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DOE OSTI2018

Declining demographic performance and dispersal limitation influence the geographic distribution of the perennial forb Astragalus utahensis (Fabaceae)

Abstract A central goal of ecology is understanding the determinants of species’ distributions. “Metapopulation” models for the existence of distributional boundaries predict that species’ geographic ranges arise from the landscape‐scale deterioration of habitat suitability towards the range edge (i.e., niche mechanisms), which simultaneously hinders demographic performance and limits dispersal to suitable habitat beyond the edge (i.e., dispersal limitation). However, few studies have examined both of these mechanisms for the same species by examining abundance and comprehensive measures of demographic performance across the distribution and beyond its boundary. We tested the predictions of metapopulation models for range limits by contrasting abundance, demographic performance, and population growth ( λ ) of the perennial forb Astragalus utahensis in central and northern range edge populations. We tested for dispersal limitation by transplanting individuals at and beyond the northern range boundary and monitoring their demographic performance. Astragalus abundance and stochastic λ decreased from the range centre to the northern range edge, with stochastic λ falling to or below replacement in range edge populations. However, transplants at some sites beyond the northern range edge survived and reproduced at levels similar to transplants within the range. Thus, in addition to deteriorating conditions at the range edge, dispersal limitation appears to contribute to limiting A. utahensis’ northern distribution . Synthesis. Our results support metapopulation models for range limits by suggesting that decreased demographic performance constrains the viability of range edge populations while contributing to dispersal limitation of Astragalus utahensis’ distribution. Thus, the tandem action of niche and dispersal processes appears to play an important role in constraining this species’ northern latitudinal range.

Baer, Kathryn C.↗

NASA NTRS2007

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗

NASA NTRS2019

A Validation Study of the Performance Prediction Methodology of the Early Warning Metrics

Complex projects frequently experience delays and develop backlogs of their project control milestones during the acquisition and development lifecycles. In response, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) formed an independent group of Subject Matter Experts (SMEs) to monitor the execution performance of GSFC Flight projects and instruments that are under development. The SME team’s objective is to generate data driven performance-based indicators that quantify the degree to which projects are meeting their respective schedule and budget commitments. One of these performance-based indicators, the Early Warning Metrics, provides performance forecasts and insight to project performance relative to historical successful projects. Herein this paper describes the purpose and utility of the Early Warning Metrics. Additionally, the initial prediction method used in the creation of the metrics is described along with its validity and the validity of comparable prediction methods.

Holloman, Sherrica↗

NASA NTRS1992

Steady and Transient Performance Prediction of Gas Turbine Engines

This Lecture Series covers topics of aero-thermodynamic performance prediction methods for gas turbine engines with respect to steady and transient operation. This includes advanced cycle calculation methods, also taking into account variable cycle engine types. A very important objective is the consideration of installation effect, i.e., Reynolds number and inlet distortions, as well as advanced control concepts for increasing engine surge margins. In addition to these topics, individual papers include practical considerations in developing the engine cycle, dynamic simulation, inlet distortion effects in aircraft propulsion system integration, “smart” engines, performance and heal monitoring models. This Lecture Series, sponsored by the Propulsion and Energetics Panel of AGARD and the Consultant and Exchange Programme of AGARD presented on 27th -28th May 1992 in Cambridge, MA, United States, 9th-10th June 1992 in Neubiberg, Germany and 11th-12th June 1992 in Chàtillon/Bagneux (near Paris), France

Aircraft engines↗

NASA NTRS1997

A New Approach in Spacecraft Monitoring

This paper describes the end-to-end system design, operational scenarios, performance of the ground monitor, and the DS1 experiment.

on-board intelligence Beacon Monitor Europa Pluto↗

DOE OSTI2019

EGS Collab Project Electrical Resistivity Tomography Characterization and Monitoring

The EGS (Enhanced Geothermal Systems) Collab project is performing stimulation experiments in highly monitored and well-characterized intermediate-scale (~10-20 m) field test beds. The characterization and monitoring system includes an array of electrodes grouted in place within six monitoring wells, with 16 electrodes per well. The electrodes enable characterization of the 3D low-frequency electrical properties of the host rock, and changes in those properties during stimulation and tracer testing using both static and time-lapse Electrical Resistivity Tomography. In this talk we present: 1) ERT array design and installation, 2) baseline (pre-stimulation) imaging results, 3) time-lapse data collected during stimulation operations, and 4) real-time imaging during clean water injections intended to illuminate flow paths as a decrease in bulk electrical conductivity. We will also discuss aspects and lessons learned for conducting ERT imaging operations in the presence of high fluid pressure gradients during stimulation and flow operations. Results to date reveal a highly heterogeneous rock fabric, ranging over four orders of magnitude in bulk electrical conductivity, and high polarization capacity. Baseline imaging results are consistent with borehole logs and core studies. Time-lapse imaging results to identify major flow paths during tracer studies are forthcoming and will be discussed during this presentation. Ultimately the ERT imaging data sets provide useful information for validating and verifying model predictions in preparation for research at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE).

