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At least 1,153 records · Page 64

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Associations between Frequency of Culinary Herb Use and Gut Microbiota

While evidence suggests that culinary herbs have the potential to modulate gut microbiota, much of the current research investigating the interactions between diet and the human gut microbiome either largely excludes culinary herbs or does not assess use in standard culinary settings. As such, the primary objective of this study was to evaluate how the frequency of culinary herb use is related to microbiome diversity and the abundance of certain taxa, measured at the phylum level. In this secondary data analysis of the INCLD Health cohort, we examined survey responses assessing frequency of culinary herb use and microbiome analysis of collected stool samples. We did not observe any associations between frequency of culinary herb use and Shannon Index, a measure of alpha diversity. Regarding the abundance of certain taxa, the frequency of use of polyphenol-rich herbs and herbs with certain quantities of antibacterial compounds was positively associated with Firmicutes abundance, and negatively associated with Proteobacteria abundance. Additionally, the total number of herbs used with high frequency, defined as over three times per week, was also positively associated with Firmicutes abundance, independent of adjustments, and negatively associated with Proteobacteria abundance, after adjusting for dietary factors. Frequency of culinary herb use was not associated with Bacteroidota or Actinobacteria abundance.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Deep Learning for Land Cover Classification Using Only a Few Bands

There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information and thus help improve the land cover classification performance. Although hyperspectral data with hundreds of channels provide detailed spectral signatures, the curse of dimensionality might lead to degradation in the land cover classification performance. Moreover, in some practical applications, hyperspectral data may not be available due to cost, data storage, or bandwidth issues, and RGB and near infrared (NIR) could be the only image bands available for land cover classification. Light detection and ranging (LiDAR) data is another type of data to assist land cover classification especially if the land covers of interest have different heights. In this paper, we examined the performance of two Convolutional Neural Network (CNN)-based deep learning algorithms for land cover classification using only four bands (RGB+NIR) and five bands (RGB+NIR+LiDAR), where these limited number of image bands were augmented using Extended Multi-attribute Profiles (EMAP). The deep learning algorithms were applied to a well-known dataset used in the 2013 IEEE Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest. With EMAP augmentation, the two deep learning algorithms were observed to achieve better land cover classification performance using only four bands as compared to that using all 144 hyperspectral bands.

58 GEOSCIENCES↗

DOE OSTI2022

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Ozone Gas: Scientific Justification and Practical Guidelines for Improvised Disinfection using Consumer-Grade Ozone Generators and Plastic Storage Boxes

Here, we describe direct measurements of ozone concentration achievable in small enclosed containers (plastic storage boxes) for use as improvised decontamination systems for small articles such as disposable PPE (N95 masks, nitrile gloves, etc.), clothing, mail and small packages, food, and other miscellaneous articles. The emphasis is on the reliable and sustained generation of ozone gas concentrations of sufficient concentration and duration to create an effective virucidal environment to achieve more than 95% to 99% viral inactivation, based upon the data already published in the peer-review literature on this topic. The suggestion that ozone be used to inactivate virus is certainly not a new idea. Our objective in this report is to make clear that the necessary levels of ozone can be improvised using simple, easy-to-use, inexpensive, and widely available supplies, and that there is every theoretical and experimental reason to believe that this approach is as highly effective in viral inactivation by ozone as are the far more expensive, complex, cumbersome, and less available equivalent ozone (and other) disinfectant systems that have themselves become unavailable during times of pandemic crisis. Using multiple types of readily available commercial ozone generators, concentration in the tested improvised enclosure is tracked over time to assess ozone charging and decay rates, and the ozone quenching effects of items placed in the box. Generator performance is compared against published ozone dosage values for virucidal and antimicrobial activity. Bubbler and box-fan-type ozone generators were found to be effective at achieving and maintaining target concentrations of 10ppm ozone or higher, whereas automotive cigarette lighter and universal serial bus type plug in “air freshener” ozone generators could not achieve the target concentrations in these experiments. Calculations and practical guidelines for assembly and effective use of an ozone box for improvised decontamination are offered. The majority of this report is directed toward the scientific justification and rationale for this approach. The end of the document summarizes the findings and offers simplified designs for the construction and use of ozone boxes as an improvised method of disinfection.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Mapping of Benthic Habitats at Marine Renewable Energy Sites Using Multibeam Echosounder and Sediment Profile Imaging Technologies

