperature dependence of the solubility data is expressed using the empirical straight line relationship existing between the logarithm of the solubility and the reciprocal of the absolute temperature.

Dillon, I. G.↗

Anomaly Detection in Sequential Health Care Data using Higher-Order Network Representation

The ever-increasing use of information technology (IT) in health care presents new challenges to patient care. Information errors arising from the use of Health IT and their implications on care delivery and patient outcomes have been widely reported. Information errors can lead to changes in clinical decisions, care processes, and care outcomes, among others. An altered care process, for example, could interrupt the sequence of care, which could lead to changes in care decisions and/or changes in care outcomes. We define interruptions in the care process as anomalies in the care sequence. In this paper, we present a new approach based on the higher-order network (HON) representation to detect anomalies in sequential health care data using electronic health records. The results show that there are higher-order dependencies in health care data; and that the use of HON representation is more effective than the first-order network representation for detecting anomalies in sequential health care data.

Niu, Haoran↗

Analysis of Information Content in High-Spectral Resolution Sounders using Subset Selection Analysis

In this paper, we summarize the results of the sensitivity analysis and data reduction carried out to determine the information content of AIRS and IASI channels. The analysis and data reduction was based on the use of subset selection techniques developed in the linear algebra and statistical community to study linear dependencies in high dimensional data sets. We applied the subset selection method to study dependency among channels by studying the dependency among their weighting functions. Also, we applied the technique to study the information provided by the different levels in which the atmosphere is discretized for retrievals and analysis. Results from the method correlate well with intuition in many respects and point out to possible modifications for band selection in sensor design and number and location of levels in the analysis process.

Velez-Reyes, Miguel↗

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗

Utilizing Flight Data to Update Aeroelastic Stability Estimates

Stability analysis of high performance aircraft must account for errors in the system model. A method for computing flutter margins that incorporates flight data has been developed using robust stability theory. This paper considers applying this method to update flutter margins during a post-flight or on-line analysis. Areas of modeling uncertainty that arise when using flight data with this method are investigated. The amount of conservatism in the resulting flutter margins depends on the flight data sets used to update the model. Post-flight updates of flutter margins for an F/A-18 are presented along with a simulation of on-line updates during a flight test.

Lind, Rick↗

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗

The dependence of single event upset on proton energy /15-590 MeV/

Low earth orbit satellite and Jupiter orbiter probe semiconductor devices may incur soft errors or single event upsets, manifested as bit flips, during exposure to such nuclear particles or heavy ions as trapped protons with energies ranging up to 1000 MeV. Experimental data is given on the average proton fluence needed to cause a bit flip as a function of proton energy for isoplanar bipolar TTL RAMs. Error dependence data shape and threshold energy can be related to the existing body of theoretical data on energy deposition following proton nuclear reactions. Experimental data also show that the relative cross sectional amplitude for functionally identical devices can be related to the device's power consumption.

Nichols, D. K.↗

Circulation regime-dependent nonlinear interactions during northern hemisphere winter

Data of 500 mb geopotential heights, obtained in Januaries from 1963-1977 are used to study the relationship between the interaction of different scales of motion and the circulation regime characterizing the large-scale pattern. Geostrophic and 500 mb height streamfunctions and energy and enstrophy spectra are computed. Differences in the height variance, kinetic energy, and enstrophy spectra of the large positive anomaly events are compared to normal circulation. Systematic differences in the nonlinear cascading are examined. The data reveal that transient eddies perform a regime-dependent function in the interactions with atmospheric circulation modes on the scale of the persistent anomalies.

Brown, P. S.↗

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Ulbrich, Norbert Manfred↗

A proven approach for more effective software development and maintenance

Modern space flight mission operations and associated ground data systems are increasingly dependent upon reliable, quality software. Critical functions such as command load preparation, health and status monitoring, communications link scheduling and conflict resolution, and transparent gateway protocol conversion are routinely performed by software. Given budget constraints and the ever increasing capabilities of processor technology, the next generation of control centers and data systems will be even more dependent upon software across all aspects of performance. A key challenge now is to implement improved engineering, management, and assurance processes for the development and maintenance of that software; processes that cost less, yield higher quality products, and that self-correct for continual improvement evolution. The NASA Goddard Space Flight Center has a unique experience base that can be readily tapped to help solve the software challenge. Over the past eighteen years, the Software Engineering Laboratory within the code 500 Flight Dynamics Division has evolved a software development and maintenance methodology that accommodates the unique characteristics of an organization while optimizing and continually improving the organization's software capabilities. This methodology relies upon measurement, analysis, and feedback much analogous to that of control loop systems. It is an approach with a time-tested track record proven through repeated applications across a broad range of operational software development and maintenance projects. This paper describes the software improvement methodology employed by the Software Engineering Laboratory, and how it has been exploited within the Flight Dynamics Division with GSFC Code 500. Examples of specific improvement in the software itself and its processes are presented to illustrate the effectiveness of the methodology. Finally, the initial findings are given when this methodology was applied across the mission operations and ground data systems software domains throughout Code 500.

