Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “resource potential”

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 OSTI2023

Avoiding symmetry roadblocks and minimizing the measurement overhead of adaptive variational quantum eigensolvers

Quantum simulation of strongly correlated systems is potentially the most feasible useful application of near-term quantum computers. Minimizing quantum computational resources is crucial to achieving this goal. A promising class of algorithms for this purpose consists of variational quantum eigensolvers (VQEs). Among these, problem-tailored versions such as ADAPT-VQE that build variational ansätze step by step from a predefined operator pool perform particularly well in terms of circuit depths and variational parameter counts. However, this improved performance comes at the expense of an additional measurement overhead compared to standard VQEs. Here, we show that this overhead can be reduced to an amount that grows only linearly with the number n of qubits, instead of quartically as in the original ADAPT-VQE. We do this by proving that operator pools of size 2 n − 2 can represent any state in Hilbert space if chosen appropriately. We prove that this is the minimal size of such "complete" pools, discuss their algebraic properties, and present necessary and sufficient conditions for their completeness that allow us to find such pools efficiently. We further show that, if the simulated problem possesses symmetries, then complete pools can fail to yield convergent results, unless the pool is chosen to obey certain symmetry rules. We demonstrate the performance of such symmetry-adapted complete pools by using them in classical simulations of ADAPT-VQE for several strongly correlated molecules. Our findings are relevant for any VQE that uses an ansatz based on Pauli strings.

Shkolnikov, V. O.↗
DOE OSTI2025

An Early Investigation of the HHL Quantum Linear Solver for Scientific Applications

In this paper, we explore using the Harrow–Hassidim–Lloyd (HHL) algorithm to address scientific and engineering problems through quantum computing, utilizing the NWQSim simulation package on a high-performance computing platform. Focusing on domains such as power-grid management and climate projection, we demonstrate the correlations of the accuracy of quantum phase estimation, along with various properties of coefficient matrices, on the final solution and quantum resource cost in iterative and non-iterative numerical methods such as the Newton–Raphson method and finite difference method, as well as their impacts on quantum error correction costs using the Microsoft Azure Quantum resource estimator. We summarize the exponential resource cost from quantum phase estimation before and after quantum error correction and illustrate a potential way to reduce the demands on physical qubits. This work lays down a preliminary step for future investigations, urging a closer examination of quantum algorithms’ scalability and efficiency in domain applications.

hybrid software for QC-HPC↗
DOE OSTI2023

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Grid Value Investigation of Medium-Voltage Back-to-Back Converters: Preprint

This paper presents the work which investigates the value that the medium voltage back to back (MVB2B) converter can bring to the grid, through two potential applications: voltage regulation powered by the reactive power adjustment function, and the distributed energy resource (DER) adoption enhancement powered by the quantitative power transfer function. Two groups of distribution systems have been prepared for the value investigation, including IEEE 123-bus system for voltage regulation study and two utility provided realistic distribution systems for DER adoption enhancement study. The analysis results have demonstrated that the MVB2B converter can bring significant value to the grid through the two aforementioned applications. Particularly, with MVB2B converter transferring power between two feeders, a substantial amount of backfeeding solar power can be avoided, and the size of the energy storage which is used to store the extra solar power can be significantly reduced.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2024

High-Level Assessment of Grid Infrastructure in Southeast Asia to Support Regional Interconnections

The purpose of this slide deck is to provide an overview of the benefits of interregional transmission and to assess the specific transmission landscape of Southeast Asia, with respect to potential interconnections between Singapore and neighboring countries. This analysis also explores the distribution of renewable resources and electricity demand in ASEAN (the Association of Southeast Asian Nations) as well as current and anticipated interregional transmission, in order to inform future interconnection plans.

ASEAN↗
DOE OSTI2024

Zero-Emission Vehicle Adoption Resource Guide for Government Fleets in Jackson County, Illinois