Objectives/Scope: The goal of this work was to develop a consistent and semi-automated seafloor survey method for generating high-resolution, benthic habitat maps for environmental assessments and monitoring of marine renewable energy sites. Sediment profile and plan view imaging (SPI/PV) technology was combined with multibeam bathymetry and acoustic backscatter methods to demonstrate a rapid, cost-effective benthic mapping protocol. A key technical innovation of this project was the development of an image processing platform that automatically measures key features from the images. Methods: Multibeam echosounder (MBES) acoustic and SPI/PV surveys were conducted at three coastal areas off the U.S. west coast, including the PacWave South energy test site off of Newport, Oregon. Point data on physical and biological sediment conditions obtained from the SPI/PV imagery were used to efficiently ground-truth the high-resolution MBES bathymetry and backscatter mosaics. The SPI camera is an optical corer that obtains an undisturbed 21 by 15 cm, high-resolution, cross-sectional image of the sediment–water interface and upper sediment column. The plan view camera attached to the SPI camera frame captures a downward looking view of the seabed immediately before the SPI image is obtained. As part of this project, we developed a computer vision image processing platform (iSPI) that uses deep convolutional neural networks and other approaches to automatically identify and measure key features in the images, such as grain size and surface relief. Results: Detailed benthic habitat maps were generated using this mapping approach for three different marine settings. The sites mapped included a silt-dominated embayment; a sloping, nearshore, transitional very fine to coarse sand bottom; and a medium, sand-dominated continental shelf marine energy test site. In each case, acoustic and imaging surveys were completed in less than week, and detailed benthic habitat maps were generated within 60 days. The results were placed within the Coastal and Marine Ecological Classification Standard (CMECS) habitat mapping framework, and various combinations of the bathymetry, backscatter, and SPI and PV data were used to generate CMECS component maps. Novel Information: This project developed and demonstrated a repeatable and cost-effective approach for efficiently mapping benthic habitat conditions over broad areas of the seafloor by combining state-of-the-art acoustic and imaging techniques. The primary survey tools used in this project have been used previously in both the offshore renewable (wind) and oil and gas sectors to map and monitor benthic environments. This project’s innovations include 1) the focused use of high-resolution SPI/PV imagery to ground-truth acoustic mosaics, and 2) the development of a computer automated image analysis processing tool that both streamlines and standardizes the generation of data from the imagery and makes the data extraction process more cost-effective and repeatable.

13 HYDRO ENERGY↗

DOE OSTI2022

An Investigation into the Effects of Swirl on the Performance and Emissions of an Opposed-Piston Two-Stroke Engine using Large Eddy Simulations

Opposed-piston two-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a conventional four-stroke diesel engine. However, the uniflow scavenging process is difficult to control over a wider range of speed and loads due to its sensitivity to pressure dynamics, port timings, and port design. Specifically, the angle of the intake ports can be used to generate swirl which has implications for open and closed cycle effects. This study proposes an analysis of the effects of port angle on the in-cylinder flow distribution and combustion performance of an OP-2S using computational fluid dynamics engine. Large Eddy Simulation (LES) was used to model turbulence given its ability to predict in-cylinder mixing and cyclic variability. A three-cylinder model was validated to experimental data collected by Achates Power and the grid was verified using an LES quality approach from the literature. The model was used to simulate port angles from 12 to 29 degrees at constant pressure and temperature boundary conditions. Results indicated that the higher bulk swirl ratio generated by larger port angles tends to trap more internal residuals. This effect on the scavenging performance, combined with the larger trapped swirl ratio, also has a significant impact on the combustion performance in a two-stroke engine. It was concluded that there exists a tradeoff of efficiency and emissions that must be considered when increasing the port angle in a uniflow two-stroke engine. 1. Introduction Two-stroke engines were developed in the 1800s and are commonly used in practice today for lightweight power applications such as motorcycles or handheld power tools, as well as large-bore low speed engines for stationary power and marine applications. Two-stroke engines provide the distinct advantage of higher torque/power output but present challenges due to its coupled intake and exhaust process. Four-stroke engines have the benefit of using two full piston strokes to induct intake charge and to expel exhaust gases. Controlling the trapped charge composition in a twostroke engine via a scavenging process is crucial for reliable and efficient engine operation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.

Brown, Nicolas E.↗

DOE OSTI2022

Sizing ice hydrometeor populations using the dual-wavelength radar ratio

Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, D v , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of D v retrievals using DWR are around 0.6 mm when D v is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as D v , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Photogrammetry using Apollo 16 orbital photography, part B

Discussion is made of the Apollo 15 and 16 metric and panoramic cameras which provided photographs for accurate topographic portrayal of the lunar surface using photogrammetric methods. Nine stereoscopic models of Apollo 16 metric photographs and three models of panoramic photographs were evaluated photogrammetrically in support of the Apollo 16 geologic investigations. Four of the models were used to collect profile data for crater morphology studies; three models were used to collect evaluation data for the frequency distributions of lunar slopes; one model was used to prepare a map of the Apollo 16 traverse area; and one model was used to determine elevations of the Cayley Formation. The remaining three models were used to test photogrammetric techniques using oblique metric and panoramic camera photographs. Two preliminary contour maps were compiled and a high-oblique metric photograph was rectified.

