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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantified Fast Frequency Response of Inverter-Based Resources for Bulk-Power System Study

Quantifying fast frequency response (FFR) of inverter-based resources (IBRs) is crucial for robust frequency regulation, managing resources, and improving system reliability in the power grids with high penetration levels of IBRs. This paper proposes a concept of frequency response scheme that its response is quantifiable and applicable to the generic IBR models. To achieve this, a stepwise-energy function is derived as a control module by considering operational constraints of IBRs. Then the module is implemented along with generic IBR models in electromagnetic transient (EMT) and electromechanical-based software. To quantify the FFR, the implemented module calculates available incremental active power for a specific time duration. This energy profile is being updated depending on IBR’s operating conditions and is provided into a power grid upon detecting a frequency event. Thus, due to this characteristic, this scheme can quantify the FFR and enable applicable IBRs to provide their available headroom within frequency arrest period. Thereby, this scheme can help estimate IBRs’ frequency response and is more effective in improving the initial frequency response than frequency-dependent control schemes: rate-of-change-of-frequency based and droop-based control schemes. The performance of the proposed scheme was tested under different IBR penetration levels using PSLF and PSCAD simulators.

Kim, Jinho↗
DOE OSTI2023

Livermore Computing User and System Scripts

LCUSS is a collection of scripts used to improve productivity on HPC systems for both administrators and general users. It will include general scripts for user management, scripts for helping users interact with LC resource management software (e.g. SLURM and Flux), and scripts to automate common user command-line tasks on LC and other HPC machines. These scripts are intended to be made available to all LC users. Hosting them on GitHub will allow LC staff, users, and collaborators to work on them together.

Long, Jeffery↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

How fast can one resize a distributed file system?

Efficient resource utilization becomes a major concern as large-scale distributed computing infrastructures keep growing in size. Malleability, the possibility for resource managers to dynamically increase or decrease the amount of resources allocated to a job, is a promising way to save energy and costs. However, state-of-the-art parallel and distributed storage systems have not been designed with malleability in mind. The reason is mainly the supposedly high cost of data transfers required by resizing operations. Nevertheless, as network and storage technologies evolve, old assumptions about potential bottlenecks can be revisited. In this study, we evaluate the viability of malleability as a design principle for a distributed storage system. We specifically model the minimal duration of the commission and decommission operations. To show how our models can be used in practice, we evaluate the performance of these operations in HDFS, a relevant state-of-the-art distributed file system. We show that the existing decommission mechanism of HDFS is good when the network is the bottleneck, but can be accelerated by up to a factor 3 when storage is the limiting factor. We also show that the commission in HDFS can be substantially accelerated. With the highlights provided by our model, we suggest improvements to speed both operations in HDFS. We discuss how the proposed models can be generalized for distributed file systems with different assumptions and what perspectives are open for the design of efficient malleable distributed file systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Framework for Integrating Quantum Simulation and High Performance Computing

Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM & NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.

Shehata, Amir [ORNL] (ORCID:0000000224531426)↗
DOE OSTI2026

Bat Acoustic Survey Data Collected June 2024 in and near Self Sufficiency Parcel-2 (SSP2) on the Oak Ridge Reservation (ORR)

The US Department of Energy (DOE) Oak Ridge Reservation (ORR) is located in Anderson and Roane Counties, Tennessee. A portion of the ORR, known as Self-Sufficiency Parcel 2 (SSP2) is planned for transfer for private use. The SSP2 Site is approximately 670 acres (Figure 1-1), although the current plan is to only clear and develop a portion of this acreage. Any inquiries about the land transfer and future development should be directed to DOE Oak Ridge Environmental Management, as this is beyond the scope of the Natural Resources Management Team (NRMT). NRMT records bat data for the entire ORR, including acoustic monitoring, mist netting and cave surveys. A few surveys have previously been conducted for small land transfers adjacent to SSP2 (See Appendix A), but not for the entire SSP2 area. Since bats have a large range, it was decided that collecting data while SSP2 was still accessible would be beneficial for the NRMT dataset. Acoustic data was therefore collected within and near SSP2 during the summer of 2024. This write-up is not a Biological Assessment (BA). However, the data and information provided can be used during the creation of a BA and consultations with US Fish and Wildlife Service (USFWS) in order to comply with federal directives of the Endangered Species Act of 1973 (16 U. S. C. 153 et seq.). The SSP2 site was surveyed during summer roosting/maternity season of 2024 using ultrasonic acoustic monitors to record calls from all bat species whose home ranges include the ORR. Special note was taken for presence of Federally listed Endangered and Threatened (T&E) bat species, as well as bat species which are Proposed for Federal listing, Candidate for federal listing, and state listed. Summer roosting season, from May 15 to August 15, is crucial to forest-dwelling T&E bat species for rearing young and foraging. Results of these surveys indicate the presence of three Federally listed bat species: Gray bat (Myotis grisescens--Endangered), Indiana bat (Myotis sodalis--Endangered), and Northern long-eared bat (Myotis septentrionalis--Endangered). Two additional bat species were present on the SSP2 Site: Tricolored bat (Perimyotis subflavus--Proposed for Federal listing) and Little brown bat (Myotis lucifugus—Candidate for Federal listing).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Utility Managed Distributed Energy Resources Intelligent Community - UDERMS iCommunity (Final Technical Report)

