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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Smart Grid Enabled EVSE

The combined team of GE Global Research, Federal Express, National Renewable Energy Laboratory, and Consolidated Edison has successfully achieved the established goals contained within the Department of Energy’s Smart Grid Capable Electric Vehicle Supply Equipment funding opportunity. The final program product, shown charging two vehicles in Figure 1, reduces by nearly 50% the total installed system cost of the electric vehicle supply equipment (EVSE) as well as enabling a host of new Smart Grid enabled features. These include bi-directional communications, load control, utility message exchange and transaction management information. Using the new charging system, Utilities or energy service providers will now be able to monitor transportation related electrical loads on their distribution networks, send load control commands or preferences to individual systems, and then see measured responses. Installation owners will be able to authorize usage of the stations, monitor operations, and optimally control their electricity consumption. These features and cost reductions have been developed through a total system design solution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Evaluating Basin-Scale Forest Adaptation Scenarios: Wildfire, Streamflow, Biomass, and Economic Recovery Synergies and Trade-Offs

Active forest management is applied in many parts of the western United States to reduce wildfire severity, mitigate vulnerability to drought and bark beetle mortality, and more recently, to increase snow retention and late-season streamflow. A rapidly warming climate accelerates the need for these restorative treatments, but the treatment priority among forest patches varies considerably. We simulated four treatment scenarios across the 3,450 km 2 Wenatchee River basin in eastern Washington, United States. We used a decision support tool (DST) to assess trade-offs and synergies within and among treatments on wildfire risk and smoke emissions, water yield and snow retention, biomass production, and economic return. Treatment scenarios emphasized prescribed burning ( BurnOnly ), biomass production ( MaxBiomass ), gap-based thinning to optimize water yield ( IdealWater ), and a principle-based restoration scenario ( RA1 ). Fire hazard, smoke emissions, and biomass production metrics were evaluated across scenarios using the Forest Vegetation Simulator, and water yields were modeled using the Distributed Hydrology Soil Vegetation Model. Simulations were summarized to both patch- (10 1 –10 2 ha) and subwatershed- (10 3 –10 4 ha) scales, and treatment effects were evaluated against an untreated baseline landscape. We used logic models to rank effect sizes by scenario across metrics along a continuum between −1 (no or weak effect) to +1 (large effect). All treatments produced benefits across one or more ecosystem services and led to synergistic benefits to water yield and wildfire hazard reduction. Tradeoffs among resource benefits were clear in wilderness where reliance on prescribed burning without mechanical treatment increased costs and eliminated the potential for biomass recovery. The BurnOnly scenario improved fire risk metrics and streamflow, but effect sizes were lower compared to other treatments. IdealWater showed the strongest benefits overall, demonstrating the ability to capture multiple resource benefits through spatially explicit thinning. Our study provides a framework for integrating strategic and tactical models that evaluate tradeoffs and synergies gained through varied management approaches. We demonstrate the utility of decision support modeling to enhance management synergies across large landscapes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

A hierarchical-multiobjective framework for risk management

A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.

Haimes, Yacov Y.↗
NASA NTRSDate not supplied

The Next Frontier for Remote Sensing of Freshwater HABS: Utilizing Imaging Spectroscopy Data to Identify Cyanobacteria Bloom Types

Cyanobacteria Harmful Algal Blooms (HABs) and their associated toxicity are a concern for inland waters. Due to the extensive spatial coverage and frequent data availability of satellite-based sensors, multi-spectral remote sensing tools have demonstrated utility for monitoring, understanding, and managing these blooms. The next frontier is utilizing high spectral resolution imaging spectroscopy data, such as from NASA’s upcoming PACE, GLIMR, and SBG missions planned for this decade, which allow for the development of more sophisticated cyanobacteria detection algorithms. We evaluate the performance of cyanobacteria genera differentiation algorithms using precursor datasets in support of these upcoming hyperspectral missions. In situ measurements of lake optical, biological, chemical, and physical properties are used to characterize cyanobacteria blooms in hypereutrophic Clear Lake, CA, USA, which supports large, diverse algal and cyanobacteria populations. Data collection occurred during 12 field events in 2021-2022 across all seasons. Three field events were conducted concurrently with hyperspectral data acquisitions from the DESIS sensor on the International Space Station. The results of this study will support the development of future tools utilizing satellite-based imaging spectroscopy data to identify the cyanobacteria genera present in a bloom, and thus the potential for cyanotoxin production. This outcome – the ability to quickly characterize a cyanobacteria bloom at a low cost – will have enormous benefits for public health.

