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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Online Prototype Toolset for Predicting and Optimizing P&T Performance (FY23 Status Report)

A new web-based toolset is being developed to support ongoing remediation optimization efforts and implementation of an adaptive site management strategy for the 200 West Area Pump-and-Treat (P&T) system at the Hanford Site. This toolset, comprising the well performance index tool and the well optimization pre-screening tool, will offer a user-friendly interface to predict and optimize the P&T well network’s performance at a preliminary level. Efforts in fiscal year (FY) 2023 focused on three main components: updating the existing deep learning model for predicting P&T performance, designing and developing a prototype of a web-based performance index tool, and initiating the conceptual design of the well optimization pre-screening tool. The well performance index tool is based on a pre-trained deep learning model that allows users to select a target contaminant and well screen length, then visualize the predicted performance of potential new wells across the site. The well optimization pre-screening tool includes two separate modules: the pre-computed scenario viewer, which organizes and visualizes offline optimization simulation results, and the quick analysis module, which provides real-time model prediction using user-specified well locations. In FY24, the plan is to add web-based applications to SOCRATES for both the well performance prediction tool and the optimization prescreening tool, with accompanying user and theory guides. These tools are intended to enable an accessible, easily applied, and transparent approach to remedy planning and decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗
DOE OSTI2026

Report on Coastal Structure Integrated Wave Energy Converters (CSI-WECs)

This report investigates a largely underexplored, and underexploited, application for wave energy: coastal structure integrated wave energy converters (CSI-WECs). These WEC types have significant potential to rapidly advance the wave energy industry while addressing the challenges of coastal community resiliency and marine energy integration and application, and the urgent need for increased coastal protection. To further support the value proposition investigation of this work, three wave energy developers agreed to conduct an energy production analysis of their technology for the four sites identified. Additionally, a geographic information system-based tool was developed that supports efficient and comprehensive site assessment for optimal and high-value deployments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Certifying the Performance of Fixative Technologies under Open Air Demolition Activities for D and D - 20096

Department of Energy (DOE) facilities undergoing deactivation and decommissioning (D and D) activities struggle with safety concerns of residual radioactive contamination leftover after gross decontamination efforts have concluded. The positive effects of implementing fixative technologies for decommissioning and maintenance is known across the DOE complex. However, there is no standardized metric in place that quantifies the performance of these technologies such as incombustible fixative platforms that immobilize the contamination in a solid polymer material under normal operating conditions or when exposed to stressors. The primary focus of this research is to provide the empirical data necessary to properly characterize the effects of implementing fixative technologies on mitigating the release of contamination. In addition, this effort has been used to identify and establish uniform testing protocols to quantify operational parameters of fixating platforms and properly credit such systems under a variety of operational conditions and stressors that can arise during open air demolition efforts (e.g. impact, water, thermal, etc.). The established protocols will be provided to the ASTM International E10.03 Subcommittee on Radiological Protection for Decontamination and Decommissioning of Nuclear Facilities and Components for the potential of formal standardization. Attributes to be addressed during testing are material compromise from impact stress, thermal stress for incombustible fixative materials, and immobilization factors (how well an immobilizing platform is capable of retaining fixated material during thermal and impact stressors). In developing these test methods, a greater understanding of the material's behavior under anticipated and unanticipated events, such as decommissioning activities and contingency events as outlined in the Basis of Interim Operations (BIO), can be successfully characterized. There are several key components of the experimental methodology that is essential in empirically certifying fixative technologies. A surrogate contaminant with a unique signature has been utilized with the implementation of a uniform contamination process of test coupons that is quantifiable and replicable for direct fixative comparisons. A modular test chamber has also been used to apply the various stressors of interest. Collection of released contamination that includes airborne and resettled contaminant particles and analyzed using mass spectrometry. This research directly supports DOE complex-wide concerns in terms of final disposition of nuclear facilities and the considerations made during their time between ceasing facility operation and final disposition. The results of this effort aims to provide a standardized road map and logical decision flow to better facilitate fixative technologies into D and D activities required to achieve the desired facility end state. (authors)

