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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. Ground truth spectral signature data for various types of scenes, including ground with and without annuals, and various shrubs, were collected. When these signature data are plotted with infrared (MSS band 6 or 7) reflectivity on one axis and red (MSS band 5) reflectivity on the other axis, clusters of data from the various types of scenes are distinct. This method of expressing spectral signature data appears to be more useful for distinguishing types of scenes than a simple infrared to red reflectivity ration. Large areas of varnished desert pavement are visible and mappable on ERTS-1 and high altitude aircraft imagery. A large scale vegetation pattern was found to be correlated with the presence of the desert pavement. The large scale correlation was used in mapping the vegetation of the area. It was found that a distinctive soil type was associated with the presence of the varnished desert pavement. The high salinity and exchangeable sodium percentage of this soil type provide a basis for the explanation of both the large scale and small scale vegetation pattern.

Mcginnies, W. G.↗
NASA NTRS1974

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. It is possible to determine, from ERTS imagery, native arid plant distribution. Using techniques of multispectral masking and extensive fieldwork, three native vegetation communities were defined and mapped in the Avra Valley study area. A map was made of the Yuma area with the aid of ground truth correlations between areas of desert pavement visible on ERTS images and unique vegetation types. With the exception of the Yuma soil-vegetation correlation phenomena, only very gross differentiations of desert vegetation communities can be made from ERTS data. Vegetation communities with obvious vegetation density differences such as saguaro-paloverde, creosote bush, and riparian vegetation can be separated on the Avra Valley imagery while more similar communities such as creosote bush and saltbush could not be differentiated. It is suggested that large differences in vegetation density are needed before the signatures of two different vegetation types can be differentiated on ERTS imagery. This is due to the relatively insignificant contribution of vegetation to the total radiometric signature of a given desert scene. Where more detailed information concerning the vegetation of arid regions is required, large scale imagery is appropriate.

Mcginnies, W. G.↗
NASA NTRS1975

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. Research results include a method for determining the reflectivities of natural areas from ERTS data taking into account sun angle and atmospheric effects on the radiance seen by the satellite sensor. Ground truth spectral signature data for various types of scenes, including ground with and without annuals, and various shrubs were collected. Large areas of varnished desert pavement are visible and mappable on ERTS and high altitude aircraft imagery. A large scale and a small scale vegetation pattern were found to be correlated with presence of desert pavement. A comparison of radiometric data with video recordings shows quantitatively that for most areas of desert vegetation, soils are the most influential factor in determining the signature of a scene. Additive and subtractive image processing techniques were applied in the dark room to enhance vegetational aspects of ERTS.

Mcginnies, W. G.↗
NASA NTRS1982

Infrared remote sensing of the vertical and horizontal distribution of clouds

An algorithm has been developed to derive the horizontal and vertical distribution of clouds from the same set of infrared radiance data used to retrieve atmospheric temperature profiles. The method leads to the determination of the vertical atmospheric temperature structure and the cloud distribution simultaneously, providing information on heat sources and sinks, storage rates and transport phenomena in the atmosphere. Experimental verification of this algorithm was obtained using the 15-micron data measured by the NOAA-VTPR temperature sounder. After correcting for water vapor emission, the results show that the cloud cover derived from 15-micron data is less than that obtained from visible data.

Chahine, M. T.↗
DOE OSTI2024

Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, in this paper, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Magnetic Field Sensing via Acoustic Sensing Fiber with Metglas® 2605SC Cladding Wires

Magnetic field sensing has the potential to become necessary as a critical tool for long-term subsurface geophysical monitoring. The success of distributed fiber optic sensing for geophysical characterization provides a template for the development of next generation downhole magnetic sensors. In this study, Sentek Instrument’s picoDAS is coupled with a multi-material single mode optical fiber with Metglas® 2605SC cladding wire inclusions for magnetic field detection. The response of acoustic sensing fibers with one and two Metglas® 2605SC cladding wires was evaluated upon exposure to lateral AC magnetic fields. An improved response was demonstrated for a sensing fiber with in-cladding wire following thermal magnetic annealing (~400 °C) under a constant static transverse magnetic field (~200 μT). A minimal detectable magnetic field of ~500 nT was confirmed for a sensing fiber with two 10 μm cladding wires. The successful demonstration of a magnetic field sensing fiber with Metglas® cladding wires fabricated via traditional draw processes sets the stage for distributed measurements and joint inversion as a compliment to distributed fiber optic acoustic sensors.

