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DOE OSTI2022

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Propane Fueling Infrastructure Trends: A Decade in Review

This report provides information on propane fueling infrastructure and industry trends over the last 10 years. It is informed primarily by propane fueling station location data collected through the Alternative Fuels Data Center's Alternative Fueling Station Locator from 2011 through 2021. Industry stakeholders, including the Propane Education & Research Council (PERC) and other members of the Alternative Fuels Data Center Station Locator Propane Working Group, also provided data and additional context around trends seen in the data.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

FY23 Status of Quality Assurance Plan for Out-of-Pile Test Data

The DOE Advanced Reactor Technology program has supported recovery and preservation of legacy metallic fuel data collected as part of the US fast reactor program, recognizing it as essential to development and licensing activities for advanced fast reactors. Databases were established as organized collections of experimental records and data generated from in-pile experiments at EBRII, FFTF, and TREAT as well as related out-of-pile examinations of irradiated fuels. The Out-of-Pile Transient Database (OPTD), includes records of over 150 out-of-pile furnace transient tests on metallic fuels conducted at Argonne’s Alpha-Gamma Hot Cell Facility to evaluate their transient performance and characterize fuel/cladding interaction. The database is accessible to registered users from US universities, laboratories, and nuclear industry. Because the data in OPTD has not been formally qualified, its applicability and ability to support licensing activities is limited. This report outlines progress and plans to quality assure data in OPTD, maximizing its impact for model validation and verification as well as qualification of fuels for safe and effective use in advanced reactor designs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

A New Vehicle-to-Vehicle Communication Technology Based on Binary Light Code

The proliferation of Connected and Autonomous Vehicles (CAVs) has necessitated the development of efficient, reliable communication methods between vehicles and their surroundings. This study presents a novel methodology, the VECTOR system, that addresses this need by converting dynamic vehicle data into a binary code and displaying it on an LED panel. The system involves a three-step process of data collection, polynomial fitting of velocity data, and encoding the polynomial parameters into binary form using a Cyclic Redundancy Check (CRC). The study also explores the practical application of this system by conducting experiments with modified Lincoln MKZ hybrids, demonstrating the feasibility and efficiency of this approach. The paper presents both the methodology and results of these experiments, further expanding upon the potential applications and implications for CAV technology. By comparing the final accuracy, we find this approach can achieve 80% of the original velocity data.

Ma, Ke↗

DOE OSTI2023

Energy Justice Framework for Marine Energy: Considerations from PacWave

To accelerate the energy transition while addressing land use conflicts and community opposition, federal policies and incentives require that new energy infrastructure provide direct benefits to communities, and ensure that these benefits remain in the community. The objective of this study is to develop a framework for collecting demographic, socioeconomic, and environmental data and supporting communities in understanding how such data can support more just and equitable outcomes. Specifically, this study addresses two research questions: (1) How can energy justice be incorporated into ME project life cycle, and (2) what social and economic data are needed to assess how marine energy development supports energy justice? Based on our literature review and the data collection template, a case study of PacWave, a wave energy testing facility located on the central Oregon Coast, is employed to draw more specific implications for how energy justice can be integrated into marine energy. PacWave represents a flagship investment by Oregon State University, the State of Oregon, and the Department of Energy. The facility is situated in Lincoln County, which is home to the Confederated Tribes of Siletz Indians and family-scale fishing enterprises. PacWave has strong community support as a testing site and holds potential to provide valuable lessons for other communities.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

The Jefferson Lab Eta Factory Experiment and Applications of PbWO4 Calorimeters in Future Experimental Facilities