The Utility Managed Distributed Energy Resources Intelligent Community (UDERMS iCommunity) project, led by PacifiCorp and supported by the U.S. Department of Energy’s Building Technologies Office (Award No. DEEE0009782), aimed to demonstrate an integrated, utility-managed “behind-the-meter” distributed energy resource (DER) program connecting multifamily, commercial, institutional, and industrial buildings to deliver grid services and improve energy efficiency.

14 SOLAR ENERGY↗
DOE OSTI2021

Grid Architecture Guidance Specification for FAST-DERMS (V.1.0)

This document provides grid architecture guidance to support the Grid Modernization Laboratory Consortium (GMLC) Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solution (FAST-DERMS) project. The FAST-DERMS project seeks to develop an architecture and reference implementation solution that enables the provision of reliable, resilient, and secure transmission and distribution (T&D) grid services through the scalable aggregation and near-real-time management of utility-scale and small-scale distributed energy resources (DERs).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Assessing the Potential Impact of River Chemistry on Arctic Coastal Production

The Arctic coastal margin receives a disproportionately large fraction of the global river discharge. The bio-geochemistry of the river water as it empties into the marine environment reflects inputs and processes that occur as the water travels from its headwaters. Climate-induced changes to Arctic vegetation and permafrost melt may impact river chemistry. Understanding the impact of river nutrients on coastal marine production, and how this may change in the future, are important for resource managers and community members who monitor and rely on coastal food resources. Using the Energy Exascale Earth System Model we explore the impact of timing and river nutrient concentrations on primary production in each coastal Arctic region and then assess how this influences secondary production and particle fluxes supporting the benthic food web. Our results indicate that while the concentration of Arctic river nitrogen can have a significant impact on annual average nitrogen and primary production in the coastal Arctic, with production increases of up to 20% in the river influenced interior Seas, the timing of the river nutrient inputs into the marine environment appears less important. Bloom timing and partitioning between small and large phytoplankton were minimally impacted by both river nutrient concentration and timing, suggesting that in general, coastal Arctic ecosystem dynamics will continue to be primarily driven by light availability, rather than nutrients. Under a doubling river nutrient scenario, the percentage increase in the POC flux to the benthos on river influenced Arctic coastal shelves was 2-4 times the percentage increase in primary production, suggesting changes to the river nutrient concentration has the potential to modify the Arctic food web structure and dynamics. Generally, the nutrient-induced changes to primary production were smaller than changes previously simulated in response to ice reduction and temperature increase. However, in the Laptev Sea, the production increase resulting from a doubling of river nutrients exceeded the production increase simulated with an atmospheric warming scenario. Dissolved organic carbon is presently poorly represented in the model so its impact on production is hard to simulate. Applying established relationships between modeled DOC, total DOC, and light absorption we illustrate that DOC could play a very important role in modulating production. Our findings highlight the importance of developing more realistic river nutrient and discharge forcing for Earth System Models such that their impact on the critical Arctic coastal domain can be more adequately resolved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

WIRE: Resource-efficient Scaling with Online Prediction for DAG-based Workflows

This paper introduces WIRE that manages resources for the DAG-based workflows on IaaS clouds. WIRE predicts and plans resources over the MAPE (Monitor-Analyze-Plan-Execute) loops to: 1) Estimate task performance with online data, 2) Conduct simulations to predict the upcoming loads based on online estimates and workflow DAGs, 3) Apply a resource-steering policy to size cloud instance pools for the maximal parallelism that is consistent with low cost. We implement WIRE on Pegasus WMS/HTCondor and evaluate its performance on the ExoGENI network cloud. The results show that WIRE attains low resource cost with the performance that is typically within a factor of two of optimal.

