SEARCH · Engineering Papers

Results for “key management”

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 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Advance Distribution Management System (ADMS)

This presentation explores the transition from traditional distribution management systems to Advanced Distribution Management Systems (ADMS) as a foundation for smart grid development. It highlights the key benefits of ADMS, including enhanced reliability, improved operational efficiency, and increased situational awareness. The presentation also addresses common implementation challenges such as system integration, data management, and organizational readiness. It concludes with a forward-looking perspective on the evolving role of ADMS and essential takeaways for utilities and stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗

DOE OSTI2022

Climate-aware decision-making: lessons for electric grid infrastructure planning and operations

Abstract Climate change poses significant risks to large-scale infrastructure systems and brings considerable uncertainties that challenge historical planning approaches. Here we focus on how climate awareness might be better incorporated into planning and decision-making in the electric power sector. To do so, we consider lessons from decision science literature where researchers have specifically focused on how to make better decisions under uncertainty. We perform a three-part review: of decision science literature on best practices for decision-making under uncertainty, of industry practice documents to understand how new uncertainties may affect the types of decisions electric utilities are making today, and of literature on electricity sector planning under climate change to assess how lessons from decision science might fit into sector-specific analyses. We discuss how characterizations of uncertainty from the decision science literature might guide approaches in the electricity sector to appropriately capture climate-related uncertainties. We also distill three key ideas from the decision science literature that can be incorporated into electricity sector planning to manage these new uncertainties: robustness, adaptive planning, and multi-stakeholder engagement. We offer example recommendations for how these key ideas might be incorporated into one essential type of planning activity, capacity expansion.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Waste-to-Energy Technical Assistance for Local Governments

The goal of this project is to mobilize data, information, and knowledge generated about organic waste streams to local governments and support their decision-making. It builds on previous work related to wet organic waste resources (food waste, sludge, manure, waste fats and oils). The project provides an improved understanding of local waste challenges and priorities to inform BETO's R&D strategies and decision-making. It also supports local governments' goals and plans related to sustainable waste management, enables energy and/or resource recovery projects development at municipal level, and facilitates public-private partnerships. A key challenge is associated with more activities requested by entities than program allows which is mitigated by prioritization by requesting agency. All FY21 and FY22 TA requests have been completed. Major accomplishments include: 1). 34 requests managed in the past two years, 2) Distilled key challenges faced by communities. Key outcomes include strong community participation since inception of the program, dedicated program web site, deliverables tailored to communities' needs, and distribution materials (e.g., fact sheets, brochures) for a broader audience.

BIOMASS FUELS↗

DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2022

Adaptive management of large-scale ecosystem restoration: increasing certainty of habitat outcomes in the Columbia River Estuary, U.S.A.

Ecological restoration programs in dynamic coastal environments can benefit from adaptive management, including an iterative process for identifying and addressing critical uncertainties. We highlight key developments under the three pillars that have increased the rate of restoration by the Columbia Estuary Ecosystem Restoration Program (CEERP) over 20 years: science, coordination, and management. We show how such programs can be institutionalized to ensure that estuary ecosystems are better understood, conserved, and restored. The principal conservation effort under CEERP is to reconnect historical floodplain wetlands to the mainstem. The program also supports other restoration actions that demonstrate a high potential to benefit ecosystem function and endangered salmon populations, however, there is greater uncertainty regarding these less-utilized techniques. Through adaptive management, we address both technical uncertainty regarding benefits to the environmental resource and programmatic uncertainty pertaining to decision-making. Here, we examine three periods of CEERP growth to establish how complementary research and restoration actions have improved program outcomes over time. We highlight the tools and processes that were developed and integrated into the program to refine program strategy, improve project design, and maximize ecological benefits. CEERP supported 77 restoration projects and reconnected over 7,000 acres of floodplain habitat to the lower Columbia River between 2004 and 2021. Building on these successes, we outline current plans to better engage landowners and local communities, solicit new project types, and maintain enough flexibility within the program to adapt to new priorities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Smart Planning Support for Nuclear Power Plant Work Planners

