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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Crucible Melter Simulation in Nek5000

Nuclear tank waste at the Hanford site is slated for vitrification in large scale refractory-lined melters to transform it into a stable borosilicate waste form suitable for long-term storage or disposal. Molten glass corrodes the refractory lining over time at a rate correlated to the velocity of molten glass against the refractory-lined wall. To properly design a melter and plan for maintenance, it is necessary to accurately model the glass flow and find the correlation between flow velocity and corrosion rate. This modeling was started in STAR-CCM+ CFD software and is being continued in Nek5000 for its fast-running and quick turnaround code. This poster explains the basic process of reconstructing the geometry, fluid properties, and heating of test melters in Nek5000. The geometry is imported from a mesh file and boundary conditions assigned based on surface IDs. The fluid properties are set in the .par and .usr case files. The heating of the actual crucibles in joule heating with electrodes but simulated in Nek5000 with a volumetric heat source term. This volumetric heat source is fit to the actual heating profile with piecewise polynomials and exponentials. Basic results and verification methods are explained in the poster, as well as further work that must be done to complete modeling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

High-heat transfer lithium-ion batteries: A new era in battery thermal management

Despite advances in lithium-ion battery technology, critical challenges remain that must be addressed to accelerate electric vehicle (EV) adoption and global energy transformation. Significantly improved battery thermal management (BTM) is key to overcoming these challenges. BTM approaches focus on increasing heat transfer coefficients via air, liquid, or refrigerant cooling, but less attention is given to reducing the battery's thermal resistance, a major bottleneck for heat transfer. This work introduces a novel approach to reduce battery thermal resistance by integrating in-plane heat transfer with optimized cell geometry, minimized thermal resistances, and reduced interfacial resistances, representing a departure from previous methods. The standard prismatic can cell incorporating this technology is referred to as the high heat transfer (HHT) battery. An equivalent resistance battery thermal model is developed for speed and accuracy, validated against experimental data in the literature, demonstrating strong correlation and ensuring reliable predictions for real-world performance. Thermal performance metrics of the conventional and HHT batteries are compared using a parametric study with air, liquid, and refrigerant boundary conditions across a range of aspect ratios. The HHT battery shows a heat removal rate up to 20 times higher than a conventional battery. These findings suggest that HHT technology could be transformative for EV battery performance, enabling fast charging, mitigating thermal runaway, extending battery life, reducing cold-weather power loss, increasing reliability, lowering costs, and enabling higher energy density, all critical for EV adoption and energy transformation. Future work will focus on prototyping and real-world testing to refine these findings for commercial-scale applications.

25 ENERGY STORAGE↗
DOE OSTI2020

Enterprise Credentialing Service Statement of Work (SOW)

The scope of this project includes providing professional services in support of the development and deployment of an Enterprise Credentialing Service for the Department of Energy (DOE) National Nuclear Security Administration (NNSA), which will be used for issuing and managing credentials used for authentication, digital signature, and encryption functions by users, applications, and devices in a closed computing environment. The Seller shall provide subject matter expertise for the design and deployment of the technologies and processes that comprise the Enterprise Credentialing Service, which will include a public key infrastructure (PKI) and a credential management system (CMS) that issues and manages PKI-based smartcard credentials. The Enterprise Credentialing Service will support approximately 17,000 users at 15 DOE NNSA sites and laboratories located across the continental United States.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Reliability metrics and their management implications for open pond algae cultivation

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-to-calculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.