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

Considerations for Managing DOE Standard Canisters within an Over-canister as Part of an Integrated Waste Management System PPT

To better enable informed decision making regarding the back-end of the nuclear fuel cycle, the Integrated Waste Management Program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring research into a comprehensive integrated waste management system (IWMS) that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). An important aspect of the IWMS is DOE-managed Spent Nuclear Fuel (SNF). DOE and its predecessor agencies have generated, transported, received, stored, and reprocessed SNF at DOE facilities nationwide, and DOE is responsible for managing the SNF currently in its possession. These fuels come from a wide range of reactor types that employ various cladding materials, fuel materials, and enrichments. To enable interim, road-ready dry storage (RRDS) of the wide variety of SNF types found in the DOE inventory, a standardized canister system (i.e., the DOE Standard Canister) was proposed for the packaging demonstration. This robust, welded canister system is designed to confine radionuclides, prevent criticality by precluding content moderation, and satisfy other requirements as part of a larger storage, transportation, and disposal system. While SNF has yet to be loaded into a DOE Standard Canister, DOE Standard Canister designs were included in past storage facility and disposal facility design licensing endeavors. In a renewed effort to evaluate packaging SNF at Idaho National Laboratory (INL) in a RRDS configuration, researchers are planning the RRDS Packaging Demonstration. This demonstration is supplemented by analytical structural, criticality, and material compatibility evaluations that support management of SNF in DOE Standard Canisters, taking advantage of past analysis work to the extent possible. One of the largest differences between the current Packaging Demonstration and past analytical evaluations is the inclusion of an over-canister containing multiple DOE Standard Canisters. For the Packaging Demonstration, DOE Standard Canisters loaded with SNF are planned to be placed in a larger diameter over-canister. The sealed over-canister could then be placed in a storage overpack for onsite storage, or in a transportation overpack for shipment to an offsite storage location or disposal site once one becomes available. This paper examines the relevant considerations and provides a preliminary evaluation of integrating the over-canister configuration into the storage, transportation, and disposal processes of the overall waste management system. For storage and transportation, the over-canister can be considered analogous to a multi-purpose canister (MPC) for commercial SNF. For disposal, the DOE Standard Canisters could be removed from the over-canister and placed in a co-disposal waste package with canisters containing vitrified high-level radioactive waste (HLW) similar to configurations examined previously, or the sealed over-canisters might be capable of direct disposal in a waste package.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Draft Summary Report on Irradiated Fuel Handling and Management for LOTUS

The National Reactor Innovation Center (NRIC) has conceptualized the design of the Laboratory for Operation and Testing in the United States (LOTUS) test bed to provide the United States Department of Energy (DOE) with the infrastructure necessary to make advanced reactor designs available for commercial developers. LOTUS will provide a test bed to developers with the capabilities of supporting a wide range of experiment design possibilities. Upon completion of the developers’ operations and experiments within the test bed, the irradiated fuel, reactor components, and other experiment materials must be removed. Idaho National Laboratory (INL) possesses significant capabilities for radioactive material handling such as casks, carts, and forklifts. However, given the unique environment presented by the NRIC-LOTUS test bed, located inside the Zero Power Physics Reactor (ZPPR) Perimeter Intrusion Detection and Assessment System (PIDAS) area at the Materials and Fuels Complex (MFC) and the complexity of novel removal activities of recently operated reactor experiments through the new proposed access tunnel. The efficacy was not apparent for existing equipment to provide all the needed capability. To bridge the potential gaps in cask designs, storage, and transportation, NRIC requested the development of trade studies for the transfer, handling, and storage requirements of irradiated fuel salts and other radioactive materials. NRIC directed Boston Government Services, LLC (BGS) to perform the trade studies and develop a report analyzing alternatives. In addition to the BGS reports, the Idaho National Lab’s (INL), provided by the first potential user’s Advanced Reactor Development (ARD) team, prepared a feasibility study for the storage of specific irradiated fuel within the existing ZPPR vault.This summary report is intended to present the trade studies, options, and alternatives that were investigated. The maturity level of LOTUS, the reactor, fuel salt containers, gloveboxes, and reactor testing campaign and concept of operations were not at a level sufficient to base critical decisions on. This report is not intended to present a final recommendation. The final recommendations for fuel storage location, transport, handling equipment, and operations will be made in FY 2024 and will be based on known materials, test campaign requirements, funding, and final analysis of the fuel and equipment to be used.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Satellite Data Applications for Sustainable Energy Transitions