remote sensing↗
DOE OSTI2011

Simulated population responses of common carp to commercial exploitation

Common carp Cyprinus carpio is a widespread invasive species that can become highly abundant and impose deleterious ecosystem effects. Thus, aquatic resource managers are interested in controlling common carp populations. Control of invasive common carp populations is difficult, due in part to the inherent uncertainty of how populations respond to exploitation. To understand how common carp populations respond to exploitation, we evaluated common carp population dynamics (recruitment, growth, and mortality) in three natural lakes in eastern South Dakota. Common carp exhibited similar population dynamics across these three systems that were characterized by consistent recruitment (ages 3 to 15 years present), fast growth (K = 0.37 to 0.59), and low mortality (A = 1 to 7%). We then modeled the effects of commercial exploitation on size structure, abundance, and egg production to determine its utility as a management tool to control populations. All three populations responded similarly to exploitation simulations with a 575-mm length restriction, representing commercial gear selectivity. Simulated common carp size structure modestly declined (9 to 37%) in all simulations. Abundance of common carp declined dramatically (28 to 56%) at low levels of exploitation (0 to 20%) but exploitation >40% had little additive effect and populations were only reduced by 49 to 79% despite high exploitation (>90%). Maximum lifetime egg production was reduced from 77 to 89% at a moderate level of exploitation (40%), indicating the potential for recruitment overfishing. Exploitation further reduced common carp size structure, abundance, and egg production when simulations were not size selective. Our results provide insights to how common carp populations may respond to exploitation. Although commercial exploitation may be able to partially control populations, an integrated removal approach that removes all sizes of common carp has a greater chance of controlling population abundance and reducing perturbations induced by this invasive species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Stem Inc. SunShot Incubator Program Final Technical Report

In this Energy Storage Control Algorithms project, Stem sought to develop tools and control algorithms to increase the value and reduce balance-of-system and grid integration costs associated with adding distributed solar generation to the grid. These advances fell under the headings SolarScope and SolarController. Stem sought to create initial market traction with a fully commercialized product for the solar industry to size storage systems (SolarScope) as well as a solar intermittency-mitigation framework for utilities (SolarController) in the course of the project. The company sought to align strategic growth plans and enable the rollout of the products to broader audiences in multiple geographic regions by leveraging the major solar companies in the national market as partners. Both final products were both intended to be commercialized. They are: SolarScope: Analysis tool to identify viable PV + storage projects and thereby expedite the sales and interconnection processes. SolarScope combines customer load data, PV production estimates, utility rate tariff, and simulated storage into a simple user interface for PV developers. Developers can easily identify viable solar + storage sites without the need for complex and time consuming, site-by-site spreadsheet modeling. SolarContoller: Tool to autonomously dispatch distributed storage in order to mitigate voltage fluctuation and reduce curtailment. SolarController co-optimizes, in real time, storage dispatch for circuit stability and curtailment reduction, enabling higher penetrations of PV. SolarController is automated, not requiring utility dispatch or management, as Stem hardware senses grid voltage, frequency, customer load, PV production, and power factor. In the end the two products met with different outcomes. SolarScope was tested by potential users, and continues to be used as a foundational platform for partnership with key solar industry partners. SolarController, on the other hand, was successful in lab testing but was not commercialized due to a lack of marketability and lack of interested customer base. Together the development of these two products marked a material step forward for Stem; and a new milestone along the pathway of integration for the solar and storage industries. SolarScope is leading to real, out-of-the-lab project development in storage + solar for the commercial customer sector. Meanwhile SolarController has opened the eyes of regulators and utility executives alike to the potential of distributed solar and by doing so, has moved the conversation forward for the integration of distributed energy resources more broadly on the grid.

25 ENERGY STORAGE↗
DOE OSTI2014

Utilization of Heat Pump Water Heaters for Load Management

The Energy Conservation Standards for Residential Water Heaters require residential electric storage water heaters with volumes larger than 55 gallons to have an energy factor greater than 2.0 after April 2015. While this standard will significantly increase the energy efficiency of water heaters, large electric storage water heaters that do not use heat pump technologies may no longer be available. Since utilities utilize conventional large-volume electric storage water heaters for thermal storage in demand response programs, there is a concern that the amended standard will significantly limit demand response capacity. To this end, Oak Ridge National Laboratory partnered with the Tennessee Valley Authority to investigate the load management capability of heat pump water heaters that meet or exceed the forthcoming water heater standard. Energy consumption reduction during peak periods was successfully demonstrated, while still meeting other performance criteria. However, to minimize energy consumption, it is important to design load management strategies that consider the home s hourly hot water demand so that the homeowner has sufficient hot water.

