SEARCH · Engineering Papers

Results for “Remote Access”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Energy Efficiency Assistance for Galena Alaska

The City of Galena sits along the north bank of the Yukon River with no road access. Temperatures regularly reach negative 20°F in the winter and sunlight extends for up to 21 hours a day in the summer. Galena’s 400 residents, including members of the Koyukuk Athabascan culture, primarily use fuel oil and locally forested wood for heating and electricity generation. Because these resources are costly to obtain, local households have a high energy burden, spending 7% of their annual income on energy (averaging $4,000 per year). To reduce this burden, the City of Galena joined the U.S. Department of Energy’s (DOE) Remote Alaska Community Energy Efficiency (RACEE) Competition, where they received financial and technical assistance to implement energy savings solutions across their community, including building envelope improvements, solar panels, and LED lighting. Additionally, Galena installed new energy monitoring equipment to continue measuring the impacts of this work beyond the RACEE project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Investigating the Applications of In-Situ Resource Utilization for Future Crewed Mars Missions

Several advancements are necessary before humans can safely explore Mars. One emerging strategy is In-Situ Resource Utilization (ISRU): the process of extracting raw materials found onsite and converting them into usable products to ensure a constant flow of vital resources and greatly reduce overall mission cost. Scientists must confirm the presence and accessibility of these resources for future crewed missions. Our team investigated the feasibility of ISRU in NE Syrtis, a region of Mars with varied geology, mineralogy, and hydrological history. NE Syrtis has abundant subsurface water and a diverse suite of mineral deposits including olivine, phyllosilicates, sulfates, and carbonates–all of which can be leveraged for fuel, medical supplies, and/or construction materials. We conceptualized a joint rover and helicopter expedition to analyze and sample these minerals over a two-year primary mission using Java Mission-planning and Analysis for Remote Sensing (JMARS), Planetary Data Systems (PDS), and Computer-Aided Design (CAD). We plotted a strategic traverse to regions of interest identified from remote sensing data and planned operations at each target. Our mission aimed to prepare for human presence on Mars by demonstrating the utility and viability of ISRU-focused operations.

Zahra M. Ronizi↗

DOE OSTI2021

Open Data and Deep Semantic Segmentation for Automated Extraction of Building Footprints

Advances in machine learning and computer vision, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics, cost-effectively, and at scale. These characteristics are relevant to a variety of urban and energy applications, yet are time consuming and costly to acquire with today’s manual methods. Several recent research studies have shown that in comparison to more traditional methods that are based on features engineering approach, an end-to-end learning approach based on deep learning algorithms significantly improved the accuracy of automatic building footprint extraction from remote sensing images. However, these studies used limited benchmark datasets that have been carefully curated and labeled. How the accuracy of these deep learning-based approach holds when using less curated training data has not received enough attention. The aim of this work is to leverage the openly available data to automatically generate a larger training dataset with more variability in term of regions and type of cities, which can be used to build more accurate deep learning models. In contrast to most benchmark datasets, the gathered data have not been manually curated. Thus, the training dataset is not perfectly clean in terms of remote sensing images exactly matching the ground truth building’s foot-print. A workflow that includes data pre-processing, deep learning semantic segmentation modeling, and results post-processing is introduced and applied to a dataset that include remote sensing images from 15 cities and five counties from various region of the USA, which include 8,607,677 buildings. The accuracy of the proposed approach was measured on an out of sample testing dataset corresponding to 364,000 buildings from three USA cities. The results favorably compared to those obtained from Microsoft’s recently released US building footprint dataset.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

JPL activities on development of acousto-optic tunable filter imaging spectrometer

Recent activities of JPL in the development of a new type of imaging spectrometers for earth observation and planetary exploration are reported. This instrument uses the acousto-optic tunable filter (AOTF) as high resolution and fast programmable bandpass filter. AOTF operates in the principle of acousto-optic interaction in an anisotropic medium. This filter can be tuned in sequential, random, and multiwavelength access modes, providing observational flexibility. The diffraction process in the filter generates two diffracted monochromatic beams with polarization orthogonal to each other, creating a unique capability to measure both polarimetric and spectral properties of the incoming light simultaneously with a single instrument. The device gives wide wavelength operations with reasonably large throughput. In addition, it is in a compact solid-state structure without moving parts, providing system reliability. These attractive features give promising opportunities to develop a new generation of airborne/spaceborne and ground, real-time, imaging spectrometer systems for remote sensing applications.