Dejneka, Zach (ORCID:0000000179415708)↗
DOE OSTI2024

All-digital Sensor System for Distributed Downhole Pressure Monitoring in Unconventional Fields

This project developed and validated (through field tests) a new low-cost all-digital pressure sensing technology for in situ distributed downhole pressure monitoring in unconventional oil and gas (UOG) fields. The all-digital sensing technology uses a built-in non-electric analog-to-digital converter (ADC) to transform the pressure information into a combination of binary (ON/OFF) states. As such, the system does not need downhole electronics for signal conditioning and telemetry. The all-digital sensors can be remotely logged over a long distance, and many sensors can be multiplexed for distributed sensing. Based on a review of unconventional wells in the Lower 48 states, the specification of the sensor is to measure pressure up to 69 MPa (10,000 psi) and temperature up to 250°C. A sensor with a helical bourdon sensing element and a digital signal decoder of 50 mm diameter and 109 mm length was constructed. The helical bourdon sensing element was made of 304L stainless steel and filled with motor oil. The digital converter was made up of 8 digital reading pads constructed of high-temperature epoxy with conductive inserts made of stainless steel. The sensor had a linear response to pressure with an accuracy of 0.14 MPa (20 psi). To withstand the high pressure, the sensor was enclosed in a stainless-steel pressure housing with a wall thickness of 5.5 mm, a diameter of 73 mm, and a length of 724 mm. In the laboratory tests, the sensor exhibited no temperature-related effects on the results. The sensor did not show drift over a 14-day test period at elevated pressure. A field test was conducted where the sensor was deployed in a test wellbore at the Quest drilling test facility to a depth of 0 feet over three weeks. The sensor was attached to the production rods, along with a downhole reference sensor of PPS27 type, which is a permanent downhole monitoring system. During the testing phase, the test well annular blow-out preventer was closed, and the well was pressurized at the surface to 11 MPa (1600 psi). The sensor read the elevated bottom hole pressure of 1500 psi. A multiplexing unit was created for the sensor to deploy multiple sensors on one data transmission line in a distributed approach. The multiplexing unit was tested in a simulated environment of 3048 m (10,000 ft) with five sensors distributed. The sensors were pressurized at different intervals. The multiplexed sensors recorded the correct pressure, and the multiplexing did not interfere with the readings. The proposed concept of an all-digital pressure sensor for harsh downhole environments was designed, manufactured, and tested in the laboratory and tested at the field to a up to 69 MPa and 250°C. This technology has high-temperature tolerance and has potential in downhole areas outside oil and gas, such as carbon capture and storage (CCS) and geothermal wells. The sensor concept has been proven in this project, but to create a commercially viable product, manufacturing a sensor with a smaller diameter needs to be performed.

02 PETROLEUM↗
DOE OSTI2025

Advancing Temperature Monitoring of the Bottom Anode in a Direct Current Electric Arc Furnace Operations with Distributed Optical Fiber Sensors.

The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. Furthermore, this work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and Rayleigh backscattering (RBS). The early detection of temperature anomalies along the length of the anode pin through distributed sensing enhances operational safety, providing a robust alternative to traditional thermocouples.

42 ENGINEERING↗
NASA NTRS2000

Retrieving the Vertical Structure of the Effective Aerosol Complex Index of Refraction from a Combination of Aerosol in Situ and Remote Sensing Measurements During TARFOX

The largest uncertainty in estimates of the effects of atmospheric aerosols on climate stems from uncertainties in the determination of their microphysical properties, including the aerosol complex index of refraction, which in turn determines their optical properties. A novel technique is used to estimate the aerosol complex index of refraction in distinct vertical layers from a combination of aerosol in situ size distribution and remote sensing measurements during the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX). In particular, aerosol backscatter measurements using the NASA Langley LASE (Lidar Atmospheric Sensing Experiment) instrument and in situ aerosol size distribution data are utilized to derive vertical profiles of the "effective" aerosol complex index of refraction at 815 nm (i.e., the refractive index that would provide the same backscatter signal in a forward calculation on the basis of the measured in situ particle size distributions for homogeneous, spherical aerosols). A sensitivity study shows that this method yields small errors in the retrieved aerosol refractive indices, provided the errors in the lidar-derived aerosol backscatter are less than 30% and random in nature. Absolute errors in the estimated aerosol refractive indices are generally less than 0.04 for the real part and can be as much as 0.042 for the imaginary part in the case of a 30% error in the lidar-derived aerosol backscatter. The measurements of aerosol optical depth from the NASA Ames Airborne Tracking Sunphotometer (AATS-6) are successfully incorporated into the new technique and help constrain the retrieved aerosol refractive indices. An application of the technique to two TARFOX case studies yields the occurrence of vertical layers of distinct aerosol refractive indices. Values of the estimated complex aerosol refractive index range from 1.33 to 1.45 for the real part and 0.001 to 0.008 for the imaginary part. The methodology devised in this study provides, for the first time, a complete set of vertically resolved aerosol size distribution and refractive index data. yielding the vertical distribution of aerosol optical properties required for the determination of aerosol-induced radiative flux changes.