Wu, S. S. C.↗

NASA NTRS1974

Some findings on the applications of ERTS and Skylab imagery for metropolitan land use analysis

The author has identified the following significant results. Work undertaken on a three-sensor land use data evaluation for a portion of the Phoenix area is reported. Analyses between land use data generated from 1970 high altitude photography and that detectable from ERTS and Skylab, especially in terms of changes in land use indicate that ERTS and Skylab imagery can be used effectively to detect and identify areas of post-1970 land use change, especially those documenting urban expansion at the rural-urban fringe. Significant preliminary findings on the utility of ERTS and Skylab data for metropolitan land use analysis, substantiated by evaluation with 1970 and 1972 ground control land use data are reported.

Alexander, R. H.↗

NASA NTRS1974

Extracting land use information from the earth resources technology satellite data by conventional interpretation methods

A procedure for obtaining land use data from satellite imagery by the use of conventional interpretation methods is presented. The satellite is described briefly, and the advantages of various scales and multispectral scanner bands are discussed. Methods for obtaining satellite imagery and the sources of this imagery are given. Equipment used in the study is described, and samples of land use maps derived from satellite imagery are included together with the land use classification system used. Accuracy percentages are cited and are compared to those of a previous experiment using small scale aerial photography.

Vegas, P. L.↗

NASA NTRS1974

Computer-implemented land use classification with pattern recognition software and ERTS digital data

Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

Joyce, A. T.↗

NASA NTRS1974

Land use and mapping

The ERTS program provides data that can be used to derive information relative to the actual use of the land resource, in a practical and timely manner. ERTS data provide coverage of total land areas, and its repetitive nature enables the detection and monitoring of changes taking place in land use. Generally, the techniques and the procedures used to extract information from ERTS data may be categorized as pertaining to either the interpretations of ERTS imagery or to the use of digital data and computer techniques. Examples are given of the use of ERTS-1 data for land use classification in: (1) New England areas; (2) Chesapeake Bay and Washington, D.C.; (3) Mississippi Gulf Coast; (4) Los Angeles, California; (5) Houston, Texas; and (6) Phoenix, Arizona.

Joyce, A. T.↗

NASA NTRS1974

Computer and photogrammetric general land use study of central north Alabama

The object of this report is to acquaint potential users with two computer programs, developed at NASA, Marshall Space Flight Center. They were used in producing a land use survey and maps of central north Alabama from Earth Resources Technology Satellite (ERTS) digital data. The report describes in detail the thought processes and analysis procedures used from the initiation of the land use study to its completion, as well as a photogrammetric study that was used in conjunction with the computer analysis to produce similar land use maps. The results of the land use demonstration indicate that, with respect to computer time and cost, such a study may be economically and realistically feasible on a statewide basis.

Jayroe, R. R.↗

NASA NTRS1975

Photomorphic mapping for land-use planning

A comparison of different land types based on their physical and environmental characteristics is seen as a useful, if not vital, element of land-use planning decisions. The use of the photomorphic-mapping technique is described in order to delineate and compare the different land types in Boulder County, Colorado, according to their constraints and values for agricultural and urban uses. Employing high-altitude color infrared aerial photography of Boulder County at a scale of 1:100,000, photomorphic areas were delineated according to similarities in pattern, tone, and texture on the photographs. The boundaries of the areas were checked and adjusted using information from thematic maps and sampling data. Constraints on specific land uses in the county could then be described on a regional basis using the photomorphic areas as a framework.

Nichol, J. E.↗

NASA NTRS1975

Land use and environmental assessment in the central Atlantic region

Data from high altitude aircraft, LANDSAT and Skylab were used in a comprehensive regional survey of land use and its associated environmental impact in the Central Atlantic Regional Ecological Test Site (CARETS). Each sensor system has advantages that were demonstrated by producing experimental land use maps and other data products, applying them to typical problems encountered in regional planning and environmental impact assessment, and presenting the results to prospective users for evaluation. An archival collection of imagery, maps, data summaries, and technical reports was assembled, constituting an environmental profile of the central Atlantic region. The investigation was organized into four closely-related modules, a land use information module, an environmental impact module, a user interaction and evaluation module, and a geographic information systems module. Results revealed a heterogeneous user community with diverse information needs, tending, however, definitely toward the higher-resolution sensor data and the larger-scale land use maps and related information products. Among project recommendations are greater efforts toward improving compatibility of federal, state, and local land use information programs, and greater efforts toward a broader exchange of imagery, computer tapes, and land use information derived therefrom.

Alexander, R. H.↗