Cheng, Li-Jen↗

DOE OSTI2016

NORM Concentration Determination in Common Materials in an Urban Environment

The United States government performs searches for illicit radiation sources before and during large special events, such as State of the Union addresses, presidential inaugurations, or the recent papal visit. Clear detection of sources is difficult due to natural background radiation, which can vary greatly throughout a given search area. Background radiation is mostly a function of the materials used in roadways, sidewalks, and building exteriors. A team of scientists from Oak Ridge National Laboratory (ORNL), Lawrence Livermore National Laboratory (LLNL), the Remote Sensing Laboratory (RSL), and Lawrence Berkeley National Laboratory (LBNL) is exploring the nature and variability of background count rates in order to improve the performance of searches in urban areas. A series of background measurements have been and will continue to be taken at a Military Operations on Urban Terrain (MOUT) environment at the Fort Indiantown Gap (FTIG) National Guard training facility in Pennsylvania. This site replicates a small town with asphalt roads, concrete intersections, buildings, sidewalks, curbs, and gravel parking areas. Unlike an actual urban area, traffic and pedestrian access can be easily controlled to avoid interference with measurements. This paper documents the efforts focused on characterizing the various concentrations of radioactive material found in these materials at the site. The NORM concentrations determined from this work will be incorporated in to a large-scale simulation (a 'virtual test-bed') that can be used to investigate various search techniques and algorithms, detector suite configurations, and to produce representative synthetic data for future work. A combination of measurement and simulation was used to determine the concentration of {sup 40}K and the radioactive nuclides in the uranium series and the thorium series in several materials at the FTIG MOUT site. The predicted concentrations are consistent with other published results, and they matched favorably with synthetic data generated with MCNP6 models using the determined NORM concentrations and estimates of the FTIG environment as described by available construction plans and using standard material assumptions. Future measurements will incorporate lessons learned from this study. More measurements will be made of the concrete intersections at the site. The methodology explained in this report will also be carried out on building materials in an effort to characterize NORM concentrations in these background sources. Other modeling and simulation work that should be conducted includes a robust sensitivity analysis in which the effects of small changes to the model (and measurement) system can be characterized to help bound the uncertainty on the final NORM concentration predictions. (authors)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

In-vacuum multi-modal monochromator for synchrotron-based hard x-ray micro-imaging

The original monochromator design we present consists in a high-vacuum vessel comprising three monochromators mounted side-by-side: a Lauë/Lauë, a Bragg/Bragg, and a double-multilayer monochromator. The selection of one monochromator type is done remotely by sliding laterally the crystal support in the monochromator vessel. In this way, exotic combinations such as Lauë/Bragg are also possible. Installation and commissioning of the new monochromator at ESRF beamline ID19 was carried out 2013-2014 (the multilayers not being installed yet). Beamline ID19 offers not only superb beam characteristics for phase-contrast imaging with a high level of sensitivity but also compared to other synchrotron X-ray imaging facilities a large beam of currently up to 7 cm × 1.3 cm. A wide energy range can be accessed in a fixed-exit mode (depending on the optics chosen the accessible energy range is between 10 keV and 200 keV). A beryllium exit window (10 cm × 10 cm active opening) completes the monochromator assembly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1993

Polarimetric Multispectral Imaging Technology

The Jet Propulsion Laboratory is developing a remote sensing technology on which a new generation of compact, lightweight, high-resolution, low-power, reliable, versatile, programmable scientific polarimetric multispectral imaging instruments can be built to meet the challenge of future planetary exploration missions. The instrument is based on the fast programmable acousto-optic tunable filter (AOTF) of tellurium dioxide (TeO2) that operates in the wavelength range of 0.4-5 microns. Basically, the AOTF multispectral imaging instrument measures incoming light intensity as a function of spatial coordinates, wavelength, and polarization. Its operation can be in either sequential, random access, or multiwavelength mode as required. This provides observation flexibility, allowing real-time alternation among desired observations, collecting needed data only, minimizing data transmission, and permitting implementation of new experiments. These will result in optimization of the mission performance with minimal resources. Recently we completed a polarimetric multispectral imaging prototype instrument and performed outdoor field experiments for evaluating application potentials of the technology. We also investigated potential improvements on AOTF performance to strengthen technology readiness for applications. This paper will give a status report on the technology and a prospect toward future planetary exploration.