Redemann, J.↗
NASA NTRS2000

Retrieving the Vertical Structure of the Effective Aerosol Complex Index of Refraction from a Combination of Aerosol in Situ and Remote Sensing Measurements During TARFOX

The largest uncertainty in estimates of the effects of atmospheric aerosols on climate stems from uncertainties in the determination of their microphysical properties, including the aerosol complex index of refraction, which in turn determines their optical properties. A novel technique is used to estimate the aerosol complex index of refraction in distinct vertical layers from a combination of aerosol in situ size distribution and remote sensing measurements during the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX). In particular, aerosol backscatter measurements using the NASA Langley LASE (Lidar Atmospheric Sensing Experiment) instrument and in situ aerosol size distribution data are utilized to derive vertical profiles of the 'effective' aerosol complex index of refraction at 815 nm (i.e., the refractive index that would provide the same backscatter signal in a forward calculation on the basis of the measured in situ particle size distributions for homogeneous, spherical aerosols). A sensitivity study shows that this method yields small errors in the retrieved aerosol refractive indices, provided the errors in the lidar derived aerosol backscatter are less than 30% and random in nature. Absolute errors in the estimated aerosol refractive indices are generally less than 0.04 for the real part and can be as much as 0.042 for the imaginary part in the case of a 30% error in the lidar-derived aerosol backscatter. The measurements of aerosol optical depth from the NASA Ames Airborne Tracking Sunphotometer (AATS-6) are successfully incorporated into the new technique and help constrain the retrieved aerosol refractive indices. An application of the technique to two TARFOX case studies yields the occurrence of vertical layers of distinct aerosol refractive indices. Values of the estimated complex aerosol refractive index range from 1.33 to 1.45 for the real part and 0.001 to 0.008 for the imaginary part. The methodology devised in this study provides, for the first time a complete set of vertically resolved aerosol size distribution and refractive index data, yielding the vertical distribution of aerosol optical properties required for the determination of aersol-induced radiative flux changes

Redemann, J.↗
NASA NTRS2019

Intercomparison of Aerosol Volume Size Distributions Derived from AERONET Ground-Based Remote Sensing and LARGE in Situ Aircraft Profiles During the 2011–2014 DRAGON and DISCOVER-AQ Experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).

Schafer, Joel S.↗
NASA NTRS2017

Accurate Characterization of Rain Drop Size Distribution Using Meteorological Particle Spectrometer and 2D Video Disdrometer for Propagation and Remote Sensing Applications

Accurate measurements of rain drop size distributions (DSD), with particular emphasis on small and tiny drops, are presented. Measurements were conducted in two very different climate regions, namely Northern Colorado and Northern Alabama. Both datasets reveal a combination of (i) a drizzle mode for drop diameters less than 0.7 mm and (ii) a precipitation mode for larger diameters. Scattering calculations using the DSDs are performed at S and X bands and compared with radar observations for the first location. Our accurate DSDs will improve radar-based rain rate estimates as well as propagation predictions.

disdrometer↗
DOE OSTI2023

Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays”. In the the four-year effort, VT-CPT collaborated with the Departments of Mathmatics at VT and Sentek Instrument, LLC (Sentek) to develop a fiber-optic sensing system capable of real-time simultaneous distributed measurement of multiple subsurface, drilling, and production parameters. The ultra-sensitive fiber optic distributed acoustic sensing technology, picoDAS, developed by Sentek was integrated with a novel multi-material optical sensing fiber fabricated by CPT-VT to obtain distributed acoustic and magnetic field measurements with ultrahigh sensitivity and high spatial resolution. The sensing technology successfully developed and demonstrated under this research program is truly unique has application beyond subsurface imaging to include carbon storage and electrical grid monitoring, as well as healthcare and nuclear fusion. The project, sponsored by the Advanced Technology Program, began in 2019 and had the original goal of developing the next generation of harsh environment sensing systems. Exhaustive theoretical modeling was performed to optimize the multi-material optical fiber design. VT developed the processing techniques employed to successfully fabricate single mode fibers with metal cladding wires. Sensing fibers with nickel and Metglas cladding wires were fully characterized, inscribed with sensors, and fully integrated with the picoDAS system. Laboratory scale testing was performed to demonstrate performance upon exposure to lateral and transverse magnetic fields. Preliminary field trials were performed for prototype magnetic and acoustic sensing systems upon near surface deployment at VT. The distributed acoustic and magnetic field sensing system was advanced from a (Technology Readiness Level) TRL=2 to a TRL=5 via laboratory scale system validation in relevant environments. The truly one-of-its kind distributed magnetic and acoustic sensing system is expected to find immediate applications that require subsurface monitoring, to include carbon storage site monitoring, and has the potential to be a distributive technology in healthcare and electric grid markets. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future by ensuring affordable, abundant, and reliable energy that drives a robust economy and national security. Technical accomplishments during the program are summarized briefly here and described in detail in the remainder of the report.