Transitioning to a sustainable energy system poses a massive challenge to communities, nations, and the global economy in the next decade and beyond. A growing portfolio of satellite data products is available to support this transition. Satellite data complement other information sources to provide a more complete picture of the global energy system, often with continuous spatial coverage over targeted areas or even the entire Earth. We find that satellite data are already being applied to a wide range of energy issues with varying information needs, from planning and operation of renewable energy projects, to tracking changing patterns in energy access and use, to monitoring environmental impacts and verifying the effectiveness of emissions reduction efforts. While satellite data could play a larger role throughout the policy and planning lifecycle, there are technical, social, and structural barriers to their increased use. We conclude with a discussion of opportunities for satellite data applications to energy and recommendations for research to maximize the value of satellite data for sustainable energy transitions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from quantitative models inform actions ranging from short-term and local decisions, such as those about technology and infrastructure deployment, and global and long-term negotiations and targets. Computational limits require model designers to balance coverage and resolution (i.e., breadth versus depth). Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses with less resolution than models that focus on a single sector's energy use. GCAM balances global supply and demand of all energy carriers projecting prices using internal calculations for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This globally comprehensive model was used to frame the Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050, which the White House released in 2021 and has been used to inform national and global economy-wide climate change mitigation discussions and strategy development for decades. Unlike GCAM, sectoral models focus on a portion of the energy sector and with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects electricity system capacity expansion and operation with high-fidelity representation of emerging technologies for deep decarbonization, such as variable renewable energy and energy storage, and integration of these technologies into the electric grid. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices, with a focus on adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of electrification and energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas mitigation strategies in the United States. The integrated multisector and sector-specific modeling approaches represented by GCAM and these sectoral models are complementary. The integrated multisector approach calculates energy pricing and resource allocation within the model, which is important for consistency when future conditions substantially diverge from current conditions in transformative scenarios. The sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and trade-offs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and it addresses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Dispatch Schedule Generation for Demand Flexibility Measures

This supplemental document describes the methodology used for determining the dispatch timing of various EUSS demand flexibility measures. Demand flexibility measures are designed to reduce/dispatch electricity demand in buildings during especially beneficial/critical times. The method used in this work utilizes predictions of building loads to generate a schedule that reflects the periods when the building's daily peak load occurs to support decision making in demand flexibility measures. The dispatch schedule generation method described in this document creates an hourly schedule that includes a load dispatch (peak) window for each day for a whole year based on load prediction, with options using different prediction methods: perfect prediction, bin-sampling method, fixed schedule, and outdoor air temperature (OAT)-based prediction method. The perfect prediction method performs a simulation to obtain the annual load profile as predicted load, representing the scenario of perfect load prediction. The bin-sampling method (1) categorizes days into representative bins by temperature characteristics, (2) performs simulations on sample days from each of those bins to create representative (or predicted) load, and (3) assigns representative loads for all days in a year based on the bin categorization. The fixed schedule method defines uniform start and end time of peak window with assumed fixed daily peak time, for all days in a season or a year. The OAT-based prediction method uses the statistics of OAT (minimum and maximum) as the indicators of peak load, with specified delay response time from building loads to temperature. Given the load prediction, daily peak periods are determined as a time window with specified length in each day that include the predicted daily peak load and with a secondary rule such as maximizing energy saving potential. The dispatch schedule generation method is not a standalone measure and is intended to be combined with other demand flexibility measures that could leverage the peak schedule and apply demand controls on specific systems or devices for demand response, such as measures described in "Measure Documentation - Thermostat Control for Load Shedding" and "Measure Documentation - Thermostat Control for Load Shifting".