Operation and Maintenance costs of a nuclear power plant account for 60% of overall plant costs due to the nuclear industry?s risk-adverse culture (World Nuclear Association, 2020). The industry relies on highly conservative estimates to avoid risk and brute force reactions to manage the unexpected and keep a plant running safely. This approach has kept plants operating safer than any other power source available over the last six decades (Ritchie, 2020). However, these conservative methods have cost the nuclear industry in market competitiveness. The solution? Transform the conservative approaches to accurate, efficient, and still safe data-driven approaches that leverage advanced technologies available in the digital age of operation. This project endeavored to identify two key aspects to successfully incorporate historical work execution data. First, where in the work management process is that information most pertinent? Next, what variables are key to informing the best strategy for organizing the upcoming work? The Smart Planner uses data collected by dynamic work instructions to provide a basis for suggesting requirements of similar, upcoming work packages. Further, it curbs inefficiencies of the work management process by analyzing the likelihood of discovery work, offering suggestions to build a contingency package. All this taking place as the work planner builds work packages that meet the predetermined scope of work to be performed.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Chemist: A Domain-Specific Language by Chemists for Chemists

Managing the complexity of quantum chemistry (QC) software is key to ensuring it remains accessible, maintainable, and reusable. Noticeably missing from the QC ecosystem are modules targeting bottleneck routines. Here we argue that this is likely due to the difficulty in defining interfaces for such modules. To that end, we introduce the open-source, publicly available Chemist library https://github.com/NWChemEx/Chemist. Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks. The usefulness of Chemist is demonstrated by discussing the interface of NWChemEx’s Fock build module and by showcasing a proof-of-concept self-consistent field algorithm containing uncertainty propagation.

Algorithms↗

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 OSTI2022

Wildfire Mitigation Plans in Power Systems: A Literature Review

Some of the deadliest wildfires in the U.S., such as California’s 2018 wildfires, have been ignited by power systems. In an effort to prevent and minimize the ignition of wildfires, or control them if ignited, energy companies have developed wildfire mitigation plans. This paper provides energy companies and power system operators, engineers, researchers, and suppliers an overview of the state-of-the-art studies that address key topics in these wildfire mitigation plans and compares the wildfire mitigation plans of several energy companies. The key topics include grid design and system hardening, asset management and inspection, situational awareness and forecasting, operational response, vegetation management, public safety power shutoff, and risk-spend efficiency. Here this paper also presents a comparison of several energy companies’ decision-making criteria for initiating a public safety power shutoff. Finally, we discuss opportunities for future research studies that could help energy companies prevent wildfire ignitions.

42 ENGINEERING↗

DOE OSTI2022

HI-STORM Overpack and MPC-32 Thermal-Hydraulic Model with MOOSE Framework

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. The safe management of the spent nuclear fuel (SNF) is a key aspect of the back-end of the nuclear fuel cycle. Spent fuel dry storage systems are becoming a popular and effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution to maintain spent fuel for 60 years before final disposal. Dry cask storage has many characteristics that make it attractive. It fulfills the safety requirements of the Nuclear Regulatory Commission (NRC) while providing modularity and flexibility to contractors. The HI-STORM overpack and MPC-32 canister are the main parts of the HI-STORM 100 dry cask storage system. These components remove heat from the system using natural circulation, requiring no human intervention. This is the characteristic that provides passive heat removal and low maintenance features in dry cask storage systems. To develop a thermal model for a dry cask storage system, the physics behind the system should be defined clearly. There are two natural circulation loops in the system; circulation of helium cools down the nuclear assemblies in the MPC, while circulation of air cools down the walls of the MPC. This work aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. In this study, we will investigate and demonstrate the thermal-hydraulics modeling capabilities of the MOOSE framework, including natural circulation, heat transfer, and porous flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Pumped Storage Hydropower Augmented with Pressurized Air: The Ground-Level Integrated Diverse Energy Storage (GLIDES) System — GLIDES System Configurations and Use Cases