Pajerski, Rose↗

Single-channel and single-energy partial-wave analysis with continuity improved through minimal phase constraints

Single-energy partial-wave analysis has often been applied as a way to fit data with minimal model dependence. However, remaining unconstrained, partial waves at neighboring energies will vary discontinuously because the overall amplitude phase cannot be determined through single-channel measurements. This problem can be mitigated through the use of a constraining penalty function based on an associated energy-dependent fit. However, the weight given to this constraint results in a biased fit to the data. In this paper, for the first time, we explore a constraining function which does not influence the fit to data. The constraint comes from the overall phase found in multichannel fits which, in the present study, are the Bonn-Gatchina and Jülich-Bonn multichannel analyses. The data are well reproduced and weighting of the penalty function does not influence the result. The method is applied to K⁢Λ photoproduction data and all observables can be maximally well reproduced. While the employed multichannel analyses display very different multipole amplitudes, we show that the major difference between two sets of multipoles can be related to the different overall phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

MGS MAG/ER Data Analysis Using a Time and Magnetic Field Dependent Electron Transport Model

The goal of that project was to examine certain details about the dayside electron environment at Mars as seen by the Mars Global Surveyor (MGS) magnetometer/electron reflectometer (MAG/ER) instrument. Specifically, we stated that we would use the Khazanov and Liemohn (K&L) kinetic electron transport model to analyze features in the observations. This code includes a non-uniform magnetic field and time-dependence in the result (different from most other models of this type). It was originally developed for electron motion along field lines in the Earth's magnetosphere (between conjugate ionospheres), and is thus quite appropriate for application to the Mars magnetic field scenario. Numerous code developments were implemented and the Mars version of the K&L model is fully operational. Initial results from this code have focused on the examination of MGS MAG/ER observations in the crustal field region when it is on the dayside. After several presentations at scientific meetings, this study culminated in a JGR publication last year.

Liemohn, Michael W.↗

Developing a Standard for Earth Observation Data Preservation Content - A Path to Future Usability

For datasets to be usable, many pieces of information in addition to the data themselves are essential. During the active parts of the lifecycle of dataset generating projects, the needed information is usually accessible through individuals familiar with the various aspects of the projects. However, the utility of datasets tends to outlive the lives of projects, by several decades in many cases. Thus it is essential to capture all the relevant information about the datasets, data, metadata and associate knowledge that is sufficient to read, understand, interpret and reuse the datasets, while the projects are still active. The capture and preservation should be such that the data are usable when no consultation is available from the original project participants. Identification of specific categories of content through an international standard is beneficial to the user communities of the future, so that projects involving Earth observations and generating data products can consistently plan for preservation and future usability of the project outcomes. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The standard, ISO 19165-1, titled "Geographic Information - Preservation of digital data and metadata Part 1: Fundamentals" considers geographic information preservation in general. It acknowledges that "specific content items needed to preserve the full provenance and context of the data and associated metadata depend on the needs of the designated community and types of datasets (e.g., maps, remotely sensed data from satellites and airborne instruments, physical samples). Follow-up parts to this standard may be developed detailing content items appropriate to individual disciplines." NASA proposed an extension to this standard, titled "Geographic information -- Preservation of digital data and metadata -- Part 2: Content specifications for Earth observation data and derived digital products." The development of this extension is in progress with participation by an international team representing nine countries. The purpose of this paper is to introduce this standard and report on its status.

