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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.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Results from Accelerated Environmental Testing of Barcoded Identifiers for UF 6 Cylinders

This report provides the qualitative and quantitative results from the accelerated environmental testing campaign. A total of 444 samples were subjected to 10 tests that included UV, salt fog, temperature, blowing dust, high pressure and temperature water, and impact exposure. Each sample included a two-dimensional barcode and an alphanumeric string representing the cylinder identification number. When evaluating the results, primary attention was placed on the decodability of the barcodes using a barcode verifier device, since machine scanning a barcode offers the greatest efficiency and accuracy gains when reading cylinder identification numbers during safeguards activities. Contrast was considered the critical test parameter because maintaining contrast under a wide range of environmental conditions is of fundamental importance to decoding the identification number of the barcodes. Additionally, manual readability of the alphanumeric string was considered an important factor in determining whether an inspector or operator could still read the identification number of the cylinder if the barcode proved to be undecodable.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

NETL Well Integrity Workshop: Identifying Well Integrity Research Needs for Subsurface Energy Infrastructure

Wells are a critical component of subsurface energy infrastructure. Ensuring the integrity of wells as engineered pathways for the safe extraction, injection, and storage of fluids in the subsurface is key to maximizing the effectiveness and resilience of that infrastructure. Addressing well integrity issues in a technically robust manner that promotes environmental sustainability and social equity is also an important focus of the United States (U.S.) Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management. Industry best practices, regulatory standards, modern monitoring data acquisition and control systems, and decades of research and development have dramatically improved the performance and reliability of wells for hydrocarbon extraction and underground injection in the oil and gas industry. Yet, important innovation is required to improve and ensure well integrity performance in engineered geologic systems where operational environments (fluid composition, temperature, pressure, and/or stress conditions) and long functional life cycles of well systems present unique challenges. Additionally, work is needed to understand and manage the long-term integrity and risks associated with legacy wells—especially those located adjacent to and presenting hazards for new subsurface activity.

02 PETROLEUM↗
DOE OSTI2021

Structural Health Monitoring: Using an Autoencoder to Identify Damage in a Bolted Joint [Capstone Project]

Los Alamos National Laboratory (LANL) is an important fixture in the United States Department of Energy’s (DOE) National Nuclear Security Agency (NNSA) complex. LANL is one of the largest national laboratories in the country, and the laboratory’s primary mission is to support the nation’s nuclear stockpile. The lab functions as a design agencies for the NNSA and performs extensive testing on weapons as part of that mission. The shock and vibration test team at LANL utilizes electrodynamic shaker systems for important qualification testing in support of the laboratory’s mission. Modern engineering relies heavily on bolted joints to connect two objects. During these shaker tests, engineers depend on bolted joints to secure the test article to a fixture and the fixture to the table. The test article may be hazardous and contain high explosives which could create a safety issue if a bolted joint failed. A loss of preload in a bolt will affect the way energy is input to the system and may introduce nonlinearities as the joint opens and closes. The loss of preload can create challenges controlling the test and make acquired signals useless. Being able to monitor preload within bolted joints during testing can improve the quality of the data and keep workers safe.

42 ENGINEERING↗
DOE OSTI2022

Identifying Electric Vehicles to Best Serve University Fleet Needs and Support Sustainability Goals

University fleets represent an enticing opportunity to explore the near-term feasibility of achieving net-zero-carbon emissions in transportation. In many instances, universities operate much like a small, self-contained ecosystem with all the same transportation needs as a larger municipality, but with a smaller geographic footprint. Their fleets often include a wide variety of vehicle types serving the campus, including low-speed vehicles (e.g., golf carts), light-duty sedans, SUVs, and pickups, as well as medium-duty trucks and delivery vehicles. The mix of vehicle and operational needs combined with broader activities related to net-zero campuses makes universities and colleges unique microcosms to determine the feasibility of and path to achieving net-zero fleets. As the availability of electric drivetrains expands beyond light-duty sedans, fleets need to understand when it will be operationally and financially appropriate to start adding electric drivetrains to their fleets. To better understand these opportunities, NREL contracted Sawatch Labs to analyze the role electric vehicles (EVs) can have in helping universities meet net-zero emissions and fleet sustainability goals they have instituted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Techno-Economic Wind Blade Manufacturing Model to Identify Opportunities for Cost Improvements Phase II IACMI Project 4.6/4.8

In IACMI Project 4.6 and IACMI Project 4.8, an Excel-based Techno-Economic Model (TEM) of the manufacturing process for composite wind turbine blades and a DELMIA Factory Flow Simulation of a generic wind blade manufacturing facility was developed. Together, these two tools provide a combined economic modeling capability that accounts for the material, labor, overhead and full-lifecycle operating costs associated with wind blade manufacturing as well as the impact of process flow and factory layout on overall manufacturing efficiency. The tools provide a novel means of detailed comparative analysis of the economic feasibility of proposed technologies and process changes for blade manufacturing. The modeling tools were developed with close support from members of industry and visits to multiple blade manufacturing facilities. With industry oversight, a detailed generalized manufacturing process plan and facility layout were developed with manufacturing parameters, material costs and economic factors based on historical data. Dassault Systèmes and the University of Texas at Dallas (UTD) contributed to the development of the Techno-Economic Model by providing macros to enable the generation of Bill of Material (BOM) data from a 3D blade design in either CATIA or NuMAD format, respectively. The TEM was built with the capability to directly import a Bill of Materials for economic analysis, and with the addition of the macros provided by Dassault and UTD, the TEM can directly import blade designs from both CATIA and NuMAD file formats. The modeling tools developed in Project 4.6 were used to investigate four wind blade manufacturing concepts in detail and select one to explore with laboratory-scale experimentation in Project 4.8. The four manufacturing concepts that were investigated were down-selected by the full project team from a larger list of concepts. The selections were made based on a number of criteria ranking viability and level of interest for each concept. The ‘One-Step Close’ manufacturing concept was ultimately selected for investigation in Project 4.8 and the demonstration was performed at the NREL CoMET facility. The TPI advanced manufacturing facility in Warren, RI contributed the production of several prototype components, the designs for which were developed by Janicki Industries. The demonstration project provided clear indication of the viability of the One-Step Close manufacturing concept for blade manufacturing and good validation of the Techno-Economic Model’s prediction of its economic impact.