The goal of the new JLab Eta Factory (JEF) experiment, conducted with the GlueX detector in Hall D at Jefferson Lab, is to perform measurements of various ¿(') decays with a primary focus on rare neutral modes. The experiment’s physics program ranges from precision tests of low-energy QCD to searches for gauge bosons with masses below 1 GeV that could couple the Standard Model (SM) sector to the dark sector. The experiment will collect a high-statistics data sample of ¿(') mesons produced via a beam of tagged photons. The GlueX detector features a large, nearly uniform acceptance for both neutral and charged particles, enabling efficient identification of complex multi-particle final states. To meet the requirements of the JEF experiment, the inner section of the forward lead-glass calorimeter in the GlueX detector has been upgraded with lead tungstate (PbWO4) scintillating crystals. PbWO4 offers exceptional characteristics, such as a small radiation length and Molire radius, and large light yield, that make it ideal for constructing high- granularity, high-resolution, radiation-hard detectors. These properties enable excellent spatial separation and energy resolution of reconstructed electromagnetic showers, establishing PbWO4 as the material of choice for many high-precision experiments. The JEF experiment began data collection in April 2025 and will operate concurrently with the GlueX experiment, whose primary objective is the search for gluonic excitations in the meson spectrum. I will give an overview of the JEF experiment, the GlueX detector, and the feasibility of further upgrades to support future ¿ physics studies. Special attention will be given to the newly constructed PbWO4 scintillating calorimeter and recent advancements in calorimeter instrumentation.

Somov, Alexander↗

DOE OSTI2025

Modal Analysis and Testing of a Cantilever Beam: Results and Guide

This report discusses modal analysis and testing of a cantilever beam including an introduction to modal testing, simulation, analysis, and a comparison of results. An accompanying presentation can be found from the LLNL CASIS website. Modal testing and analysis are essential for characterizing the response of a structure during vibration environments. Determining natural frequencies and mode shapes helps determine whether resonances will be reached during operations and if so, how the structure will respond and how the response can be tuned. The goal of this work is to convey the basics of modal testing and analysis through a simple project. This can be applied later to more complex, applicable structures. This includes a variety of work including data collection, finite element analysis and data processing. For this project a cantilever beam was chosen because it is a simple, well-characterized structure.

42 ENGINEERING↗

DOE OSTI2022

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R 2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m 3 /m 3 ). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Enabling Renewable Energy While Protecting Wildlife: An Ecological Risk-Based Approach to Wind Energy Development Using Ecosystem-Based Management Values

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.

17 WIND ENERGY↗

DOE OSTI2023

Data from: Arctic ice-ocean interactions in an 8-to-2 kilometer resolution global model

This data collection represents all UH8to2 model data used for the publication "Arctic ice-ocean interactions in an 8-to-2 kilometer resolution global model." This includes ocean and sea ice characteristics from the 2017-2020 UH8to2 model run. Further details about the model setup, forcing, and our interpretation of these data can be found in the publication.

58 GEOSCIENCES↗

NASA NTRS1972

Definition of multipath/RFI experiments for orbital testing with a small applications technology satellite

An investigation was made to define experiments for collection of RFI and multipath data for application to a synchronous relay satellite/low orbiting satellite configuration. A survey of analytical models of the multipath signal was conducted. Data has been gathered concerning the existing RFI and other noise sources in various bands at VHF and UHF. Additionally, designs are presented for equipment to combat the effects of RFI and multipath: an adaptive delta mod voice system, a forward error control coder/decoder, a PN transmission system, and a wideband FM system. The performance of these systems was then evaluated. Techniques are discussed for measuring multipath and RFI. Finally, recommended data collection experiments are presented. An extensive tabulation is included of theoretical predictions of the amount of signal reflected from a rough, spherical earth.

Birch, J. N.↗

NASA NTRS1977

ASDAR (aircraft to satellite data relay) flight test report

The aircraft to Satellite Data Relay (ASDAR), an airborne data collection system that gathers meteorological data from existing aircraft instrumentation and relays it to ground user via a geo-synchronous meteorological satellite, is described and the results of the first test flight on a commercial Boeing 747 aircraft are presented. The flight test was successful and verified system performance in the anticipated environment.

Domino, E. J.↗

NASA NTRS1981

Summary of measurement results of ozone, methane, and nonmethane hydrocarbons for C-54 aircraft. 1979 Southeastern Virginia Urban Plume Study

Methane, nonmethane hydrocarbon, and ozone data collected in a C-54 aircraft during the 1979 Southeastern Virginia Urban Plume Study are presented. Three major aircraft experiments were flown on five separate days in August collecting 20 hours of flight data. Direct correlation between ozone and hydrocarbon plumes was observed on several occasions.