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Software Control Program For Transportable Microgrid State-of-charge Balancing And Frequency Stability Controls

A deterministic state-of-charge (SOC) balancing approach software control code is introduced as an integral secondary management to primary control layer of an islanded small microgrid or nanogrid system made up of multiple grid-forming inverter/battery/solar combination systems, where each set of batteries with each inverter are on independent DC buses (i.e. non-paralleled on the DC sides). A DERMS-level control approach, algorithm and automation controller program was developed to improve coordination and enable microgrid asset compliance and SOC balancing, enabling provision of a system-level power stability support architecture, load support, and asset scalability. The architecture is configured to treat each unit or micro/nano-grid as a node in a microgrid network, allowing for autonomous DERMS control regarding load and SOC balancing and power stability. As the network grows with the addition of units, greater coordination efforts may be required. The ideal small network microgrid ranges from 2-10 inverter/battery units before additional control parameters must be considered in the existing architecture. The control approach focuses on a deterministic state-of-charge analysis as the primary level control process followed by a secondary control loop using a forced frequency-watt droop strategy to conform off-the-shelf components into behaving under a leader-follower configuration. Adopting this control scheme has been shown to allow for a balanced, unit-coordinated microgrid network, enabling stable power flow. The deterministic state-of-charge approach is introduced as an integral primary control layer of an islanded small network microgrid. A standard strategy for SOC balancing is implementing a battery management system (BMS) to control SOC on the DC side. An alternative approach is to determine how to coordinate sending and receiving power on the AC side with multiple units. The latter approach assesses all the integrated units in the microgrid network. Once the individual units are identified, further system data is required to calculate each unit's total kWh, provided information about its capability to supply or consume kWh and availability. The secondary control layer in the multi-layered small network microgrid methodology uses the primary layer’s decision to initiate frequency setpoint changes, initializing the SOC balancing. The secondary control layer considers numerous system-dependent variables to enable a charging and discharging profile based on adjustable frequency setpoints. The combined architecture will result in stable, coordinated power flow enhancing an AC microgrid's functionalities.

Myers, KurtS [Idaho National Laboratory (INL), Ida↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2024

ILAW Container Cost Reduction and Optimization Study

This study, performed on behalf of Washington River Protection Solutions (WRPS), examines the potential for making cost savings for the Immobilized Low Active Waste (ILAW) containers over the mission life of the Waste Treatment and Immobilization Plant (WTP). it builds on earlier study assessments 24590-LAW-RPT-M-01-001 Rev 0 ILAW Product Container Specifications Optimization Study and DOE/ORP-2013-02 Rev 0 Decision Analysis of Low-Active Waste Container Finishing Handling System Alternatives. The WTP design and installed equipment has evolved over an extended period ~20 years. Consequently, some of the existing requirements relating the ILAW containers may no longer be applicable under current mission plans where the glass filled containers are placed into the Integrated Disposal Facility (IDF) rather than stacked in an engineered purpose-built ventilated store as originally envisioned. The study team reviewed available WTP project reference documents to establish the functions the container must perform and assign requirements against each of these functions. With the assumptions that some of the existing WTP contract restrictions would not necessarily apply to the subsequent facility operations contract the container requirements were reviewed to identify those which were ‘hard constraints‘, imposed by regulatory requirements. Initially each of these hard constraints were reviewed, evaluated and documented to see if they precluded the use of an alternate less expensive material of construction, carbon steel, to the existing 304 L stainless steel in the current container specification. That review did not generate any fatal flaws for a change in material of construction to carbon steel allowing the study team to examine the impacts of material cost savings, potential changes to the design and requirements and impacts on interfaces of the containers with the existing WTP process equipment from container receipt, transfers, glass filling, cooling and export. In addition, a change in container target fill level was evaluated and qualitative, and quantitative where feasible, impacts to the container fabrication process assessed. Lastly, additional follow on development or testing activities to support the use of carbon steel were assessed and a recommended path forward with a ROM cost and timescale developed.