electrical resistivity tomography, geophysics, geo↗

DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗

DOE OSTI2022

Progress of Tripwire: Multi-Modal Distributed Sensing for Repository Verification

This project is developing and demonstrating a multi-modal sensor system, TRIPWIRE, for containment verification in inaccessible radiological and nuclear waste repositories. The TRIPWIRE system will continuously monitor ionizing radiation and electromagnetic fields in the vicinity of emplaced nuclear materials buried in a repository, reporting on disturbances with a real-time alarm control station. The system will use long-length scintillating fiber bundles (SFBs) to perform area radiation monitoring; these will be coupled to kilometer-scale multimodal optical communication fibers – all light sensors and electronic components used with this system will be located above ground. Electromagnetic fields, and changes in local dielectric conditions caused by intrusion and soil movement, will be monitored using commercial grade, ported "leaky" coaxial cables (PCCs), with control electronics also located above ground. This paper documents the results of the simulations and modeling efforts that have helped identify the optimal placement of the SFBs. Additionally, the paper includes the current progress on the multi-modal SFB-PCC system, including the fabrication of long-length (>3-m) fibers and their coupling to optical fibers.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2022

Progress of Tripwire: Multi-modal Distributed Sensing for Repository Verification

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2022

Assessing the Effectiveness of Generalized Likelihood Ratio Test Detector Schemes in Seismic Event Detection and the Avoidance of Nontarget Signals

Cross-correlation techniques have played a long-standing and pivotal role in seismic event monitoring. However, the performance of correlation-based detectors is challenged by nuisance seismicity, or nontarget signals. Such detections are a problem when the mission is to automatically map events to the correct source region. Using aftershocks of the 2014 $M_w$ 6.0 South Napa, California, earthquake, we demonstrate the effectiveness of utilizing a dynamic correlation processor framework in a generalized likelihood ratio test (GLRT) detector configuration to minimize nontarget detections. A GLRT maximizes a detection statistic with respect to one or more unknown parameters. In this case, the detection statistic is a template signal match against the waveform in a window sliding over a data stream, and the unknown parameter is an index variable indicating group membership of the template event or events. Detected events are assigned to the event group that yields the largest detection statistic. In this work, our results show that a GLRT detector will outperform a suite of independently operating correlation and subspace detectors in terms of having a lower nontarget detection rate at a given missed detection rate. We also show that a GLRT detector composed of a few high-rank subspace detectors has a slightly higher nontarget detection rate, but a significantly lower missed detection rate, than a GLRT detector composed of many low-rank subspace detectors. The high-rank GLRT configuration produced impressive results even with marginal data (single channel, single station, and very low time bandwidth product), which bodes well for the utility of building efficient aftershock classification systems and global monitoring systems at larger scales. However, future work is required to assess performance at the regional scale and to assess the performance of the system at detecting target events not used in the detector template creation.

58 GEOSCIENCES↗

DOE OSTI2021

Performance assessment of low-cost environmental monitors and single sensors under variable indoor air quality and thermal conditions

Not Available

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1972

Fabrication, test and demonstration of critical environment monitoring system

Design and performance of an analytical system for the evaluation of certain environmental constituents in critical environmental areas of the Quality Reliability and Assurance Laboratory are reported. Developed was a self-contained, integrated, minimum sized unit that detects, interrogates, and records those parameters of the environment dictated for control in large storage facilities, clean rooms, temporarily curtained enclosures, and special working benches. The system analyzes humidity, temperature, hydrocarbons particle size, and particle count within prescribed clean areas.

