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Hughes, David

Publications and source records attributed to Hughes, David.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Automated remote sensing tools to counter illicit maritime activity: vessel detection, bathymetry and topography from WorldView imagery

Illicit maritime activity, such as piracy and smuggling, is a global issue that often occurs in areas where interdiction authorities are sparse, ground-based monitoring technologies like radar lack range and coverage, and dark vessels abound. Our objective was to assess vessel congregation patterns, identify likely beaching areas based on terrain maps, and use them to narrow the search for potential smuggling transfer and overland routes in a specific region along the Puntland coast of Somalia. To accomplish this goal, we developed automated protocols applied to WorldView satellite imagery for (1) vessel detection and size classification, (2) shallow-water bathymetric characterization, and (3) coastal topography mapping. Utilizing a single sensor for vessel detection and topographic and bathymetric extraction at high spatial resolution and at a high re-visit rate provides a simplification to near-shore characterization for monitoring purposes. The extracted topography and bathymetry are then presented as a single, comprehensive perspective of a coastal region. The vessel-detection algorithm identified all vessels larger than approximately 15 metres in length (35 of 35), but misidentified six artefacts (i.e. false positives), resulting in an overall accuracy of 85%. The combined vessel and terrain maps facilitated the identification of a potential beaching and overland transportation route location.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗
DOE OSTI2023

UAS Edge Computing of Energy Infrastructure Damage Assessment

Energy infrastructure assessments are needed within 72 hours of natural disasters, and previous data collection methods have proven too slow. We demonstrate a scalable end-to-end solution using a prototype unmanned aerial system that performs on-the-edge detection, classification (i.e., damaged or undamaged), and geo-location of utility poles. The prototype is suitable for disaster response because it requires no local communication infrastructure and is capable of autonomous missions. Collections before, during, and after Hurricane Ida in 2021 were used to test the system. The system delivered an F1 score of 0.65 operating with a 2.7 s/frame processing speed with the YOLOv5 large model and an F1 score of 0.55 with a 0.48 s/frame with the YOLOv5 small model. Geo-location uncertainty in the bottom half of the frame was ~8 m, mostly driven by error in camera pointing measurement. With additional training data to improve performance and detect additional types of features, a fleet of similar drones could autonomously collect actionable post-disaster data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Weakly-Supervised, Multitask Deep Learning Framework for Shadow Mitigation in Remote Sensing Imagery

We propose a weakly-supervised, multitask framework for training a convolutional neural network to solve the problem of cloud shadow mitigation given only cloud and shadow masks as labels. The network minimizes the Wasserstein distance between shadows and their proximal sunlit neighborhoods, generating a supervisory signal directly from within the input image. We extract further utility from the shadow mask through multitask learning by introducing an auxiliary task of shadow segmentation. Our approach is advantageous since it performs mitigation in an end-to-end framework which requires only a shadowed image for inference. We apply this process to the Landsat 8 OLI SPARCS validation data set and demonstrate plausible results.

Couwenhoven, Scott↗
DOE OSTI2022

A microfluidic system that replicates pharmacokinetic (PK) profiles in vitro improves prediction of in vivo efficacy in preclinical models

Test compounds used on in vitro model systems are conventionally delivered to cell culture wells as fixed concentration bolus doses; however, this poorly replicates the pharmacokinetic (PK) concentration changes seen in vivo and reduces the predictive value of the data. Herein, proof-of-concept experiments were performed using a novel microfluidic device, the Microformulator, which allows in vivo like PK profiles to be applied to cells cultured in microtiter plates and facilitates the investigation of the impact of PK on biological responses. We demonstrate the utility of the device in its ability to reproduce in vivo PK profiles of different oncology compounds over multiweek experiments, both as monotherapy and drug combinations, comparing the effects on tumour cell efficacy in vitro with efficacy seen in in vivo xenograft models. In the first example, an ERK1/2 inhibitor was tested using fixed bolus dosing and Microformulator-replicated PK profiles, in 2 cell lines with different in vivo sensitivities. The Microformulator-replicated PK profiles were able to discriminate between cell line sensitivities, unlike the conventional fixed bolus dosing. In a second study, murine in vivo PK profiles of multiple Poly(ADP-Ribose) Polymerase 1/2 (PARP) and DNA-dependent protein kinase (DNA-PK) inhibitor combinations were replicated in a FaDu cell line resulting in a reduction in cell growth in vitro with similar rank ordering to the in vivo xenograft model. Additional PK/efficacy insight into theoretical changes to drug exposure profiles was gained by using the Microformulator to expose FaDu cells to the DNA-PK inhibitor for different target coverage levels and periods of time. We demonstrate that the Microformulator enables incorporating PK exposures into cellular assays to improve in vitro–in vivo translation understanding for early therapeutic insight.