Energy storage is essential for cost-effective integration of variable renewable energy sources to support a low-carbon grid. It is also a key enabler of a modern grid infrastructure for demand management. However, several main challenges remain for different kind of energy storage technologies in grid scale deployment. Currently, the largest source of utility-scale storage and long-duration storage in the US is pumped storage hydropower (PSH). Prospect of growth in conventional PSH faces challenges that have limited its deployment over the last three decades, including high capital costs and long deployment timelines. Batteries have high energy densities and are the primary technology of choice for small-scale energy storage. Compressed air energy storage (CAES) is another large-scale energy storage technology, but there are few plants deployed worldwide. They suffer from their low round trip efficiency (RTE) due to the use of high-pressure air compressors. To address some of the challenges associated with these various storage technologies, the Ground-Level Integrated Diverse Energy Storage (GLIDES) is a modular PSH technology that was invented in 2015 at Oak Ridge National Laboratory. It utilizes gas compression to store electric energy. GLIDES stores energy by compressing gas using a liquid piston in high-pressure vessels. In doing so the vessels act as the upper reservoir in conventional PSH. Initially, the vessels are filled with gas to a prescribed pressure. To store energy, GLIDES uses a hydraulic piston pump to pump water into the pressurized vessels. As the water volume increases inside the vessels, water acts as a hydraulic piston compressing the gas on top of it. This process can be thought of as pumping water from the lower reservoir to the higher reservoir in PSH, increasing the water head. To dispatch the stored energy, the high-head water in the vessel is discharge through a high head Pelton hydraulic turbine that is connected to an electric generator. Employing high-pressure vessels enables GLIDES to reach water heads ~10-80 times higher than conventional PSH, achieving ~40 times higher energy densities, and overcomes the geographic limitation of conventional PSH. Although its energy density is much lower than that of batteries, GLIDES holds the potential advantages of having long service life, ease of system integration and being less hazardous over batteries. GLIDES prospective scalability could make it suitable for wide range of applications from behind the meter storage in buildings to grid-scale storage. It also makes it suitable for installations in densely populated urban areas where energy storage is most needed and real estate is limited. Over the last 5 years, work has focused on increasing GLIDES’ energy density, decreasing its initial capital cost of the system, and increasing its revenue potential. Several designs were developed and prototyped to verify and demonstrate the improvement in energy density. The latest prototype achieved energy density of 1.21 kWh/m 3 . Our analysis showed that it could achieve up to 1.7 kWh/m 3 with a mixture of air and carbon dioxide as the gas being compressed.

13 HYDRO ENERGY↗

DOE OSTI2022

Insert Modeling in UNF ST&DARDS

The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is a software tool that integrates a used nuclear fuel (UNF) or spent nuclear fuel (SNF) relational database and key analysis capabilities to simplify and automate numerous UNF management and fuel cycle–related activities. UNF-ST&DARDS is being developed for the US Department of Energy’s Office of Nuclear Energy Spent Fuel and Waste Disposition program. UNF-ST&DARDS provides an integrated framework that uses advanced modeling and simulation to predict the behavior of SNF over the timescales associated with permanent disposal in a geologic repository. After leaving the spent fuel pool, SNF is transferred to dry storage in a dual-purpose canister (DPC). DPCs are considered “dual purpose” because they are designed for both storage and transportation, removing the need to transfer the fuel to a separate transportation cask. However, much research has been conducted investigating the feasibility of directly disposing of DPCs in geologic repositories. Direct disposal of DPCs could reduce worker exposure during repackaging, reducing the amount of low-level waste from the discarded DPCs and potentially saving billions of dollars. Therefore, direct disposal of as-loaded DPCs is desirable if it can be done safely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Analytics Supporting Stockpile and Enterprise Planning [Slides]

A robust and growing modeling effort supports Los Alamos weapons leadership as well as NNSA (NA18, NA12, NA19) and DoD (DASD-NM, USSTRATCOM). Current work are valuable to several key NNSA working groups supporting strategic planning: Stockpile Stewardship Management Plan (SSMP); Requirements & Planning Document (RPD) analysis; Requirements and Capacity Working Group (RCWG); Production Integration Collaboration Working Group (PICWG); Enterprise Modeling and Analysis Consortium (EMAC); Cost Estimating Analysis Group (CEAG).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

Assessment of Water Management and Costs on CO 2 Geologic Storage Operations in Saline-Bearing Formations

Management of reservoir pressure is expected to be a key issue in the implementation of carbon capture and storage (CCS) projects, as it may be necessary to produce brine from an aquifer to offset the increase in subsurface pressure.

58 GEOSCIENCES↗

DOE OSTI2022

Development of a MOOSE thermal model of the MPC-32 canister and HI-STORM overpack

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Data Centers in Higher Education

This fact sheet summarizes some of the key needs, barriers, and opportunities related to data center management and operations in the Higher Education Sector.

data center, data center management, higher educat↗