Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Resource 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Achieving Energy Savings in Small- and Medium-Sized Public Facilities: A Strategic Approach to Prioritizing and Financing

This resource is for state, local government, and K-12 school staff managing small- and medium-sized facilities. Readers will learn to address the unique challenges of smaller energy-saving projects and make informed decisions about financing. Section 1 provides tools for obtaining the information required to prioritize potential energy upgrades. Section 2 presents financing options for energy upgrades, as well as insights that will help decision makers select the right financing model for their project and jurisdiction. Section 3 summarizes key takeaways and highlights additional resources for small- and medium-sized public facilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Development and Application of a Risk Analysis Toolkit for Plant Resources Optimization

This report summarizes the R&D activities of the Risk Informed Asset Management (RIAM) project during fiscal year 2020 (FY20). This project focuses on the development of methods designed to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture) provided system/component health/cost data. This project development lives in cooperation with the Plant Health Management (PHM) project which focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate most relevant sources of risk. This year’s activities for the RIAM project focused on the continuation of schedule optimization algorithms developed in FY19. While in FY19 we focused on both deterministic and stochastic capital budgeting methods, in FY20 we moved forward by implementing two versions of schedule optimization methods. The first one reformulates the capital budgeting problem in a distributionally robust form which allows the user to rely on data directly rather than proposing a distribution from the data itself. The second version reformulates the capital budgeting explicitly using risk measures as variables to maximize/minimize. Lastly, we focused on the development of methods designed to identify the optimal maintenance posture based on the Pareto Frontier analysis. Rather than performing a tradeoff analysis (i.e., identify the absolute best posture), the Pareto Frontier analysis performs a trade space exploration approach (i.e., identify value and costs of several postures and have the analyst perform the task of imposing desired value and cost constraints). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California

Floating offshore wind is being considered in northern California as indicated by the Bureau of Ocean Energy Management’s issuance of a lease consideration in the Humboldt Call Area. Humboldt County offers access to this enormous resource, but local electric load and transmission are limited. The potential impacts of offshore wind generators at three different scales were studied using a regional grid model of Humboldt County. Offshore wind generation was calculated using modeled wind speed data and 12-MW turbine specifications and integrated with projected load and historical generation. Offshore wind farms deployed in the Humboldt Call Area achieve annual capacity factors between 45% and 54% after losses and maintenance. Power output is variable between and within seasons, with full power output 30% of the time and no output approximately 20% of the time. Electricity from a 48-MW wind farm provides 22% of regional load with limited exports. A 144-MW wind farm serves 38% of local load, exporting 40% of its electricity with the extant 70-MW transmission capacity. A full build-out of 1836 MW would result in 88% curtailment with existing transmission. Across scenarios, offshore wind variability necessitates reliance on existing power plants to meet local demand in periods of low wind.

17 WIND ENERGY↗
DOE OSTI2023

Subordinated Gaussian Processes for Solar Irradiance

Traditionally the power grid has been a one-way street with power flowing from large transmission-connected generators through the distribution network to consumers. This paradigm is changing with the introduction of distributed renewable energy resources (DERs), and with it, the way the grid is managed. There is currently a dearth of high fidelity solar irradiance datasets available to help grid researchers understand how expansion of DERs could affect future power system operations. Realistic simulations of by-the-second solar irradiances are needed to study how DER variability affects the grid. Irradiance data are highly non-stationary and non-Gaussian, and even modern time series models are challenged by their distributional properties. We develop a subordinated non-Gaussian stochastic model whose simulations realistically capture the distribution and dependence structure in measured irradiance. We illustrate our approach on a fine resolution dataset from Hawaii, where our approach outperforms standard nonlinear time series models.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2024

Performance Characterization and Provenance of Distributed Task-based Workflows on HPC Platforms

Understanding performance and provenance of task-based workflows poses significant challenges, particularly in distributed configurations where resources are shared by multiple applications. Task-based workflow management systems further complicate performance predictability because of their dynamicity that subtly alters task execution order from run to run. In this paper we propose a layered characterization framework for performance and task provenance for Dask.distributed workflows running on high-performance computing (HPC) platforms. It collects data from jobs, the workflow management system, and the operating system to aid in understanding the performance of these workflows. Our approach encompasses three main contributions: first, an extension of Dask.distributed to capture high-fidelity task provenance using Mochi data services; second, the adaptation of the established HPC I/O characterization tool Darshan to gather high-fidelity I/O data, thereby enhancing the granularity of our analysis; and third, a framework to combine and process the collected data and provide helpful insights into performance characterization and reproducibility, alongside our lessons learned.