Heimendinger, K. W.↗

NASA NTRS1994

Factors controlling precision and accuracy in isotope-ratio-monitoring mass spectrometry

The performance of systems in which picomole quantities of sample are mixed with a carrier gas and passed through an isotope-ratio mass spectrometer system was examined experimentally and theoretically. Two different mass spectrometers were used, both having electron-impact ion sources and Faraday cup collector systems. One had an accelerating potential of 10kV and accepted 0.2 mL of He/min, producing, under those conditions, a maximum efficiency of 1 CO2 molecular ion collected per 700 molecules introduced. Comparable figures for the second instrument were 3 kV, 0.5 mL of He/min, and 14000 molecules/ion. Signal pathways were adjusted so that response times were <200 ms. Sample-related ion currents appeared as peaks with widths of 3-30 s. Isotope ratios were determined by comparison to signals produced by standard gases. In spite of rapid variations in signals, observed levels of performance were within a factor of 2 of shot-noise limits. For the 10-kV instrument, sample requirements for standard deviations of 0.1 and 0.5% were 45 and 1.7 pmol, respectively. Comparable requirements for the 3-kV instrument were 900 and 36 pmol. Drifts in instrumental characteristics were adequately neutralized when standards were observed at 20-min intervals. For the 10-kV instrument, computed isotopic compositions were independent of sample size and signal strength over the ranges examined. Nonlinearities of <0.04%/V were observed for the 3-kV system. Procedures for observation and subtraction of background ion currents were examined experimentally and theoretically. For sample/ background ratios varying from >10 to 0.3, precision is expected and observed to decrease approximately 2-fold and to depend only weakly on the precision with which background ion currents have been measured.

NASA Discipline Exobiology↗

NASA NTRS2014

Performance Evaluation of the Operational Air Quality Monitor for Water Testing Aboard the International Space Station

In the history of manned spaceflight, environmental monitoring has relied heavily on archival sampling. For short missions, this type of sample collection was sufficient; returned samples provided a snapshot of the presence of chemical and biological contaminants in the spacecraft air and water. However, with the construction of the International Space Station (ISS) and the subsequent extension of mission durations, soon to be up to one year, the need for enhanced, real-time environmental monitoring became more pressing. The past several years have seen the implementation of several real-time monitors aboard the ISS, complemented with reduced archival sampling. The station air is currently monitored for volatile organic compounds (VOCs) using gas chromatography-differential mobility spectrometry (Air Quality Monitor [AQM]). The water on ISS is analyzed to measure total organic carbon and biocide concentrations using the Total Organic Carbon Analyzer (TOCA) and the Colorimetric Water Quality Monitoring Kit (CWQMK), respectively. The current air and water monitors provide important data, but the number and size of the different instruments makes them impractical for future exploration missions. It is apparent that there is still a need for improvements in environmental monitoring capabilities. One such improvement could be realized by modifying a single instrument to analyze both air and water. As the AQM currently provides quantitative, compound-specific information for target compounds present in air samples, and many of the compounds are also targets for water quality monitoring, this instrument provides a logical starting point to evaluate the feasibility of this approach. In this presentation, we will discuss our recent studies aimed at determining an appropriate method for introducing VOCs from water samples into the gas phase and our current work, in which an electro-thermal vaporization unit has been interfaced with the AQM to analyze target analytes at the relevant concentrations at which they are routinely detected in archival water samples from the ISS.

Wallace, William T.↗

NASA NTRS2014

Performance Evaluation of the Operational Air Quality Monitor for Water Testing Aboard the International Space Station

Real-time environmental monitoring on ISS is necessary to provide data in a timely fashion and to help ensure astronaut health. Current real-time water TOC monitoring provides high-quality trending information, but compound-specific data is needed. The combination of ETV with the AQM showed that compounds of interest could be liberated from water and analyzed in the same manner as air sampling. Calibration of the AQM using water samples allowed for the quantitative analysis of ISS archival samples. Some calibration issues remain, but the excellent accuracy of DMSD indicates that ETV holds promise for as a sample introduction method for water analysis in spaceflight.

Wallace, William T.↗

DOE OSTI2020

First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska North Slope – Producer Responses and Operational Lessons Learned

The US Department of Energy and Hilcorp Alaska, LLC are jointly cosponsoring a field pilot project entitled “First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil Enhanced Oil Recovery (EOR).” The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on Alaska North Slope (ANS). Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot which was designed to acquire field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Hydrolyzed polyacrylamide (HPAM) polymer injection started on August 28, 2018 using a custom made polymer mixing and pumping unit. Polymer solution properties such as concentration, viscosity, and filter ratio, have been closely monitored and adjusted as necessary. Operational procedures have been improved to ensure adequate injectivity and polymer propagation through the formation. Oil and water production is tested frequently to monitor water cut performance, and produced water is sampled and analyzed for polymer content. Tracers were pumped pre and post polymer injection startup to compare polymer flood breakthrough timing and sweep efficiency. Polymer injectivity of the horizontal wells drilled in the Schrader Bluff NB sand is found to be sufficient to replace the reservoir production voidage although there were some declines as high viscosity polymer swept the near wellbore region. Production data show significant reduction in water cut and the oil production rate has stabilized. No polymer production has been confirmed from the two horizontal producers after 22 months of polymer injection into the two supporting horizontal injectors. Tracer data show very low sweep efficiencies with waterflood alone, whereas significant improvement has been achieved with polymer flood. Many operational lessons have been learned and improvements have been made regarding polymer mixing, pumping, and onsite quality control, particularly in a challenging Arctic environment. Adequate polymer injection rate can be achieved with diligent monitoring and quality assurance of the properties of the injected polymer solution.