Xie, Bing↗
DOE OSTI2024

Generalized Relationship Linking Water Balance and Vegetation Productivity across Site-to-Regional Scales

Evapotranspiration (ET) is a pivotal component in catchment-scale water balance and is essential for informed watershed management. Nevertheless, uncertainties in ET observation or modeling have been hindering effective water resources management. This study addresses this gap by establishing a robust, generalized linear relationship between ET and gross primary productivity (GPP) at the catchment scale. We test the linearity of the relationships between monthly GPP and ET data at 380 near-natural catchments across various climatic and landscape conditions in the contiguous U.S., yielding Pearson’s r ≥ 0.6 for 97% of the 380 catchments. We then develop a regionalization strategy to parameterize this GPP-ET relationship at the catchment scale by identifying and utilizing the linkages between the parameter values and extensively available hydroclimatic and landscape data. We demonstrate the efficacy of the proposed GPP-ET relationship and parameter regionalization strategy by their combined predictive capacity, where the predicted monthly GPP matches well with remote-sensing-based GPP product, achieving Kling-Gupta Efficient (KGE) values ≥ 0.5 for 92% of the catchments. In addition, we verify the relationship and its parameter regionalization at 35 AmeriFlux sites with KGE ≥ 0.5 for 25 sites, suggesting that the new relationship is transferable across the site, catchment, and regional scales. Furthermore, our findings are valuable for improving remote-sensing-based estimation of monthly ET and diagnosing coupled water–carbon simulations in land surface and Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lifting and Dropping VMs to Dynamically Transition Between Time- and Space-sharing for Large-Scale HPC Systems

As HPC environments increasingly integrate with edge based systems, system architectures will need to handle a broader class of workloads and scheduling requirements. One result of this shift will be the need to simultaneously support bulk-synchronous parallel (BSP) and on-demand service based applications on the same infrastructure. This in turn will require that future resource management approaches utilize both space-shared as well as time-shared resource scheduling strategies. In this work we introduce the concept of "VM-lifting'' (and its inverse "VM-Dropping'') which allows dynamically switching an HPC workload between space-shared and time-shared scheduling regimes. Our work targets co-kernel based HPC system software environments, in which multiple specialized OS kernels execute natively on dedicated physical resource partitions inside a single compute node. With VM-lifting, a native co-kernel can be migrated at runtime to and from locally hosted Virtual Machine Environments due to changing scheduling requirements of the node. This allows an HPC node to be dynamically (re-)configured as either a time-shared Infrastructure-as-a-Service (IaaS) resource or a dedicated space shared resource based on the current workload demands. We have implemented this approach in the context of the Hobbes Exascale System Software stack and have demonstrated that a node can be reconfigured with minimal impact on the running applications.

Gordon, Nick↗
DOE OSTI2023

Sustainable Water Management: Understanding the Socioeconomic and Cultural Dimensions

With the pressing challenges of water scarcity and pollution, achieving sustainable water management is imperative for promoting long-term development. Therefore, this paper aims to examine the socio-economic and cultural factors that shape the sustainability of water management strategies in Brazil and Portugal. This study highlights various factors that influence water management, including robust legal frameworks, socio-economic disparities, cultural practices, agricultural water usage, knowledge sharing, public participation, climate change resilience, water scarcity risks, industrial water consumption, and urbanization. By conducting a SWOT analysis of water management strategies, this research synthesizes information through an extensive literature review, encompassing the legal frameworks, policies, and implemented strategies in both countries. Additionally, it investigates comparative studies among Brazil, Portugal, and other European nations to facilitate the exchange of knowledge and experiences in water management practices. The findings of this study offer valuable insights into the strengths, weaknesses, opportunities, and threats associated with water management strategies in Brazil and Portugal, thereby guiding the development of tailored policies and strategies that foster sustainability in water resource management. Additionally, the research highlights the role of digital transformation in optimizing water management practices. By integrating socio-economic, cultural, and digital factors, this study contributes to effective and sustainable water management in Brazil and Portugal, ensuring responsible utilization and preservation of water resources.

