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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TRUST Sensors in Environments: Thermocouples (SE-TC) Report Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗
DOE OSTI2020

Advances in GDSA Framework Development and Process Model Integration

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2020 advances of the Geologic Disposal Safety Assessment (GDSA) Framework and PFLOTRAN development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of disposal options and generic sites. The capability is a framework called GDSA Framework that employs high-performance computing (HPC) capable codes PFLOTRAN and Dakota.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Digital Image Correlation as an Experimental Modal Analysis Capability

Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD)

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Under the TRUST work package, engineers use and provide feedback on analysis tools and experimental results and create databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗
DOE OSTI2021

History Matching and Performance Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope (ANS) is ongoing. After more than 2.5 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is economically attractive.

Wang, Xindan↗
DOE OSTI2021

Bipolar Redox‐Active Molecules in Non‐Aqueous Organic Redox Flow Batteries: Status and Challenges

Abstract In this Review, recent advances in the development of organic bipolar redox‐active molecules (BRMs) for redox‐flow batteries (RFBs) are discussed, with special emphasis on their utilization in non‐aqueous systems. BRMs are single molecules that can be used as both anolyte and catholyte. Their unique redox chemistry enables identical components to be present in RFBs, which has distinct advantages in storage, mitigating crossover and compound degradation. Recent scientific innovations have uncovered three main strategies in preparing these bipolar species: developing stable radicals that are capable of both positive and negative redox reactions, covalently bridging electron donor‐acceptor motifs on one single molecule, and forming biredox eutectic mixtures through physically mixing active components. These approaches not only enabled symmetric flow battery design, but also resulted in electroactive materials with improved properties such as solubility, stability, and cell voltage. Nevertheless, much is still to be done. Importantly, developing BRMs that are competitive with vanadium RFBs in all performance indicators (e. g. solubility >1.0 M, voltage output >2.0 V, and cycling longevity >10 000 cycles) remains a challenge. Mechanistic studies including molecular dynamics, plausible degradation processes, and electrode/solution interface are necessary to peer into key parameters that dominate their battery performance. Accordingly, we review the current status and suggest future opportunities in these areas.

Li, Min↗
DOE OSTI2024

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗
DOE OSTI2022

IC Report for project “Developing nonlinear laser-plasma instability models for high-fidelity, multi-physics simulation capability for ICF/HED” [Slides]

We’ve achieved our technical goals: (1) Perform large-scale kinetic simulations of SRS and CBET a range of plasma and laser conditions; (2) Develop a new $\delta f$-Gaussian-mixture algorithm to represent non-Maxwellian distribution functions from particle trapping and time-dependent plasma response; (3) Develop physics-based preliminary nonlinear LPI models for coupling to LRT/ Mazinisin and AMP; and (4) Begin implementation of LPI sub-grid models into Mazinisin.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Zero Emission Drayage Trucks Demonstration (ZECT 1) (Final Report)

The objective of this project was to develop and demonstrate zero emission capable heavy-duty electric truck technologies in real world drayage operations and assess its technical feasibility to support demanding drayage duty cycles. Further objectives of the project included the promotion and acceleration of market adoption of electric truck technologies in cargo transport operations, by engaging trucking fleets and end users in demonstrating ad experiencing these technologies first-hand. The project realized the development and demonstration of two battery-electric and two battery-electric hybrid platforms that advanced the technologies and demonstrated proof of concept.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
DOE OSTI2021

Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine with Doubly-Fed Induction Generator

After several accidents occurred in wind farms in the United States and around the world, the subsynchronous oscillation (SSO) issues in grid-connected wind farms have gained serious attention. Particularly, these issues have caused significant challenges to wind turbines with a doubly fed induction generator (DFIG) because it is connected to the grid via both its stator and rotor paths. Traditionally, a P-Q capability chart is utilized to assure the safe operation boundary for a synchronous generator. But the energy conversion characteristics of a DFIG wind turbine are completely different. A critical factor to affect the reliable operation of a DFIG wind turbine is the rated current and pulse-width modulation (PWM) saturation constraints of its power converters. These constraint conditions can be affected by the wind turbine rotating speed and grid conditions. However, a detailed study of DFIG P-Q capability from these perspectives has not been conducted, which has hindered adequate understanding of many abnormal wind turbine operations reported in the literature and the development of advanced control technologies to overcome the challenges. The proposed study in this paper considers vector control implementation to DFIG power electronic converters in the dq reference frame, and the models and algorithms developed for the P-Q capability study have addressed specific DFIG power converter constraints that are different from those of a traditional synchronous generator. The paper especially focuses on exploring the dynamic natures of DFIG P-Q capability under uncertain and variable conditions to explore the root causes of many abnormal operations of DFIG wind turbines reported in the literature. The proposed study is validated through an electromagnetic transient simulation model of a grid-connected DFIG wind turbine. The proposed study has the potential to lead to the development of new DFIG control technologies that can help overcome the challenges for many abnormal operations of DFIG wind turbines.

17 WIND ENERGY↗
DOE OSTI2026

Data for "Metabolic Engineering Strategies to Produce Medium-Chain Oleochemicals via Acyl-ACP:CoA Transacylase Activity"

Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation – an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads, that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.