09 BIOMASS FUELS↗
DOE OSTI2021

Nondestructive Assay Technical Infrastructure Program Mission and Vision

The Nondestructive Assay Program (NDAP) mission and vision is achieved by identifying and accomplishing a set of programmatic goals that correspond with eight broad technical program elements. The NDAP was created as a result of Defense Nuclear Facility Safety Board Recommendation 2007-1, entitled “Safety-Related In Situ Nondestructive Assay of Radioactive Materials,” which emphasized the need to improve in situ measurements of radioactive material at US Department of Energy (DOE) defense nuclear facilities. An NDAP five-year plan will define tasks to accomplish specific goals identified in the NDAP mission and vision. This mission and vision is applicable for eight technical program elements: Hardware/Software Development, Algorithm Development and Nuclear Data, Uncertainty Quantification, Nuclear Materials, Staffing, Personnel, And Training, Data Management, Requirement and Standards, and Information Preservation and Dissemination. An additional program element is technical support, which provides daily execution management support for the NDAP, site scope, and deliverable tracking via site task managers, along with technical advisement and support from the technical support group. The NDAP mission and vision provides attributes with specific goals for each program element, and some goals benefit multiple program elements. The goals and attributes defined herein are implemented via an NDAP five-year execution plan that defines site work scope, budget, and deliverables, all of which are updated annually. The NDAP is designed to benefit nondestructive assay (NDA) needs to support DOE nuclear criticality safety programs, ensuring that NDA technology is sufficiently capable of guaranteeing the safety of those who handle, store, process, or transport fissionable materials in the complex. Especially important for the NDAP is to maximize capabilities to identify, characterize, and manage in situ fissile material deposits in process equipment to ensure nuclear criticality safety at processing facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Environmental Chamber Testing and Headspace Evaluation of a Commercial-Off-The-Shelf Foam Fixative to Support Deactivation and Decommissioning Activities

The Department of Energy (DOE) Office of Environmental Management (EM) is tasked with identifying high priority technical needs and the Technology Development (TD) tasks required to meet those needs in support of ongoing deactivation and decommissioning (D&D) of Department of Energy infrastructure across the United States. This work consists of placing a radioactively contaminated facility in stable condition to minimize any risks that could affect workers, the public, and the environment. Successful deactivation and decommissioning will leave the buildings in an agreed upon end state to provide future protection against a wide range of hazards that include radiation, asbestos, polychlorinated biphenyls, and other environmental and public health risks.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Winners are not keepers: Characterizing household engagement, gains, and energy patterns in demand response using machine learning in the United States

Demand-response programs can help utilities manage rapidly evolving electric grids, but these programs are subject to the complexities of human behavior. This paper explores a novel method for uncovering heterogeneity in households. In this work, we use a machine-learning method known as a Conditional Inference Tree (c-tree) algorithm to categorize households based on their energy behavior characteristics collected via smart meters, and explore how this translates through into heterogeneity in their real-world response to a DR program. Using data from randomized controlled trial, we generate estimates of the changes in energy use caused by the program within each household group. Our results show that the c-tree approach differentiates households by their energy-use characteristics in a way that increases the spread in enrollment rates and critical peak reduction among household groups, compared with the spreads achieved via several conventional segmentation methods. Thus, the c-tree analysis enables the most tailored targeting of major potential energy savers and could provide the greatest increase in cost-effectiveness of household recruitment into DR programs. Our results also offer fresh insights into the relationships between household energy behavior characteristics – such as peak energy use and “structural winningness” (the ability to save money under a DR program without changing energy-use behaviors) – and household decisions about enrolling in DR programs and reducing energy use. Our research also demonstrates the potential of smart meter data, combined with machine learning and econometric methods, to provide significant value to utilities, program implementers, researchers, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Results from the last DD and DT JET campaigns in the framework of the EUROfusion Tokamak Exploitation Work Package activity