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

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Chapter 13: All-Electric Vertical Take-Off and Landing Aircraft (eVTOL) for Sustainable Urban Travel

Increasing urbanization, ground congestion, and greenhouse gas emissions have spurred aircraft pioneers to capitalize on advancements in battery technology, electric motors, software, and other advances to develop all-electric vertical take-off and landing (eVTOL) aircraft intended to save travelers time within densely populated urban regions. This study served as an example for conducting a life-cycle analysis (LCA) of an eVTOL aircraft, analyzing its manufacturing process, its in-life operation as a passenger transportation service between urban locations, and (in part) end-of-life treatment. This case study aims to provide guidance on how to accurately conduct eVTOL LCA, particularly on how to define the problem, how to obtain the right information from engineers inside and outside their own organizations, and what areas to focus on. As LCA results are only as accurate as the assumptions that were made, a more rigorous LCA that includes sensitivity analysis and uncertainty characterization can help further understand the limitations of those assumptions. New technologies such as blockchain may also play an important role in LCA, including the life-cycle inventory and improving confidence intervals. Completing a credible LCA is central to supporting the argument in favor of introducing the new technology. Completing such a study will allow companies to demonstrate to relevant stakeholders the likely impact of their aircraft on the environment by quantifying the operational climate footprint of the aircraft and the manufacturing process used to build it. To this end, this case study also provides examples of how to report and present LCA results, optimizing for communications to non-LCA experts. The LCA can also assist in identifying opportunities to improve the environmental performance at various life-cycle stages, informing decision makers as products and manufacturing processes evolve or are redesigned. Given the nascency of both eVTOL aircraft manufacturing and operations, it is strongly recommended that LCA analysts treat reports on eVTOL aircraft as works-in-progress. As new information is found, design changes are made, and the aircraft or operation gains maturity, it is inevitable that some amendments will need to be made to the LCA. It is suggested that a complete overhaul of the LCA be made every 18-24 months throughout the R&D, design, and operational scale-up phases of the project.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Viability of S3 Object Storage for the ASC Program at Sandia

Recent efforts at Sandia such as DataSEA are creating search engines that enable analysts to query the institution’s massive archive of simulation and experiment data. The benefit of this work is that analysts will be able to retrieve all historical information about a system component that the institution has amassed over the years and make better-informed decisions in current work. As DataSEA gains momentum, it faces multiple technical challenges relating to capacity storage. From a raw capacity perspective, data producers will rapidly overwhelm the system with massive amounts of data. From an accessibility perspective, analysts will expect to be able to retrieve any portion of the bulk data, from any system on the enterprise network. Sandia’s Institutional Computing is mitigating storage problems at the enterprise level by procuring new capacity storage systems that can be accessed from anywhere on the enterprise network. These systems use the simple storage service, or S3, API for data transfers. While S3 uses objects instead of files, users can access it from their desktops or Sandia’s high-performance computing (HPC) platforms. S3 is particularly well suited for bulk storage in DataSEA, as datasets can be decomposed into object that can be referenced and retrieved individually, as needed by an analyst. In this report we describe our experiences working with S3 storage and provide information about how developers can leverage Sandia’s current systems. We present performance results from two sets of experiments. First, we measure S3 throughput when exchanging data between four different HPC platforms and two different enterprise S3 storage systems on the Sandia Restricted Network (SRN). Second, we measure the performance of S3 when communicating with a custom-built Ceph storage system that was constructed from HPC components. Overall, while S3 storage is significantly slower than traditional HPC storage, it provides significant accessibility benefits that will be valuable for archiving and exploiting historical data. There are multiple opportunities that arise from this work, including enhancing DataSEA to leverage S3 for bulk storage and adding native S3 support to Sandia’s IOSS library.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100): Final Report