Cheng, L.-J.↗

NASA NTRS1993

Shell stability analysis in a computer aided engineering (CAE) environment

The development of 'DISDECO', the Delft Interactive Shell DEsign COde is described. The purpose of this project is to make the accumulated theoretical, numerical and practical knowledge of the last 25 years or so readily accessible to users interested in the analysis of buckling sensitive structures. With this open ended, hierarchical, interactive computer code the user can access from his workstation successively programs of increasing complexity. The computational modules currently operational in DISDECO provide the prospective user with facilities to calculate the critical buckling loads of stiffened anisotropic shells under combined loading, to investigate the effects the various types of boundary conditions will have on the critical load, and to get a complete picture of the degrading effects the different shapes of possible initial imperfections might cause, all in one interactive session. Once a design is finalized, its collapse load can be verified by running a large refined model remotely from behind the workstation with one of the current generation 2-dimensional codes, with advanced capabilities to handle both geometric and material nonlinearities.

Arbocz, J.↗

NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗

DOE OSTI2016

Twin related domains in 3D microstructures of conventionally processed and grain boundary engineered materials

The concept of twin-limited microstructures has been explored in the literature as a crystallographically constrained grain boundary network connected via only coincident site lattice (CSL) boundaries. The advent of orientation imaging has made classification of twin-related domains (TRD) or any other orientation cluster experimentally accessible in 2D using EBSD. With the emergence of 3D orientation mapping, a comparison of TRDs in measured 3D microstructures is performed in this paper and compared against their 2D counterparts. The TRD analysis is performed on a conventionally processed (CP) and a grain boundary engineered (EM) high purity copper sample that have been subjected to successive anneal procedures to promote grain growth. Finally, the EM sample shows extremely large TRDs which begin to approach that of a twin-limited microstructure, while the TRDs in the CP sample remain relatively small and remote.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Pioneer Design of Non-contact Synchronized Measurement Devices Using Electric and Magnetic Field Sensors

Here, traditional synchrophasors rely on CTs and PTs physically connected to transmission lines or buses to acquire input signals for phasor measurement. However, it is challenging to install and maintain traditional phasor measurement units in some remote areas due to lack of facilities. Since transmission lines naturally generate alternating electrical and magnetic fields in the surrounding atmosphere, this paper presents two innovative designs for non-contact synchronized measurement devices (NCSMD), including an electric field sensor based non-contact SMD (E-NCSMD) and a magnetic field sensor based non-contact SMD (M-NCSMD). Compared with conventional synchrophasors, E-NCSMD and M-NCSMD are much more flexible to be deployed and have much lower costs, making E-NCSMDs and M-NCSMD highly accessible and useful for a wide array of phasor measurement applications. Laboratory and field experiment results verified the effectiveness of the designs of both E-NCSMD and M-NCSMD.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Transmission Challenges and Best Practices for Cost-Effective Renewable Energy Delivery across State and Provincial Boundaries

A strategically planned transmission network is an important source of flexibility for the integration of large-scale renewable energy (RE). Such a network can offer access to a broad geographic diversity of resources, which can reduce flexibility needs and facilitate sharing between neighboring balancing areas. This report builds on two previous NREL technical reports - Advancing System Flexibility for High Penetration Renewable Integration (Milligan et al. 2015) and 'Renewables-Friendly' Grid Development Strategies (Hurlbut et al. 2015) - which discuss various flexibility options and provide an overview of U.S. market models and grid planning. This report focuses on addressing issues with cross-regional/provincial transmission in China with the aim of integrating renewable resources that are concentrated in remote areas and require inter-regional/provincial power exchange.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Transmission Challenges and Best Practices for Cost-Effective Renewable Energy Delivery across State and Provincial Boundaries