Cofer, W. R., III↗

NASA NTRS1990

Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

Smith, Phillip N.↗

NASA NTRS1991

Effects of vegetation on soil moisture distribution and flux with implications for the global hydrologic cycle

Recent climate modeling experiments have identified the critical need for a better understanding of land surface - atmosphere interactions. An important issue in global climate modeling is to be able to relate land surface and atmospheric processes. In the past this link has been inadequately represented due to the lack of understanding of the interaction between the processes and also due to the large spatial variability of the hydrological and soil properties. A project was initiated at the Marshall Space Flight Center (MSFC) in FY-90 under the Center's Directorate Discretionary Fund (CDDF) to study small-scale effects of vegetation on the distribution and fluxes of soil moisture. Installation of a large array of instruments was accomplished during that first year (FY-90). During this second year of the project, the instrumentation and data collection systems were improved and data has begun to be taken. Preliminary analysis of the data show that the equipment has been functioning properly. Some of the preliminary results that have recently been analyzed are given.

Macari, Emir Jose↗

NASA NTRS1992

Experiment specific processing of residual acceleration data

To date, most Spacelab residual acceleration data collection projects have resulted in data bases that are overwhelming to the investigator of low-gravity experiments. This paper introduces a simple passive accelerometer system to measure low-frequency accelerations. Model responses for experiments using actual acceleration data are produced and correlations are made between experiment response and the accelerometer time history in order to test the idea that recorded acceleration data and experimental responses can be usefully correlated. Spacelab 3 accelerometer data are used as input to a variety of experiment models, and sensitivity limits are obtained for particular experiment classes. The modeling results are being used to create experiment-specific residual acceleration data processing schemes for interested investigators.

Rogers, Melissa J. B.↗

NASA NTRS1994

Application of materials database (MAT.DB.) to materials education

Finding the right material for the job is an important aspect of engineering. Sometimes the choice is as fundamental as selecting between steel and aluminum. Other times, the choice may be between different compositions in an alloy. Discovering and compiling materials data is a demanding task, but it leads to accurate models for analysis and successful materials application. Mat. DB. is a database management system designed for maintaining information on the properties and processing of engineered materials, including metals, plastics, composites, and ceramics. It was developed by the Center for Materials Data of American Society for Metals (ASM) International. The ASM Center for Materials Data collects and reviews material property data for publication in books, reports, and electronic database. Mat. DB was developed to aid the data management and material applications.

Liu, Ping↗

NASA NTRS2000

Development of a Vehicle Health Monitoring System for the Space Shuttle Solid Rocket Booster Program

During their brief flight, the space shuttle solid rocket boosters (SRBs) experience a severe environment. This environment in most cases is unknown. When the design engineers believe they understand the environments, something new occurs. For example, at water impact several SRBs have sustained noticeable structural damage. The severity of the damage is usually dependent upon the waves that the SRB encounter at splashdown. The space shuttle is presently scheduled to fly until 2030. To support the shuttle flight schedule, the avionics on the SRB's will need to be upgraded. The environments on the different sections of the SRB will need to be defined more completely to properly qualify the avionics for multiple flights. The combination of new avionics systems and unknown flight environments led Marshall Space Flight Center's (MSFC) SRB Project Office to request the Science and Engineering (S&E) Directorate to develop a stand-alone data acquisition system that could collect data from any area of the booster. The Enhanced Data Acquisition System (EDAS) was developed to meet this request. However, the EDAS has some technical drawbacks that needed resolved. To answer the EDAS problems, the SRB Project Office has funded MSFC's Avionics Department to begin investigating a new vehicle health monitoring (VHM) system. The major requirements are the system shall have 64 channels, have programmable sample rates up to 10,000 samples per second, have sufficient memory for a twenty minute flight and not interfere with existing operational flight avionics hardware. This paper will describe the effort to develop a VHM system that can meet the SRB requirements.

Crawford, Kevin↗