Santos, Eleonora↗
DOE OSTI2024

Eligibility Assessment of Items in the TA-60 Rack Assembly and Alignment Complex Legacy Storage Yard

The U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office (NA-LA), documented and evaluated seven structures in the Technical Area 60 (TA-60) Rack Assembly and Alignment Complex (RAAC) legacy storage yard at Los Alamos National Laboratory (LANL or Laboratory) for listing in the National Register of Historic Places (National Register). This documentation and evaluation was conducted in compliance with Section 106 of the National Historic Preservation Act of 1966, as amended; the Code of Federal Regulations (36 CFR 800); the Programmatic Agreement among the U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office, the New Mexico State Historic Preservation Office and the Advisory Council on Historic Preservation Concerning Management of the Historic Properties at Los Alamos National Laboratory, Los Alamos New Mexico (PA)1; and A Plan for the Management of the Cultural Heritage at Los Alamos National Laboratory, New Mexico (LANL’s Cultural Resources Management Plan (2017). NA-LA makes the following National Register eligibility determinations: la cuna; the rack transporter (jeep, rack trailer, and steering dolly); the Mexia diagnostic rack; the Mexia device canister; the Mexia device mounting stand; and the Mexia target stand are eligible for listing in the National Register, and the second steering dolly is not eligible for listing in the National Register. This National Register evaluation was completed because LANL proposes to develop a consolidated waste facility in TA-60 next to the former RAAC. Across 3.56 acres, LANL proposes to construct an 8,000-square-foot, pre-engineered waste storage building; a 1,500-square-foot office/warehouse building; and 28,500 square feet of covered storage. The development will also include access control features and fencing, parking spaces, and utilities. Additionally, the Laboratory will continue to use the southern part of TA-60-0017 and reuse TA-60-0086 and TA-60-0324 in the development. The consolidated waste facility will operate as a central accumulation area—storing universal waste, mixed low-level (radioactive) waste, hazardous chemicals, and New Mexico special waste—until the waste can be shipped off site.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Running Ensemble Workflows at Extreme Scale: Lessons Learned and Path Forward

The ever-increasing volumes of scientific data combined with sophisticated techniques for extracting information from them have led to the increasing popularity of ensemble workflows which are a collection of runs of individual workflows. A traditional approach followed by scientists to run ensembles is to rely on simple scripts to execute different runs and manage resources. This approach is not scalable and is error-prone, thereby motivating the development of workflow management systems that specialize in executing ensembles on HPC clusters. However, when the size of both the ensemble and the target system reach extreme scales, existing workflow management systems face new challenges that hamper their efficient execution. In this paper, we describe our experience scaling an ensemble workflow from the computational biology domain from the early design stages to the execution at extreme scale on Summit, a leadership class supercomputer at the Oak Ridge National Laboratory. We discuss challenges that arise when scaling ensembles to several million runs on thousands of HPC nodes. We identify challenges with composition of the ensemble itself, its execution at large scale, post-processing of the generated data, and scalability of the file system. Based on the experience acquired, we develop a generic vision of the capabilities and abstractions to add to existing workflow management systems to enable the execution of ensemble workflows at extreme scales. We believe that the understanding of these fundamental challenges will help application teams along with workflow system developers with designing the next generation of infrastructure for composing and executing extreme-scale ensemble workflows.

Mehta, Kshitij↗
DOE OSTI2020

Better management practices for environmentally sustainable production of microalgae and algal biofuels

The commercialization of biofuels produced from microalgae is in its infancy; therefore, many resource-management practices and production processes are still flexible. The purpose of this paper is to guide development of supply chains toward more environmentally sustainable practices. Furthermore, in this work, we review current and projected technologies and practices for autotrophic microalgae cultivation that promote environmental sustainability. We develop a framework that leverages these studies to propose better management practices (BMPs) for water quality and quantity, biodiversity, or greenhouse gas emissions in concert with productivity and profitability considerations. Some proposed BMPs are linked to numerical environmental targets, such as percent reductions in nutrient loadings to streams, whereas others seek to avoid thresholds leading to adverse health or ecological effects. Still others involve using the best available technologies, developed iteratively through life-cycle and techno-economic analyses. Proposed BMPs for microalgae cultivation focus on water quality and quantity, as well as improving greenhouse gas (GHG) emissions to obtain advanced biofuel designation. BMPs must allow producers to meet productivity and profitability targets, as well as environmental targets. These example BMPs characterize the state of science and engineering; thus, they will change over time.

09 BIOMASS FUELS↗