Singh, Dharaminder (ORCID:0000000346306403)↗
DOE OSTI2021

SPATIOTEMPORAL TRACKING OF WIDE AREA POWER OUTAGE FROM NIGHT-TIME LIGHT IMAGERY

Monitoring progress of power restoration following extreme events is essential for situational awareness about spatio-temporal distribution of populations without power and to help with response efforts. Because of the proprietary nature of restoration data, and the difficulty in obtaining power outage data from utility companies in near real-time (e.g., during hurricane Maria (2017)), this project used satellite derived nighttime lights data from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to (i) monitor wide area power outage and (ii) estimate impacted customers over time to assist with restoration. A discussion of the methodology and its implementation during hurricanes Maria (2017) and Eta (2020) is presented in this paper. Future work will focus on calibrating estimated customers based on light intensity and density distribution, and generation of restoration profiles for emergency response.

Kar, Bandana↗
DOE OSTI2021

Microbiome Aggregated Traits and Assembly Are More Sensitive to Soil Management than Diversity

How soil is managed, particularly for agriculture, exerts stresses upon soil microbiomes, resulting in altered community structures and functional states. Understanding how soil microbiomes respond to combined stresses is important for predicting system performance under different land use scenarios, aids in identification of the most environmentally benign managements, and provides insight into how system function can be recovered in degraded soils. We use a long-established field experiment to study the effects of combined chronic (press) disturbance of the magnitude of organic carbon inputs with acute (pulse) effects of physical disturbance by tillage and chemical disturbance due to inorganic fertilization and pesticide application. We show that because of the variety of ways it can be assessed, biodiversity—here based on microbial small subunit rRNA gene phylotypes—does not provide a consistent view of community change. In contrast, aggregated traits associated with soil microbiomes indicate general loss of function, measured as a reduction of average genome lengths, associated with chronic reduction of organic inputs in arable or bare fallow soils and altered growth strategies associated with rRNA operon copy number in prokaryotes, as well as a switch to pathogenicity in fungal communities. In addition, pulse disturbance by soil tillage is associated with an increased influence of stochastic processes upon prokaryote community assembly, but fungicide used in arable soils results in niche assembly of fungal communities compared to untilled grassland. Overall, bacteria, archaea, and fungi do not share a common response to land management change, and estimates of biodiversity do not capture important facets of community adaptation to stresses adequately.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Artificial illumination identification from an unmanned aerial vehicle

Artificial illumination identification within images is a useful tool for many applications. Performing such identification allows for an estimation of the illumination source spectrum, which in turn can be used for additional applications ranging from spectral detection and exploitation to statistics about nighttime light usage. Illumination identification has been performed in laboratory settings but not from an unmanned aerial vehicle (UAV) platform. Here, we test the feasibility of using a UAV and commercial off-the-shelf multispectral imaging sensor to perform such artificial illumination identification through linear discriminant analysis using nighttime UAV images. The results are very promising, showing source classification accuracies of 83.3%, 92.3%, 100%, and 100% for the incandescent, light-emitting diode, high pressure sodium, and metal halide illumination sources, respectively. We show that the information gained from the source identification can be further used to inform additional analysis, such as spectral identification. The high resolution of UAV imaging techniques combined with the knowledge of the illumination source can lead to better exploitation of such nighttime data for many applications.