Ning, Samson↗

NASA NTRS2024

Development of a High Frequency Class-A Amplifier for High Temperature Wireless Microsystems based on a Silicon Carbide Static Induction Transistor

Next generation gas turbine engine health monitoring for high performance jet engine-powered aircraft will incorporate integrated microelectronic sensors specifically designed to enhance aircraft functionality, engine efficiency, and safety. Temperature, air flow and pressure associated with the gas path as well as emissions from the engine correlate to the state of the combustor and other engine health conditions. Monitoring these parameters accurately requires positioning electronic sensors in the hot zone of the gas turbine engine, which exposes them to temperatures in excess of 400ºC. At these temperatures, signal amplification is needed at the transducer level to distinguish the desired measured signal from the significant electronic noise generated by the harsh environment. In this presentation, we report on the simulation, development, fabrication, and testing on a high temperature Class-A amplifier which utilizes a 4H-SiC Static Induction Transistor (SIT) as the active device and input/output matching and DC bias networks comprised of thin-film spiral inductors, metal-insulator-metal capacitors, and thick film chip resistors. A small signal model that emulates the operation of the 4H-SiC SIT from 25 to 400ºC, with an emphasis on operation at 400οC, was utilized. Measurements were performed from 25 to 400ºC to generate current-voltage curves, capacitive transistor characteristics and high frequency scattering parameters (S-parameters). The measured data was used to extrapolate the transconductance, gm, as a function of temperature for model development. Circuit simulation tools were used to generate S-parameters, which were compared to the measured values. At 400οC, a maximum difference between measured and simulated S-parameters for frequencies from 20 to 100 MHz were 3.84%, 0.68%, 10.61%, and 3.26% for S21, S12, S11, and S22, respectively. The average transit frequency, ft, was calculated from measured values to be 197.8 MHz, while the simulated value from the model was found to be 200 MHz. The Amplifier’s S-parameters were recorded at 20-100 MHz over a temperature range of 25-400ºC and show a gain of approximately 15.8 and 5.80 dBm at 25 and 400ºC, respectively. The input and output reflection coefficients at 50 MHz and 400ºC were -18.5 and -15.2 dB, respectively. The noise figure and phase noise were measured over the temperature range of 25-400ºC and recorded. The noise figure increased 21% at 50 MHz over the temperature range, while the 1 kHz offset of the phase noise remained below -110 dB. The stability factor, K, calculated with measured and simulated data demonstrates unconditional stability over the frequency range at 400ºC. Lastly, the 1-dB compression point was measured at 50 MHz and 400ºC with an approximated output of 9.5 dBm.

SiC↗

NASA NTRS1991

Wind tunnel blockage study of a generic three-dimensional sidewall compression scramjet inlet at Mach 10

A large scale model of a generic three-dimensional sidewall compression scramjet inlet has been designed based on the results of a computational parametric study for testing in the 31-inch Mach 10 Hypersonic Wind Tunnel at the NASA Langley Research Center. In order to increase the instrumentation density in interaction regions for a highly instrumented model, it is desirable to make the model as large as possible. When the cross-sectional area of a model becomes large relative to the inviscid core size of the tunnel, the effects of blockage must be considered. In order to assess these effects, a blockage model (an inexpensive, much less densely instrumented version of the configuration) was fabricated for preliminary testing. Since it was desired to determine both the effect of the model on the performance of the wind tunnel and also to determine if the inlet would start, the model possessed a total of 32 static pressure orifices distributed on the forebody plane and sidewalls; seventeen static pressure orifices on the tunnel wall and 3 pitot probes on the model monitored the tunnel performance. This paper presents the design considerations in the development of the wind tunnel model and the blockage aspects of the effects of contraction ratio, cowl location, Reynolds number, and angle of attack.

Holland, Scott D.↗