Dask↗
DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

SolarSTARTS: Solar-Assisted State-Aware and ResilienT infrastructure System

This final technical report provides a description and results of the design, development, testing, and validation of the Automated Resilience Management System (ARMS) solution, which integrates different systems to collect, store and process relevant information from the power distribution system to automatically manage the operation of multiple energy assets to enhance the resilience of the power grid against high-impact physical incidents (e.g., hurricanes) and cyber threats. The developed solution comprises a suite of novel AI-based algorithms designed to first detect, locate, and classify anomalies by collecting and analyzing data from multiple monitoring and control devices

14 SOLAR ENERGY↗
DOE OSTI2024

Finding ways to reduce nuclear waste: searching for the unknown one step at a time

In my home country, Venezuela, research has been stagnant. Due to the political turmoil and the crisis, many educated people have left the country in search for a better life. This has caused a deficit in any technological and scientific advances, making Venezuela one of the first South American countries to have its rate of publications decline by 29% in 2013. Currently, Venezuela lacks the infrastructure and the means to keep up with the research progress as compared to other countries in South America, such as Brazil. Since coming to the United States (US), and currently working for a national laboratory, the active research environment endorses a wide range of careers and engineering programs that allow researchers to thrive at any given field. Researchers have access to funds and tools to succeed in developing materials for the future. There are 17 national laboratories in the US, and all of these have a different research focus/objective. As examples, Los Alamos National Laboratory and Sandia National Laboratory focus is on national homeland security, weapon science, radiation effects, among others. Argonne National Laboratory focuses on nuclear energy, energy storage, high performance computing, etc. At Idaho National Laboratory (INL) the research focuses on innovating nuclear energy and clean energy resources, critical infrastructure materials, along with fuel cycle solutions to manage, dispose and find ways to recycle current and future radiological waste. Compared to other national laboratories, INL focuses slightly more on applied processes and how nuclear energy can be innovated to next reactor design and technologies. The research being conducted at INL made me apply for a Seaborg distinguished postdoctoral position. For the position itself, the researcher must submit a proposal related to actinide chemistry on a research field area. In this position, 50% of my time will be focused on my own proposal. The proposal that I am working on is focused on the innovation of nuclear energy and fuel cycle recycling, which is why I was mainly interested on working at this national laboratory. To give a bit more context of what my proposal is about, a little bit of background is necessary: After the nuclear fuel (UO2) is used in a reactor, the fuel matrix is then characterized by various fission products (FP). Among these FP (including rare earth elements, alkali/alkaline earths, and actinides), many can potentially be recovered through nuclear reprocessing technologies. In pyroprocessing, the used nuclear fuel undergoes electrochemical dissolution into a molten chloride salt mixture in an electrorefiner. Initially, uranium is reduced onto an inert cathode by applied potentials. However, numerous remaining FPs accumulate in the melt and pose challenges for recovery by an inert electrode, particularly the rare earth elements (e.g., Nd, Gd, Pr, Sm) due to their multivalent oxidation states and tendencies toward side reactions, leading to their dissolution in the electrolyte. These recovery challenges result in inefficiencies and necessitate the continual discarding of the molten chloride salt, thereby generating additional waste. Furthermore, the presence of rare earth elements and other fission products in the molten salt electrolyte alters its physical and chemical properties, affecting both uranium recovery efficiency and the longevity of the molten chloride salt. To improve the recovery efficiency of the FP, specifically rare earth elements, I am investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form. The kinetic pathways and the chemical reactions of these elements will give insights on how the recovery efficiency can be improved. The interactions and speciation of these elements are being studied by spectro-electrochemistry at high temperature environments in quartz and other ceramic materials (e.g., alumina crucibles). Some of the challenges I am facing specifically relates the reactivity of some of these elements with different glass and crucible materials. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for an efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Regulations for Bat Protection in Mexico's Wind Farms