Bioproducts↗
DOE OSTI2022

Implementation and testing of the GPT sensitivities in TRIPOLI-4

Computing the sensitivity of given reactor parameters with respect to nuclear data is mandatory in key applications such as the assessment of reactor safety or core design. In recent years, the development of Monte Carlo methods capable of estimating sensitivity coefficients based on the Standard or Generalized Perturbation Theory (SPT and GPT, respectively) has attracted intensive research efforts, especially in view of having reference golden standard simulations to be compared to faster but approximate deterministic calculations. Following our previous implementation and validation of the SPT functionalities in the Monte Carlo TRIPOLI-4, devoted to the sensitivity of the k eigenvalue, in this work we detail the development of GPT methods for ratios of reaction rates, and validate them against a few relevant benchmark results. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Nanoscale Elemental Mapping of Intact Solid–Liquid Interfaces and Reactive Materials in Energy Devices Enabled by Cryo-FIB/SEM

Many modern energy devices rely on solid–liquid interfaces, highly reactive materials, or both, for their operation and performance. The difficulty of characterizing such materials means these devices often lack high-resolution characterization in an unaltered state. Here, we demonstrate how cryogenic sample preparation and transfer can extend the capabilities of FIB/SEM techniques to solid–liquid interfaces and reactive materials common to energy devices by preserving their integrity through all stages of preparation and characterization. We additionally show how cryo-FIB/SEM paired with energy dispersive X-ray spectroscopy enables nanoscale elemental mapping of cross-sections produced in these materials and discuss strategies to achieve optimal results. Finally, we consider current limitations of the technique and propose future developments that could enhance its capabilities. Our results illustrate that cryo-FIB/SEM will be a useful technique for fields where solid–liquid interfaces or reactive materials play an important role and could, thus far, not be characterized at high resolution.

25 ENERGY STORAGE↗
DOE OSTI2020

Unveiling contextual realities by microscopically entangling a neutron

The development of qualitatively new measurement capabilities is often a prerequisite for critical scientific and technological advances. Here we introduce an unconventional quantum probe, an entangled neutron beam, where individual neutrons can be entangled in spin, trajectory and energy. The spatial separation of trajectories from nanometers to microns and energy differences from peV to neV will enable investigations of microscopic magnetic correlations in systems with strongly entangled phases, such as those believed to emerge in unconventional superconductors. We develop an interferometer to prove entanglement of these distinguishable properties of the neutron beam by observing clear violations of both Clauser-Horne-Shimony-Holt and Mermin contextuality inequalities in the same experimental setup. Our work opens a pathway to a future of entangled neutron scattering in matter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

How Quantum Sensing Will Help Solve GPS Denial in Warfare

The U.S. military’s ability to posture, deter, and prevail in future conflicts may rest on the quantum sensing position, navigation, and timing (PNT) capabilities that are currently being developed. Heavy reliance on GPS signals for PNT has become a critical vulnerability for the U.S. military. Meanwhile, the conflict in Ukraine has demonstrated that GPS denial and electronic warfare (EW) is now a key component of modern combat and satellite-guided munitions are reportedly being rendered ineffective. The Department of Defense (DOD) is focusing on upgrading GPS to use stronger, military-specific signals, which will still be vulnerable to EW and anti-satellite capabilities. A more diverse and resilient alternate-PNT strategy is needed to ensure mission success.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Bioimaging Capabilities to Enable Mapping of the Neural Connections in a Complex Brain

DOE’s Office of Science (SC), through its BRAIN Initiative Working Group, convened a virtual roundtable on November 2-4, 2020, to develop a conceptual framework for the capabilities needed to enable an interdisciplinary community of researchers to fully map the neural connections initially in the brain of a mouse and ultimately in the brain of a human. Over 30 researchers and programmatic observers from diverse scientific backgrounds, including those working in both the basic and applied sciences, participated in the roundtable and conceptualized forward-leaning ideas. In developing the framework, participants were asked to address questions under the three themes: connectome requirements, bioimaging technology, and computing and data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Materials Development and Advanced Process Simulation for Additive Manufacturing with Fiber-Reinforced Thermoplastics (Final Technical Report)

DuPont, Local Motors, and the Composites Manufacturing and Simulation Center (CMSC) at Purdue worked together to advance process simulation capabilities for Additive Manufacturing (AM) and develop printable short fiber reinforced semi-crystalline engineering thermoplastics suitable for vehicle components. DuPont provided one candidate thermoplastic material, which was evaluated against the following three criteria: 1) Printability using extrusion additive manufacturing processes. 2) Suitability for vehicle applications based on mechanical coupon screening tests. 3) Predictive capability of process simulations. Indiana Manufacturing Institute provided modeling and simulation technology and access to Purdue’s lab scale AM printer. Local Motors provided mechanical property requirements and printed demonstration prototype components using their Thermwood Large Scale Additive Manufacturing (LSAM) printer. To meet the performance and cost requirements of the automotive industry, high fiber content semi-crystalline engineering materials are required. Printing experience and property data for a 50% by weight short glass fiber reinforced material were gathered. Further, material properties required for simulating the printing process with the glass-fiber reinforced material were characterized. Knowledge was acquired with regards to the processability and performance of this thermoplastic material. Predictions of part deformation and crystallinity level were verified against experimental observations. Any significant results other than verification of simulation, e.g., novel material identified here would be impactful.

36 MATERIALS SCIENCE↗