As part of Communities LEAP (Local Energy Action Program), the National Renewable Energy Laboratory (NREL) provided technical assistance to Jackson County, Illinois to help develop their clean energy transition roadmap. Fleet electrification was identified as a potential pathway that could address the environmental injustices, high energy burden, and local pollution experienced by this former coal community. NREL worked with Jackson County, Illinois to develop a resource guide that can assist fleet managers considering a transition to electric light-duty fleet vehicles. To further understand the unique challenges of fleet electrification in Jackson County, NREL met with three leaders within the county who either managed current fleets or were responsible for fleet purchases. This resource guide includes best practices and resources that address many of the frequently asked questions that arose during these discussions. Interested fleets can then use this resource guide to help identify the initial steps needed to plan for vehicle electrification. The resource guide summarizes the basics of electric vehicle (EV) adoption for fleets, funding and incentive pathways, total cost of ownership in comparison to conventional internal combustion engine (ICE) vehicles, charging infrastructure, and pilot programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

wa-hls4ml and lui-gnn: A benchmark and GNN-based surrogate model for hls4ml resource and latency estimation

As machine learning (ML) increasingly serves as a tool for addressing real-time challenges in scientific applications, the development of advanced tooling has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as model synthesis, are now becoming limiting factors in the rapid iteration of designs. To reduce these emerging constraints, multiple efforts are being launched toward designing an ML-based surrogate model that estimates resource usage of synthesized accelerator architectures. This model would reduce the design iteration time, especially when designing within a set of given hardware constraints. This approach shows considerable potential, but as it stands, the effort is early and would benefit from coordination and standardization to assist future work as it emerges. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of more than 100,000 fully connected neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. In addition to the resource utilization and latency data provided, the dataset includes generated artifacts and log files for many of the synthesized neural networks, in order to support future research in ML-based code generation. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, as well as the average performance across a subset of the dataset. We measure the performance of a given predictor model through multiple metrics, including $R^2$ score and SMAPE on regression tasks, as well as inference time to further characterize the estimator under test. Additionally, we introduce the latency/utilization inference graph neural network (lui-gnn), a surrogate model that uses a graph neural network to represent input architectures in the form of a directed graph. This graph representation allows for a diverse set of model architectures to all be effectively handled by a surrogate model. We present the architecture and performance of the model, as evaluated by the new proposed benchmark, including SMAPE, $R^2$ score, and inference times, and find that lui-gnn generally predicts latency and utilization for the 75\% quantile within several percent of the synthesized resources on the synthetic test dataset, indicating that this approach of estimating resource and latency via a surrogate models has promise and warrants further research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Dynamic Life Cycle Assessment for Evaluating the Global Warming Potential of Geothermal Energy Production Using Inactive Oil and Gas Wells for District Heating in Tuttle, Oklahoma

Repurposing abandoned oil and gas infrastructure for geothermal energy production has great potential to reduce greenhouse gas (GHG) emissions. This study quantified the life cycle global warming potential of geothermal energy production using four inactive oil and gas wells repurposed for district heating in Tuttle, Oklahoma. A cradle-to-grave prospective life cycle assessment was performed to compare GHG emissions between the geothermal district heating system and conventional natural gas-fired heating system from 2020 to 2050. For initial implementation of the geothermal system, we investigated two approaches: 1) repurposing abandoned infrastructure from a nearby oil and gas well site, and 2) production and injection well drillings including new construction of a central heat exchange station. Environmental impacts from the geothermal system were estimated for five scenarios where a natural gas peaking boiler is incorporated to supply peak heat demand. The prospective results indicated that cumulative reduction in GHG emissions from transitioning to the geothermal district heating system increase over time as a function of future renewable resource penetration and technological advancements within electricity, fuel, and steel production. Over 30 years, the global warming potential associated with the district heating demand will have been reduced by up to 24 % with the repurposed system. These results imply that repurposing existing oil and gas infrastructure for geothermal energy systems of district heating will bring future climate benefits.

abandoned oil and gas wells↗
DOE OSTI2026

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Network Analysis of Academic Medical Center Websites in the United States

Healthcare resources are published annually in repositories such as the AHA Annual Survey Database TM . However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimizing Energy Use in Pulp & Paper with DOE’s Energy Intensive Industries Resources

The U.S. pulp and paper industry is the third-largest energy consumer in manufacturing, accounting for roughly 10% of sector energy use. Improving energy efficiency reduces operating costs and strengthens competitiveness. To support this effort, the U.S. Department of Energy (DOE), through Oak Ridge National Laboratory (ORNL), launched the Energy Intensive Industries (EII) Initiative. A two-year pilot across 45 industrial sites identified more than 4 trillion Btu/year in potential energy savings. This presentation outlines plans for a follow-up technical assistance program tailored to pulp and paper mills. Available resources include a cost-savings scoping tool, implementation planning guidance, and technical support for applying advanced methods such as Pinch Analysis for integrated process-utilities optimization. The session introduces key Pinch Analysis principles and highlights case studies demonstrating measurable improvements. ORNL also seeks industry feedback on barriers to efficiency improvements, including technology gaps and resource needs. DOE’s broader objective is to accelerate productivity and economic competitiveness across U.S. energy-intensive industries.