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a comprehensive analysis based on extensive stakeholder input of possible pathways for Puerto Rico to achieve its goal of 100% renewable energy by 2050. PR100 was an integrated effort drawing on expertise and capabilities of the contributing national laboratories that explored possible pathways for Puerto Rico to achieve its goal of 100% renewable energy in the long term (by 2050), increase reliability and resilience in the immediate term (within the next few years), and work toward energy justice. The purpose of the study is to provide decision support and inform investment decisions for implementers of Puerto Rico's energy transition. See NREL/TP-6A20-88614 for the Spanish translation of this report.

100% renewable energy target↗
DOE OSTI2024

Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY24 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., 200 DV-1 Operable Unit), particles need to be delivered a sufficient radial distance from an injection well and retained at concentrations high enough for effective treatment. An accurate description of the particle radius of influence (ROI) is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capabilities and a lack of experimental data to validate and parameterize particle transport models. To help build toward field-scale deployment, this fiscal year (FY) we have (1) developed a pre screening tool to estimate particle transport, (2) implemented particle transport models within PFLOTRAN, and (3) conducted preliminary estimations of particle ROI. While field-scale numerical simulations will ultimately be necessary before remedy design and field implementation, we have developed a pre-screening tool that offers valuable estimations of expected particle injectability and ROI in a 1-D system. The advantage of the tool is that it does not require extensive laboratory experiments and instead makes predictions based solely on routine laboratory measurements. This tool can assist in down-selection and decision-making by identifying which particle amendment systems are worth pursuing in future laboratory experiments, such as 1-D column tests and beyond. With any system, scaling up from the lab to the field presents challenges. Currently, there is no field data available for model calibration or validation. However, the theoretical particle models being developed herein are the best tools available to guide progress toward field deployment. To help bridge this gap and verify model predictions, larger-scale lab experiments are being proposed. To advance simulation capabilities, six particle transport models are being integrated into the reactive transport simulator PFLOTRAN. These include colloid filtration theory (CFT) and five additional particle transport models (M1-M5). Each model, from M1 to M5, progressively incorporates additional particle transport and retention processes. Ultimately, the simplest model capable of accurately describing 1-D column data will be selected and parameterized. During FY24, the CFT and M1 model have been fully implemented within PFLOTRAN. Using an existing 1 D column experiment, the two currently implemented particle transport models (CFT and M1), and associated parameters, were fit to this experiment. While simpler model formulations are helpful for estimations, these formulations could not fully describe particle transport and retention behavior in the previous 1-D column experiment. Thus, additional complexities will need to be considered, which will be accounted for in the M2-M5 model formulations. Additionally, because a viscous, shear thinning fluid was required to keep particles in suspension, considerations for flow will also need to also be accounted for. Therefore, a new immiscible two-phase flow mode is currently being implemented in PFLOTRAN. With some modifications, this new flow module could also support simulation of non-Newtonian liquid amendments, foams, and emulsions. We also estimated the expected ROI of solid amendments using 1-D simulations. The average predicted ROI was approximately 15 ft for micron-sized zero valent iron (mZVI) suspended in xanthan gum (XG). Using the pre screening tool and ROI estimates, additional amendment-delivery laboratory characterization and experiments are proposed. The results from additional experiments can be used to validate and parametrize particulate transport model formulations, which will ultimately provide predictive capabilities for field amendment-delivery systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