JET, the only tokamak capable of operating with deuterium–tritium (D–T) fuel (since TFTR was shutdown in 1999), has provided essential experimental data to support ITER and DEMO design and operation. Within the EUROfusion Tokamak Exploitation Work Package, JET completed its final campaigns (2022–2023), culminating in the third D–T campaign (DTE3). These experiments addressed key challenges in plasma scenarios, exhaust control, and tritium management under reactor-relevant conditions. Significant progress was achieved in demonstrating ITER-like integrated scenarios with impurity seeding, achieving partial divertor detachment and high confinement ($H_{98}(y,2)$ ≈ 0.85) at 3 MA in D–T plasmas. Advanced exhaust regimes such as quasi-continuous exhaust (QCE) and X-point radiator (XPR) were successfully achieved first in D–D and then extended to D–T operation, confirming their relevance for mixed isotope operation. Operational milestones included a new world record of 69 MJ fusion energy in tritium-rich hybrid plasmas and long-pulse H-mode operation up to 60 s, contributing with unique data to the CICLOP database. Physics studies focused on peeling-limited pedestals in support of ITER and improved understanding of edge stability and impurity screening in metallic environments. Extensive usage of the shattered pellet injector (SPI) on JET provided critical information for the design of the ITER disruption mitigation system (DMS). Real-time control systems for D/T ratio control and plasma exhaust were deployed and demonstrated in D–D and D–T, while energetic particle physics investigations unfolded the role of fast ions in turbulence suppression mechanisms. Comprehensive tritium retention studies using gas balance method, post-mortem analysis, and ITER-relevant laser induced desorption spectroscopy (LIDS) diagnostics provided essential input for tritium accountancy strategies. These results are validating the ITER operational concepts, inform DEMO design, and deliver critical experience in nuclear operation and scenario integration.

disruptions↗
DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

thermal-grid-jba v1.0.0

This is a software repository that contains models for a feasibility study of a thermal energy network for Joint Base Andrews. The work has been conducted under the ESTCP program in the project https://serdp-estcp.mil/projects/details/0694868a-3d58-4a14-a587-b8f638bfcd5c The repository contains models for energy system selection and for verification of design. The DoD management intends to give access to this code for future feasibility studies at Joint Base Andrews and possibly other bases.

Wetter, Michael [Lawrence Berkeley National Labora↗
DOE OSTI2021

Rapid simulations of hyperspectral near-field images of three-dimensional heterogeneous surfaces

The scattering-type scanning near-field optical microscope (s-SNOM) has emerged as a powerful tool for resolving nanoscale inhomogeneities in laterally heterogeneous samples. However, most analytical models used to predict the scattering near-field signals are assuming homogenous landscapes (bulk materials), resulting in inconsistencies when applied to samples with more complex configurations. In this work, we combine the point-dipole model (PDM) to the finite-element method (FEM) to account for the lateral and vertical heterogeneities while keeping the computation time manageable. Full images, spectra, or hyperspectral line profiles can be simulated by calculating the self-consistent dipole radiation demodulated at higher harmonics of the tip oscillation, mimicking real experimental procedures. Using this formalism, we clarify several important yet puzzling experimental observations in near-field images on samples with rich typography and complex material compositions, heterostructures of two-dimensional material flakes, and plasmonic antennas. The developed method serves as a basis for future investigations of nano-systems with nontrivial topography.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM). Final Report

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM) is a proposed system that will enable data from an infinite number of diverse sources to be organized and accessed from anywhere using any handheld or other computer device. The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data has the potential to generate an informational universe of unprecedented size that has never before been possible due to the prohibitive costs, managerial complexity, and technical barriers associated with ever-changing exponential-growth data flows. We envision that DREAM will accelerate discovery by enabling climate researchers, among other types of researchers, to manage, analyze, and visualize data from earth-scale measurements and simulations. DREAM’s success will be built on proven components that leverage existing services and resources. A key building block for DREAM will be the ESGF, chaired by Dean N. Williams. Expanding on the existing ESGF, the project will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. Much of the Office of Science data is currently generated by multiple stand-alone facilities. DREAM can collect data accumulated from these facilities and incorporate it into a fully integrated network accessible from anywhere in the world. The result is a completely new paradigm shift for data management, analysis, and visualization enabling researchers to: Manage their calculations, data, tools, and research results; Ensure that all data are sharable, reproducible and (re)usable—accompanied by appropriate metadata describing its provenance, syntax, and semantics at creation; Advance application performance by selectively adapting APIs and services in response to scientific requirements and architectural complexities; and Provide scalable interactive resource management—navigate data and metadata at multiple levels, provide architecture-aware data integration, analysis and visualization tools. We will engage closely with DOE, NASA, and NOAA science groups working at the leading edge of computing. These engagements—in domains such as biology, climate, and hydrology—will allow us to advance disciplinary science goals and inform our development of technologies that can accelerate discovery across DOE more broadly. We will advertise and promote our technologies via dedicated workshops, tutorials, and sessions at conferences, stand-alone events with broad inter-disciplinary invitation, and engagements with leadership facilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Guide for Joint Participation in a DOE Complex Wide SAVY-4000 Surveillance Program