Kamath, Dipti [ORNL] (ORCID:0000000278739994)↗
DOE OSTI2020

Environmental Concerns and Mitigation Associated with Geothermal Resource Confirmation Drilling Activities

In 2017-2018, the Bureau of Land Management's National Renewable Energy Coordination Office, through its Geothermal Program, funded the National Renewable Energy Laboratory (NREL) to analyze technical and environmental considerations related to geothermal resource confirmation drilling. NREL solicited input from a group of technical and environmental experts in the geothermal industry, along with analyzing National Environmental Policy Act of 1969 (NEPA) documentation for previously approved projects. The collected data and analysis will be used by the Bureau of Land Management to examine the possibility of developing a new classification of wells and/or expediting the NEPA compliance process, which could potentially reduce permitting and regulatory compliance timelines when compared to the current process for obtaining a geothermal drilling permit for resource confirmation drilling activities.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Recent Developments of Tin (II) Sulfide/Carbon Composites for Achieving High-Performance Lithium Ion Batteries: A Critical Review

The ever-increasing worldwide energy demand and the limited resources of fossil have forced the urgent adoption of renewable energy sources. Additionally, concerns over CO 2 emissions and potential increases in fuel prices have boosted technical efforts to make hybrid and electric vehicles more accessible to the public. Rechargeable batteries are undoubtedly a key player in this regard, especially lithium ion batteries (LIBs), which have high power capacity, a fast charge/discharge rate, and good cycle stability, while their further energy density improvement has been severely limited, because of the relatively low theoretical capacity of the graphite anode material which is mostly used. Among various high-capacity anode candidates, tin (II) sulfide (SnS 2 ) has been attracted remarkable attention for high-energy LIBs due to its enormous resource and simplicity of synthesis, in addition to its high theoretical capacity. However, SnS 2 has poor intrinsic conductivity, a big volume transition, and a low initial Coulombic efficiency, resulting in a short lifespan. SnS 2 /carbon composites have been considered to be a most promising approach to addressing the abovementioned issues. Therefore, this review summarizes the current progress in the synthesis of SnS 2 /carbon anode materials and their Li-ion storage properties, with special attention to the developments in Li-based technology, attributed to its immense current importance and promising prospects. Finally, the existing challenges within this field are presented, and potential opportunities are discussed.

25 ENERGY STORAGE↗
DOE OSTI2020

The Value of Increased HVDC Capacity Between Eastern and Western U.S. Grids: The Interconnections Seam Study

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.9, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions.

13 HYDRO ENERGY↗
DOE OSTI2020

Assessment of rainfall variability and future change in Brazil across multiple timescales

Abstract Rainfall variability change under global warming is a crucial issue that may have a substantial impact on society and the environment, as it can directly impact biodiversity, agriculture, and water resources. Observed precipitation trends and climate change projections over Brazil indicate that many sectors of society are potentially highly vulnerable to the impacts of climate change. The purpose of this study is to assess model projections of the change in rainfall variability at various temporal scales over sub‐regions of Brazil. For this, daily data from 30 CMIP5 models for historical (1900–2005) and future (2050–2100) experiments under a high‐emission scenario are used. We assess the change in precipitation variability, applying a band‐pass filter to isolate variability on daily, weekly, monthly, intra‐seasonal, and El Nino Southern Oscillation (ENSO) time scales. For historical climate, simulated precipitation is evaluated against observations to establish model reliability. The results show that models largely agree on increases in variability on all timescales in all sub‐regions, except on ENSO timescales where models do not agree on the sign of future change. Brazil will experience more rainfall variability in the future that is, drier or more frequent dry periods and wetter wet periods on daily, weekly, monthly, and intra‐seasonal timescales, even in sub‐regions where future changes in mean rainfall are currently uncertain. This may provide useful information for climate change adaptation across, for example, the agriculture and water resource sectors in Brazil.