Wind energy development has expanded the fastest globally among all renewable sources during the last 20 years. However, wind farms have documented adverse impacts on bats, including mortality from collisions with turbine blades and disruptions to habitat and behavior. As the world's sixth most attractive economy for renewables, with 70 operating wind farms, Mexico and its bats now face escalating threats from the country's burgeoning wind industry. Despite this rapid growth, few studies have analyzed Mexico's regulatory framework to prevent, evaluate, and mitigate wind farm effects on bats. In this study, we reviewed Mexican laws and treaties that facilitate wind farm permitting, construction, operation, and decommissioning, and searched for guidelines that specifically address bat conservation. We found eight international pacts that promote wind power adoption along with three relevant articles in Mexico's Constitution. The General Law of Ecological Balance and Environmental Protection proved most pertinent for impact management. Supplementary guidelines from the Ministry of Environment and Natural Resources offer general strategies for evaluating wind farm impacts on bats, but adherence remains voluntary. Given expanding wind power investments across Mexico, we highlight the need for more stringent national standards that require preventative and corrective measures to protect bat populations. Tighter legislation and enforcement offer pathways toward environmentally sustainable wind energy development in Mexico.

17 WIND ENERGY↗
DOE OSTI2020

Achieving the End State for the Pahute Mesa Corrective Action Units at the Nevada National Security Site - 20355

Underground nuclear testing at the Nevada National Security Site (NNSS) ended in 1992. To address the impact of radionuclide contamination from underground nuclear testing on the groundwater resources of Nevada, the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program created the Underground Test Area (UGTA) activity to characterize the radionuclides in groundwater, understand the nature and extent of radionuclide migration, and forecast the distribution of radionuclides in groundwater for 1,000 years. The UGTA activity is regulated by the Federal Facility Agreement and Consent Order (FFACO), an agreement negotiated between the Nevada Division of Environmental Protection (NDEP), DOE, and the U.S. Department of Defense (DoD). DOE is close to achieving the end state (closure in place with monitoring and institutional control) for three of the five UGTA corrective action units (CAUs) on the NNSS. A number of challenges remain to achieve the end state of the other two CAUs, both located on Pahute Mesa. Pahute Mesa was the location of 82 underground nuclear tests, less than 10% of the total number of tests on the NNSS. Yet, Pahute Mesa contains slightly more than 60% of the total radionuclides (in curies). Based on groundwater sampling in monitoring wells, two radionuclide plumes have migrated several kilometers (km) in groundwater from selected test cavities and have crossed the boundary of the NNSS (yet remain within the boundaries of Federally controlled land). The path to achieve the end state continues to evolve as more data are collected and a better understanding of radionuclide migration in groundwater is developed. DOE has invested in drilling and sampling more than 50 characterization and monitoring groundwater wells over the past 25 years. The data indicate that the primary radionuclide of concern is tritium as it is about 89% of the total radionuclide inventory (in curies). As well, only tritium has been measured in groundwater outside of cavities at concentrations exceeding the Safe Drinking Water Act (SDWA) standard. For one of the tritium plumes that has migrated across the NNSS boundary, the average rate of migration has been measured as about 45 meters (m) per year with the rate of migration at the leading edge of the plume of about 85 meters per year. At that rate of migration, the tritium plume will decay to safe levels and not reach the publicly accessible environment at concentrations above the SDWA standard. Other radionuclides, at concentrations below the SDWA standards, will be monitored to ensure they remain at safe levels. Consequently, the end state path forward for Pahute Mesa has evolved to take full advantage of the data from the monitoring network to constrain uncertainty in model forecasts and to reduce reliance on probabilistic simulations. The focus of the end state approach relies on developing a monitoring well network that is protective of human health by increasing confidence that no radionuclide plume in the groundwater will migrate undetected to the accessible environment, located about 22 km from the nearest up-gradient underground nuclear test. Using the measured data to remove uncertainty, the evaluation of radionuclide migration from Pahute Mesa is directed toward meeting the goals of the end state. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Maximizing the Benefits of On-Site Renewable Energy Generation Using On-Site Energy Storage

The commercial and industrial building sectors have a major role to play in a U.S. low-carbon future. Building owners can make a difference by deploying on-site renewable generation and storage technologies, which facilitates future-proofing their buildings as well as more effectively meeting the service requirements of the building. This resource provides an overview of common generation, storage, and load management technologies in behind-the-meter systems, and serves as a primer to demonstrate the impact on net building loads required from the grid for different sizes of renewable generation along with on-site electrical and thermal storage. These discussions can help commercial building owners communicate the value of these systems to project teams and develop innovative behind-the-meter solutions to achieve their energy goals.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2022