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

SMC Reinforced by Recycled or Textile Carbon Fiber

There is a significant need to expand material options for SMC that has traditionally used glass fibers for decades. There are several integral issues related to chopping and conveying a range of materials including glass, carbon, basalt, thermoplastic tapes, and recycled fibers. These are in a variety of forms including continuous tows, discontinuous agglomerates such as pyrolyzed carbon fibers that could be used to produce a range of SMC intermediates. Standard/conventional SMC processing is limited to cutting rotors specifically for glass and compounding with thermoset polyesters and some epoxies. The multi-material, multi-format line developed in this project is flexible to enable custom conveying and uses an interchangeable rotor dedicated for specific material types. The overall tasks undertaken in this project included: evaluation of the fiber feed mechanism, effect of textile grade carbon, evaluating servo motor controlling of conveyor, evaluate doctor box resin feed, evaluate compaction unit, evaluation of different formulations, and develop automation such as PLC programming. The new multi-material SMC line Version 2 (SCM-V2) incorporated servo motors over induction motors which gave the overall cutter system precision control and made it quiet. The addition of a 14-roll compaction unit at the end of the line in SMC-V2 enabled higher material wet out which was a limitation in the SMC Version 1 (SMC-V1). The cutters were further updated to reduce the cantilever overhang of the fiber which enabled more uniform cut lengths for glass, carbon, and basalt fibers. The overall instrumentation and system control including a remote control operation was enabled in the SMC-V2. The line speed is capable of 10-20 ft/minute. The cutting modules were designed and engineered for cutting glass, basalt and textile grade carbon in 300k and 450-600k format widths. The cutting trials were established for a range of fiber types. The study also demonstrated the utility of the line to cut and produce basalt fiber SMC. Initial trials were conducted on the properties from recycled carbon fiber (rCF) mats in epoxy resin. Overall, the Covid19 situation constrained the team from accessing the SMC line for over 18 months. Despite this challenge major advancements were made.

36 MATERIALS SCIENCE↗

NASA NTRS2006

The Echoes of Earth Science

NASA s Earth Observing System Data and Information System (EOSDIS) acquires, archives, and manages data from all of NASA s Earth science satellites, for the benefit of the Space Agency and for the benefit of others, including local governments, first responders, the commercial remote sensing industry, teachers, museums, and the general public. EOSDIS is currently handling an extraordinary amount of NASA scientific data. To give an idea of the volume of information it receives, NASA s Terra Earth-observing satellite, just one of many NASA satellites sending down data, sends it hundreds of gigabytes a day, almost as much data as the Hubble Space Telescope acquires in an entire year, or about equal to the amount of information that could be found in hundreds of pickup trucks filled with books. To make EOSDIS data completely accessible to the Earth science community, NASA teamed up with private industry in 2000 to develop an Earth science "marketplace" registry that lets public users quickly drill down to the exact information they need. It also enables them to publish their research and resources alongside of NASA s research and resources. This registry is known as the Earth Observing System ClearingHOuse, or ECHO. The charter for this project focused on having an infrastructure completely independent from EOSDIS that would allow for more contributors and open up additional data access options. Accordingly, it is only fitting that the term ECHO is more than just an acronym; it represents the functionality of the system in that it can echo out and create interoperability among other systems, all while maturing with time as industry technologies and standards change and improve.

Source record↗

NASA NTRS2019

The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES): Science Motive and Mission Overview

The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) is an interdisciplinary investigation to improve understanding of Earth's ocean ecosystem-aerosol-cloud system. Specific overarching science objectives for NAAMES are to (1) characterize plankton ecosystem properties during primary phases of the annual cycle and their dependence on environmental forcings, (2)determine how these phases interact to recreate each year the conditions for an annual plankton bloom, and (3) resolve how remote marine aerosols and boundary layer clouds are influenced by plankton ecosystems. Four NAAMES field campaigns were conducted in the western subarctic Atlantic between November 2015 and April 2018, with each campaign targeting specific seasonal events in the annual plankton cycle. A broad diversity of measurements were collected during each campaign, including ship, aircraft, autonomous float and drifter, and satellite observations. Here, we present an overview of NAAMES science motives, experimental design, and measurements. We then briefly describe conditions and accomplishments during each of the four field campaigns and provide information on how to access NAAMES data. The intent of this manuscript is to familiarize the broad scientific community with NAAMES and to provide a common reference overview of the project for upcoming publications.

Behrenfeld, Michael J.↗

NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

DOE OSTI2018

Machine learning to classify animal species in camera trap images: Applications in ecology

Motion-activated cameras (“camera traps”) are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses. We trained machine learning models using convolutional neural networks with the ResNet-18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out-of-sample (or “out-of-distribution” in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out-of-sample dataset from Tanzania, containing a faunal community that was novel to the model. The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out-of-sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies. The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non-invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our r package makes these methods accessible to ecologists.

54 ENVIRONMENTAL SCIENCES↗