02 PETROLEUM↗
NASA NTRS1975

Quantitative suspended sediment mapping using aircraft remotely sensed multispectral data

Suspended sediment is an important environmental parameter for monitoring water quality, water movement, and land use. Quantitative suspended sediment determinations were made from analysis of aircraft remotely sensed multispectral digital data. A statistical analysis and derived regression equation were used to determine and plot quantitative suspended sediment concentration contours in the tidal James River, Virginia, on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was adequate for determining suspended sediment concentrations. A correlation coefficient of 0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentrations up to about 50 mg/l. Other water quality parameters - secchi disc depth and chlorophyll - also had high correlations with the remotely sensed data. Particle size distribution had only a fair correlation with the remotely sensed data.

Johnson, R. W.↗
NASA NTRS2000

Incremental Parallelization of Non-Data-Parallel Programs Using the Charon Message-Passing Library

Message passing is among the most popular techniques for parallelizing scientific programs on distributed-memory architectures. The reasons for its success are wide availability (MPI), efficiency, and full tuning control provided to the programmer. A major drawback, however, is that incremental parallelization, as offered by compiler directives, is not generally possible, because all data structures have to be changed throughout the program simultaneously. Charon remedies this situation through mappings between distributed and non-distributed data. It allows breaking up the parallelization into small steps, guaranteeing correctness at every stage. Several tools are available to help convert legacy codes into high-performance message-passing programs. They usually target data-parallel applications, whose loops carrying most of the work can be distributed among all processors without much dependency analysis. Others do a full dependency analysis and then convert the code virtually automatically. Even more toolkits are available that aid construction from scratch of message passing programs. None, however, allows piecemeal translation of codes with complex data dependencies (i.e. non-data-parallel programs) into message passing codes. The Charon library (available in both C and Fortran) provides incremental parallelization capabilities by linking legacy code arrays with distributed arrays. During the conversion process, non-distributed and distributed arrays exist side by side, and simple mapping functions allow the programmer to switch between the two in any location in the program. Charon also provides wrapper functions that leave the structure of the legacy code intact, but that allow execution on truly distributed data. Finally, the library provides a rich set of communication functions that support virtually all patterns of remote data demands in realistic structured grid scientific programs, including transposition, nearest-neighbor communication, pipelining, gather/scatter, and redistribution. At the end of the conversion process most intermediate Charon function calls will have been removed, the non-distributed arrays will have been deleted, and virtually the only remaining Charon functions calls are the high-level, highly optimized communications. Distribution of the data is under complete control of the programmer, although a wide range of useful distributions is easily available through predefined functions. A crucial aspect of the library is that it does not allocate space for distributed arrays, but accepts programmer-specified memory. This has two major consequences. First, codes parallelized using Charon do not suffer from encapsulation; user data is always directly accessible. This provides high efficiency, and also retains the possibility of using message passing directly for highly irregular communications. Second, non-distributed arrays can be interpreted as (trivial) distributions in the Charon sense, which allows them to be mapped to truly distributed arrays, and vice versa. This is the mechanism that enables incremental parallelization. In this paper we provide a brief introduction of the library and then focus on the actual steps in the parallelization process, using some representative examples from, among others, the NAS Parallel Benchmarks. We show how a complicated two-dimensional pipeline-the prototypical non-data-parallel algorithm- can be constructed with ease. To demonstrate the flexibility of the library, we give examples of the stepwise, efficient parallel implementation of nonlocal boundary conditions common in aircraft simulations, as well as the construction of the sequence of grids required for multigrid.

VanderWijngaart, Rob F.↗