This document describes LANL Storage Program best practices when working with other User Sites to implement DOE M441.1-1 Manual requirements through the use of the SAVY nuclear material packaging system. It is a Manual directive for Field Element Managers to review and approve the SAVY-4000 container series design (with supporting technical basis) as a packaging system for use at their respective sites. This review and approval incorporates an evaluation of the User Site methodology for SAVY surveillance and the process for documenting its nuclear materials storage program. This document aims to assist the Field Element Mangers and User Sites in the processes necessary to credit LANL SAVY surveillance for key elements of the User Site surveillance plan.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

PV Performance Modeling and Stakeholder Engagement (Q1 FY2021 Project Report))

The objectives of this project are as follows: 1) Reduce uncertainty in PV performance models by developing and validating new and improved models and submodes. 2) Create and manage an open source repository of modeling functions and data. 3) Build and grow the PV Performance Modeling Collaborative 4) Represent the US in the IEA PVPS Task 13 Working group.

14 SOLAR ENERGY↗
DOE OSTI2023

Best Practices in Electricity Load Modeling and Forecasting for Long-Term Power System Planning

This report highlights best practices for enhanced load modeling and forecasting for long-term power sector planning. The best practices touch on stakeholder engagement, data acquisition and management, modeling and validation, and scenario development. Case studies are provided to highlight crosscutting lessons that could inform enhanced load modeling and forecasting across different country settings. Though this work presents best practices resulting from support to the PDOE, the list is by no means exhaustive—nor is it meant to be prescriptive.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Privacy-Preserving Transactive Energy System

In this paper, the privacy issue of recently proposed transactive energy systems for electric power systems is studied for the first time. It is identified that the private information of individual market participants is subject to the risk of leakage during their market-based interaction. In order to protect their privacy, a homomorphic encryption-based approach is developed to achieve the privacy preservation with the Paillier encryption scheme. The proposed privacy-perserving design is then demonstrated on a transactive energy system that coordinates and controls residential air conditioners to manage the feeder congestion. The simulation results confirm the effectiveness of the proposed design in protecting the privacy of individual market participants without affecting the overall system performance. Future work on the proposed design is also suggested.

Lu, Yang↗
DOE OSTI2023

Advancing uncertainty characterization for understanding projected water scarcity in multi-sector, multi-actor river basins across scales.

Invited Talk at AGU Fall Meeting 2023 Modeling how human institutions and infrastructure interact with the water cycle is essential to better understand the vulnerability, and resilience of water resources systems from the local to the global scale. This is especially true when investigating multi-sector, multi-actor responses to the effects of long-term changes and short-term shocks. It is also well recognized that uncertainty present throughout the modeling cycle (e.g., in data, functional relations, and model coupling approaches) limits our ability to trace the interactive dynamics of human-water systems, as well as to quantify their implications for management and planning. Systems with large numbers of diverse stakeholders further compound this challenge, as uncertain drivers and complex dynamics might have very disparate effects on water users. The work presented is conducted through the Integrated Multisector Multiscale Modeling (IM3) Science Focus Area, which explores how human and natural systems co-evolve in response to change. Through this multi-year effort, we have developed exploratory modeling methods to better characterize how the uncertain human and natural drivers of water scarcity yield consequential vulnerabilities in institutionally complex, multi-sectoral systems. This talk will specifically present on a series of uncertainty characterization experiments performed in the Upper Colorado River Basin, a sub-basin of the Colorado with thousands of water users. These complementary and systematic experiments are aimed at understanding: How are various uncertain stressors (e.g., climate change, demand growth) affecting the diverse water users of this basin in terms of water shortage? What are the key drivers of this shortage for each user? Methods and results from this work are used to address additional questions on the ability of adaptation to modulate the effects of these uncertain drivers, and on their compounding effects across spatial scales and through sectoral interactions.

Hadjimichael, Antonia↗