Alves, Lincoln M.↗
DOE OSTI2022

Assessment of oil and gas fields in California as potential CO 2 storage sites

California's total annual greenhouse gas (GHG) emissions (425.3 MtCO 2 e) in 2018 were about 6.4% of the US total (6,677 MtCO 2 e) and around 1% of global emissions. About 39% of 2018 GHG emissions in California were from the industrial and electrical sectors. Many of these emissions were from large stationary point sources and were suitable for carbon capture retrofit with subsequent storage of the captured carbon dioxide (CO 2 ) in geological formations. Previous studies of California found suitable geology and CO 2 storage resource. This study refines and furthers prior work using a three-stage screening process of oil fields, gas fields, and underground natural gas storage (UGS) sites by combining criteria from previous studies while excluding sites that pose technical risk or are located in regions with surface restrictions including sensitive habitats and dense populations. In the first stage, 129 CO 2 storage sites in California were identified using qualification criteria based upon formation properties including geological conditions and pore pressure. The second stage identified sensitive sites by applying conservative screens including seismic activity, faulting, population density, restricted lands, and sensitive habitats. During the third stage, 61 CO 2 potential storage sites were identified by subtraction of stage 2 areas from stage 1. The potential storage volume in the third stage ranged from 1.0 to 2.0 GtCO 2 . Finally, we applied a scoring system with seven parameters to rank the 61 potential sites based on subsurface technical criteria. The scored sites are classified as high priority, medium priority, and sites for future study. Prospective CO 2 storage sites with high and moderate priority were selected and linked to CO 2 sources. There are 14 prospective sites (above 20 MtCO 2 storage resource per site) with a total storage resource of 1024 MtCO 2 distributed in Northern and Southern California. Of these sites, there are 9 potential CO 2 -EOR sites and 1 depleted oil field with a total estimated CO 2 storage volume of ~800 MtCO 2 in the Southern San Joaquin and Ventura Basin. These 10 prospective sites with a storage resource greater than 20 MtCO 2 could potentially deliver more than 20 years of storage with an average injection rate of 40 MtCO 2 /year. The remaining 4 highly prospective sites are in Northern California. Additionally, study results suggest that saline formations should be re-evaluated in concert with storage in oil, gas, and natural gas storage reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

Phylogeny, morphology, virulence, ecology, and host range of Ordospora pajunii (Ordosporidae), a microsporidian symbiont of Daphnia spp.

ABSTRACT The impacts of microsporidia on host individuals are frequently subtle and can be context dependent. A key example of the latter comes from a recently discovered microsporidian symbiont of Daphnia , the net impact of which was found to shift from negative to positive based on environmental context. Given this, we hypothesized low baseline virulence of the microsporidian; here, we investigated the impact of infection on hosts in controlled conditions and the absence of other stressors. We also investigated its phylogenetic position, ecology, and host range. The genetic data indicate that the symbiont is Ordospora pajunii , a newly described microsporidian parasite of Daphnia . We show that O. pajunii infection damages the gut, causing infected epithelial cells to lose microvilli and then rupture. The prevalence of this microsporidian could be high (up to 100% in the lab and 77% of adults in the field). Its overall virulence was low in most cases, but some genotypes suffered reduced survival and/or reproduction. Susceptibility and virulence were strongly host-genotype dependent. We found that North American O. pajunii were able to infect multiple Daphnia species, including the European species Daphnia longispina , as well as Ceriodaphnia spp. Given the low, often undetectable virulence of this microsporidian and potentially far-reaching consequences of infections for the host when interacting with other pathogens or food, this Daphnia–O. pajunii symbiosis emerges as a valuable system for studying the mechanisms of context-dependent shifts between mutualism and parasitism, as well as for understanding how symbionts might alter host interactions with resources. IMPORTANCE The net outcome of symbiosis depends on the costs and benefits to each partner. Those can be context dependent, driving the potential for an interaction to change between parasitism and mutualism. Understanding the baseline fitness impact in an interaction can help us understand those shifts; for an organism that is generally parasitic, it should be easier for it to become a mutualist if its baseline virulence is relatively low. Recently, a microsporidian was found to become beneficial to its Daphnia hosts in certain ecological contexts, but little was known about the symbiont (including its species identity). Here, we identify it as the microsporidium Ordospora pajunii . Despite the parasitic nature of microsporidia, we found O. pajunii to be, at most, mildly virulent; this helps explain why it can shift toward mutualism in certain ecological contexts and helps establish O. pajunii is a valuable model for investigating shifts along the mutualism-parasitism continuum.

59 BASIC BIOLOGICAL SCIENCES↗