17 WIND ENERGY↗
DOE OSTI2022

Co-processing Part 3: LANL Studies Quicker Method to Identify Renewable Carbon Percentages in Fuel Blends [Success Story]

Upgrading bio-oils with petroleum feedstocks at existing refineries—known as “co-processing”—could offer a fast pathway for lowering the carbon footprint of today’s transportation fuels. With equipment and infrastructure already in place, more than 100 refineries across the country are equipped to integrate bio-oil into their processes. But just where might companies insert sustainable bio-oils into existing refinery systems like fluid catalytic crackers and hydrotreaters? If successful, just how much of that renewable or “green” carbon makes it into final fuel products? In this three-part blog series, the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), and Los Alamos National Laboratory (LANL) offer insights into these pressing coprocessing questions—and others—amid the push to dramatically expand the production of climate-friendly fuels. Read part 1 and part 2.

02 PETROLEUM↗
DOE OSTI2021

Electricity Market Dynamics as Smooth Games: Organizing Gradient-Based Learners and Identifying Instabilities

Wide-spread adoption of machine learning and distributed energy production has the potential to fundamentally change behaviours of energy markets. In practice, along with the benefits, previously unseen instabilities have begun emerging in markets currently embracing these technologies. In this report we study electricity markets as dynamical systems arising in smooth games, where energy consumers are modelled as gradient-based learners who interact on a graph through distributed energy producers. We give simple examples of how instabilities can arise even when the consumers’ local objectives seem reasonable and how these instabilities can be remedied. Drawing insights from these examples, we begin developing a general model of optimization-driven electricity market dynamics and give conditions for ensuring local Nash equilibria of the system are stable fixed points of the dynamics. Our results demonstrate how models of electricity market dynamics might be used for deriving formal guarantees in order to stabilize markets and enact regulatory policies in the face of market shocks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Identifying Controlling Variables Related to Mercury Vapor Concentrations in Legacy Facilities: SRNL Technology Development For D&D

A suite of sensor packages has been installed in the Alpha-4 facility at Y-12 and preliminary data analysis to isolate the controlling variables has been performed after two months of data collection. In line with the conceptual model presented in Section 2.0, the preliminary analysis has demonstrated that temperature, barometric pressure, and relative humidity are the key controlling variables for mercury vapor releases within the building. The data analysis will continue to explore these controlling variables across the next several months to capture a more complete picture of the annual change in meteorological conditions at Y-12.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Implementation of a feature selection algorithm in FARM to identify important state variables and time-invariant matrices

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM aids the HERON software module in the evaluation of the optimal dispatch for the different IES components. Set-point trajectories are required to meet limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To evaluate the feasibility of HERON generated set-points and to do so in an acceptable time, FARM employs reduced order models to represent the dynamic behavior of the systems to be dispatched. These surrogate models take the form of a linear dynamic system with sets of Linear Parameter Varying (LPV) matrices that are mapped to the system operating space. These matrices are derived from the trajectories of system state variables and system output variables during transients. The accuracy of LPV matrices depends on the selection of state variables. In previous reports, state variables were selected by adopting a complicated workflow requiring multiple software licenses and an advanced level of user expertise. In this report, a new workflow that automates the state variable selection process is presented. It significantly reduces the frequency of user interventions and does not require multiple software licenses. Each module in the new workflow is described in detail, and the input / output examples in each step of the workflow are provided. It was demonstrated that this workflow can greatly reduce the complexity of the state variable selection process, and that the updated FARM-Gamma and FARM-Delta validators can benefit from this workflow when solving the power dispatch problem of a representative IES test case. Finally, some code improvements that can further enhance the efficiency are suggested.

42 ENGINEERING↗
DOE OSTI2023

New signature method for identifying organic material in atmosphere and water samples

The levels of plastic contamination in the earth’s oceans have steadily increased over the past century, creating a threat to marine life and increasing climate change. Several methods have been developed over the past decade to try to determine the amount and accumulation rate of plastic impurities in the ecosystem. These methods have proven promising but suffer from long measurement times, bulky non-mobile systems, and sample degradation. We propose a smaller, faster system that employs an electron beam to examine seawater samples for polyethylene contamination levels. This process generates a full electron and photon energy spectrum analyses based on the subatomic particles generated from electron interactions. Our simulations have already been developed based on the known molecular composition of seawater and polyethylene, showing the possibility of discerning molecular plastics from microorganisms. With a system the size of a suitcase, this system would be easily deployable to remote locations around the world or installed as a monitoring system for manufacturing facilities. This concept could lead to a new methodology for the science of signatures and be applied to other biological hazard investigations, such as general virus detection.

43 PARTICLE ACCELERATORS↗