Distributed Energy Resource Cybersecurity Framework and Cyber Range Integration

Distributed energy resource (DER) systems feature complex, data-driven communications networks that require careful system coordination and constant vigilance to ensure that grid assets are secure. Because DERs are an important component of the decarbonization strategy, agencies need to secure energy data that could implicate issues of national security if compromised. To help federal energy managers assess, monitor, and manage cybersecurity while achieving decarbonization, the National Renewable Energy Laboratory's (NREL's) Distributed Energy Resource Cybersecurity Framework (DER-CF) offers a comprehensive, web-based assessment tool focusing on cyber governance or policies, technical management, and physical security. The DER-CF currently presents users with a series of pertinent cybersecurity questions that are used to generate a site-specific report and recommendations. This paper outlines a plan to integrate the DER-CF with another key asset-NREL's cyber range-to visualize cybersecurity resilience and compliance and to enhance the usability and accessibility of the DER-CF for federal facility energy managers and planners. This integration will result in a visualization environment to interpret and interact with compliance data. Its development will include regular conversations with stakeholders to assess the effectiveness of these efforts, refine the visualization capability, and ensure its value to our partners.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Final Report for ARPA-E NODES "Real-Time Optimization and Control of Next-Generation Distribution Infrastructure" Project

The project examined next-generation power distribution systems with high levels of power- electronics-interfaced distributed energy resources (DERs) that include: renewable energy systems (RESs), energy-storage devices, electric vehicles, fuel cells, small-scale diesel generators, and controllable loads. The project developed a comprehensive distribution- network management framework that unifies real-time voltage and frequency control with network-wide energy management under an integrated framework. The aim of the project was to: i) systematically optimize network-wide operation and congruently regulate voltages and frequency in the face of high volatility induced by rapidly varying RES and uncontrolled loads; ii) facilitate high renewable integration beyond 50% on an energy basis; iii) meet power-quality requirements and operational constraints; and, iv) respect response, ramp- time, and hold-time requirements for synthetic frequency and regulating reserves via fast- and longer-term dynamic energy management.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

behind-the-meter↗
DOE OSTI2023

Beneficial Integration of Energy Storage and Load Management with Photovoltaic (PV)

In recent years, a number of industry activities have aimed at addressing the integration challenges posed by the variability and uncertainty of higher penetration of renewable generation sources, like solar photovoltaic (PV) – one of the key objectives of the Sustainable and Holistic Integration of Energy Storage and Solar PV (SHINES) program launched by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). This EPRI led Beneficial Integration of Energy Storge, and Load Management with PV project aimed to design, develop, and demonstrate end-to-end distributed energy resource (DER) integration solution to build on these activities. EPRI led project team designed and implemented a local controller that uses model predictive control (MPC) algorithm to optimally manage DERs on site by planning for a receding horizon while executing the control settings for the first step of its plan. The team has also developed a system controller to interface with the local controller to demonstrate the hierarchical control and how it can leverage DER capabilities to address challenges like over voltage and thermal limit violations which typically limits the DER hosting capacity of distribution feeders. Team has demonstrated how the local controller with optimization algorithm can effectively manage controllable loads like HVAC, water heater, and pool pumps to allow for greater integration of PV with relatively smaller energy storage system requirements. Optimal utilization of the load control can also reduce the depth of discharge of batteries to meet grid export/import limit from behind-the-meter (BTM) DERs. Proper utilization of DER capabilities via local control intelligence, like the one developed and demonstrated in this project can help the industry to address integration challenges of higher penetration of solar PV in economically efficient manner. This can help to accelerate deployment of clean renewable energy systems at lower societal cost.

14 SOLAR ENERGY↗
DOE OSTI2022

Orientation to NPHR: Scripts for Training

The IAEA is training staff to train member states to use the Nuclear Power Human Resources (NPHR) model, developed at LANL, to examine their human resource plans. Part of the NPHR training involves orienting users to the files used by NPHR, namely the data file and the model files. To assist the IAEA trainers, the scripts in this document were developed for conducting the orientation sections. The scripts are intended to be used as resources for the trainers to develop their ability to deliver the orientation and not as scripts to be read to a training workshop. The scripts are accompanied by video recordings to illustrate what the trainers will show participants during the orientation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