42 ENGINEERING↗
DOE OSTI2019

Integration and operation of a sUAS-based multi-modal imaging payload equipped with a novel communication system enabling autonomous platform control

Oak Ridge National Laboratory presents a new UAS-mounted multi-modal imaging payload containing five sensors. We have integrated several distinct commercially available sensors onto a large Class-1 autonomous quadcopter aircraft: a LIDAR (Light Detection and Ranging) scanner, a hyperspectral pushbroom sensor, a multispectral camera, a longwave infrared thermal camera, and an RGB camera. The system integrates our proprietary Multi-modal Autonomous Vehicle Network (MAVNet) and communication system, allowing autonomous control via multiple communication networks. Using one common Global Navigation Satellite System (GNSS) and inertial navigation system (INS/GPS), imagery from all sensors are accurately and precisely geolocated and co-registered.

Duncan, Andrew↗
NASA NTRS2018

The History & Evolution of Spacesuits and Spacewalks - Walking in Space

The presentation and videos that will be included in this technology talk will summarize the basic functions of spacesuits, the evolution of spacesuit design, and the development plans for future exploration spacesuits. The videos will run in a loop with no audio. The speakers will generally follow the slide presentation. There will be a 5-minute intro on basic suit functions, followed by a 7-10 minute discussion on suit history and evolution, then 7-10 minutes to cover the current ISS (International Space Station) suit and the development of the next generation exploration spacesuits. That will leave around 5-10 minutes for questions and answers.

Hughes, David↗
NASA NTRS2013

Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber

When contamination-sensitive hardware must be tested in a thermal vacuum chamber, cross-contamination from other hardware present in the chamber, or residue from previous tests, becomes a concern. Typical mitigation strategies involve maintaining the temperature of the critical item above that of other hardware elements at the end of the test. A formula for relating the pumping speed of a chamber, the surface area of contamination sources, and the temperatures of the chamber, source, and contamination-sensitive items has been developed. The formula allows the determination of a temperature threshold about which contamination will not condense on the sensitive items. It defines a parameter alpha that is the fraction given by (contaminant source area)/[chamber pumping speed (time under vacuum) 0.5]. If this parameter is less than 10(exp -6), cross-contamination from common spacecraft material will not occur when the sensitive hardware is at the same temperature as the source of contamination (The chamber is isothermal within 5 C.). Knowing when it becomes safe to have the hardware isothermal permits faster and easier thermal transitions when compared with maintaining an arbitrary temperature differential between parts. Furthermore, the standard temperature differential may not be adequate under some conditions (alpha>10(exp -4)).

Hughes, David↗
NASA NTRS2011

Modeling the Effects of Spacecraft Venting on Instrument Measurements of the Martian Atmosphere for an Elliptical Orbit

Analysis has been performed for MAVEN mission. Due to the elliptical orbit, large pressure variations in orbit will be experienced, there is a need to understand how internal pressures change and the flux of gas from vents could potentially bias instrument measurements. Goal of this analysis is to predict the effect that atmospheric gases trapped and vented from spacecraft volumes could have on instrument measurements.

Petro, Elaine↗
NASA NTRS2010

Analysis of Particulate Contamination During Launch of MMS Mission

NASA's Magnetospheric MultiScale (MMS) is an unmanned constellation of four identical spacecraft designed to investigate magnetic reconnection by obtaining detailed measurements of plasma properties in Earth's magnetopause and magnetotail. Each of the four identical satellites carries a suite of instruments which characterize the ambient ion and electron energy spectrum and composition. Some of these instruments utilize microchannel plates and are sensitive to particulate contamination. In this paper, we analyze the transport of particulates during pre-launch, launch and ascent events, and use the analysis to obtain quantitative predictions of contamination impact on the instruments. Viewfactor calculation is performed by considering the gravitational and aerodynamic forces acting on the particles.

Brieda, Lubos↗