Remote Sensing; Data Systems; Open Data;↗

Spring 2014 Internship Diffuser Data Analysis

J-2X engine testing on the A-2 test stand at the NASA John C. Stennis Space Center (SSC) has recently concluded. As part of that test campaign, the engine was operated at lower power levels in support of expanding the use of J-2X to other missions. However, the A-2 diffuser was not designed for engine testing at the proposed low power levels. To evaluate the risk of damage to the diffuser, computer simulations were created of the rocket engine exhaust plume inside the 50ft long, water-cooled, altitude-simulating diffuser. The simulations predicted that low power level testing would cause the plume to oscillate in the lower sections of the diffuser. This can possibly cause excessive vibrations, stress, and heat transfer from the plume to the diffuser walls. To understand and assess the performance of the diffuser during low power level engine testing, nine accelerometers and four strain gages were installed around the outer surface of the diffuser. The added instrumentation also allowed for the verification of the rocket exhaust plume computational model. Prior to engine hot-fire testing, a diffuser water-flow test was conducted to verify the proper operation of the newly installed instrumentation. Subsequently, two J-2X engine hot-fire tests were completed. Hot-Fire Test 1 was 11.5 seconds in duration, and accelerometer and strain data verified that the rocket engine plume oscillated in the lower sections of the diffuser. The accelerometers showed very different results dependent upon location. The diffuser consists of four sections, with Section 1 being closest to the engine nozzle and Section 4 being farthest from the engine nozzle. Section 1 accelerometers showed increased amplitudes at startup and shutdown, but low amplitudes while the diffuser was started. Section 3 accelerometers showed the opposite results with near zero G amplitudes prior to and after diffuser start and peak amplitudes to +/- 100G while the diffuser was started. Hot-Fire Test 1 strain gages showed different data dependent on section. Section 1 strains were small, and were in the range of 50 to 150 microstrain, which would result in stresses from 1.45 to 4.35 ksi. The yield stress of the material, A-285 Grade C Steel, is 29.7 ksi. Section 4 strain gages showed much higher values with strains peaking at 1600 microstrain. This strain corresponds to a stress of 46.41 ksi, which is in excess of the yield stress, but below the ultimate stress of 55 to 75 ksi. The decreased accelerations and strain in Section 1, and the increased accelerations and strain in Sections 3 and 4 verified the computer simulation prediction of increased plume oscillations in the lower sections of the diffuser. Hot-Fire Test 2 ran for a duration of 125 seconds. The engine operated at a slightly higher power level than Hot-Fire Test 1 for the initial 35 seconds of the test. After 35 seconds the power level was lowered to Hot-Fire Test 1 levels. The acceleration and strain data for Hot-Fire Test 2 was similar during the initial part of the test. However, just prior to the engine being lowered to the Hot-Fire Test 1 power level, the strain gage data in Section 4 showed a large decrease to strains near zero microstrain from their peak at 1500 microstrain. Future work includes further strain and acceleration data analysis and evaluation.

Laigaie, Robert T.↗

Molecular understanding of new-particle formation from α-pinene between -50 and +25 °C

Abstract. Highly oxygenated organic molecules (HOMs) contribute substantially to the formation and growth of atmospheric aerosol particles, which affect air quality, human health and Earth's climate. HOMs are formed by rapid, gas-phase autoxidation of volatile organic compounds (VOCs) such as α-pinene, the most abundant monoterpene in the atmosphere. Due to their abundance and low volatility, HOMs can play an important role in new-particle formation (NPF) and the early growth of atmospheric aerosols, even without any further assistance of other low-volatility compounds such as sulfuric acid. Both the autoxidation reaction forming HOMs and their NPF rates are expected to be strongly dependent on temperature. However, experimental data on both effects are limited. Dedicated experiments were performed at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN to address this question. In this study, we show that a decrease in temperature (from +25 to -50°C) results in a reduced HOM yield and reduced oxidation state of the products, whereas the NPF rates (J1.7 nm) increase substantially. Measurements with two different chemical ionization mass spectrometers (using nitrate and protonated water as reagent ion, respectively) provide the molecular composition of the gaseous oxidation products, and a two-dimensional volatility basis set (2D VBS) model provides their volatility distribution. The HOM yield decreases with temperature from 6.2 % at 25°C to 0.7 % at -50°C. However, there is a strong reduction of the saturation vapor pressure of each oxidation state as the temperature is reduced. Overall, the reduction in volatility with temperature leads to an increase in the nucleation rates by up to 3 orders of magnitude at -50°C compared with 25°C. In addition, the enhancement of the nucleation rates by ions decreases with decreasing temperature, since the neutral molecular clusters have increased stability against evaporation. The resulting data quantify how the interplay between the temperature-dependent oxidation pathways and the associated vapor pressures affect biogenic NPF at the molecular level. Our measurements, therefore, improve our understanding of pure biogenic NPF for a wide range of tropospheric temperatures and precursor concentrations.

54 ENVIRONMENTAL SCIENCES↗

Review of research on wave mean flow interactions using FGGE data

Comparison is made between the conventional Eulerian diagnostics of wave mean flow interactions in the atmosphere and the diagnostics introduced by Andrews and McIntyre (1976). In the latter, the meridional circulation is represented by a residual circulation, and the eddy torque in the zonal momentum equation by the Eliassen-Palm (1960) flux divergence (or equivalently, by the poleward eddy flux of geostrophic potential vorticity). It is found that, while the new diagnostics are useful in studying stratospheric warmings and transports of conservative quantities, the conventional diagnostics are more useful in studying global energetics and wave mean flow interactions in the troposphere and lower stratosphere. Case studies diagnosed with FGGE IIIb data are presented to illustrate this point. Kung and Tanaka's (1983) comparisons of the atmospheric energy cycle for SOP-1 and SOP-2, estimated with the use of the ECMWF and GFDL FGGE IIIb data bases, are used to assess the uncertainty in calculations of energetics based on the use of FGGE IIIb data. These results demonstrate the high degree of model dependence in the FGGE IIb data sets.

Pfeffer, R. L.↗