Boudreaux, Philip R↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be difficult to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Automatic flight phase classification will enhance efficiencies of ATM/ATC-like architectures for AAM/UAM. Classifying the main flight phases (takeoff, climb, cruise, descent, and landing) provides insight to ensure safe operations, provide situational awareness of the NAS, and monitor flights in case there are any emergencies. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight for flight phase classification by leveraging distributed sensing concepts.

distributed sensing↗
NASA NTRSDate not supplied

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be challenging to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Aircraft typically have the following flight phases: takeoff, climb, cruise, descent, and landing. Classifying these flight phases provides insight into ensuring safe operations, providing situational awareness of the NAS, and monitoring flights in emergencies. Automatic flight phase classification will enhance the efficiencies of ATM/ATC-like architectures for AAM/UAM, especially since numerous aircraft will be flying in highly dense urban environments. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight into flight phase classification by leveraging distributed sensing concepts. Simulation results and post-processed flight test results demonstrate the utility of HME for automatic and robust flight phase classification for real-time AAM operations.

distributed sensing↗
DOE OSTI2016

Evaluating the Magnitude and Duration of Cold Load Pick-up on Residential Distribution Feeders Using Multi-State Load Models

The increased level of demand that is associated with the restoration of service after an outage, Cold Load Pick-Up (CLPU), can be significantly higher than pre-outage levels, even exceeding the normal distribution feeder peak demand. These high levels of demand can delay restoration efforts and in extreme cases damage equipment. The negative impacts of CLPU can be mitigated with strategies that restore the feeder in sections, minimizing the load current. The challenge for utilities is to manage the current level on critical equipment while minimizing the time to restore service to all customers. Accurately modeling CLPU events is the first step in developing improved restoration strategies that minimize restoration times. This paper presents a new method for evaluating the magnitude of the CLPU peak, and its duration, using multi-state load models. The use of multi-state load models allows for a more accurate representation of the end-use loads that are present on residential distribution feeders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2024

Optimal Managed Fast-Charging Model for Electric Vehicle Fleets with High Utilization and Multiple Charge-Acceptance Curves

A predictive control/scheduling optimization model is proposed for managed charging of an electric vehicle (EV) fleet - under time-of-use energy and demand prices, high vehicle utilization frequency (short dwell times), multiple charge- acceptance curves (configurable charging rates), and flexible vehicle demand. This context is particularly relevant for flight schools (small electric aircraft) or other commercial facilities where an EV fleet performs multiple operating and fast-charging sessions on the same day. The proposed model performs both the operational and charging scheduling of the vehicles, which is not typically done for residential managed charging and significantly increases problem complexity. The problem is formulated as a MILP model and a case study of a small fast-charging station is presented. Results demonstrate a significant reduction in operating cost, mainly from peak shaving during high demand price periods, achieved by coordinating the operation of different vehicles, chargers and charging rates.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2010

Filling Knowledge Gaps with Five Fuel Cycle Studies

During FY 2010, five studies were conducted of technology families’ applicability to various fuel cycle strategies to fill in knowledge gaps in option space and to better understand trends and patterns. Here, a “technology family” is considered to be defined by a type of reactor and by selection of which actinides provide fuel. This report summarizes the higher-level findings; the detailed analyses and results are documented in five individual reports, as follows: • Advanced once through with uranium fuel in fast reactors (SFR), • Advanced once through (uranium fuel) or single recycle (TRU fuel) in high temperature gas cooled reactors (HTGR), • Sustained recycle with Th/U-233 in light water reactors (LWRs), • Sustained recycle with Th/U-233 in molten salt reactors (MSR), and • Several fuel cycle missions with Fusion-Fission Hybrid (FFH). Each study examined how the designated technology family could serve one or more designated fuel cycle missions, filling in gaps in overall option space. Each study contains one or more illustrative cases that show how the technology family could be used to meet a fuel cycle mission, as well as broader information on the technology family such as other potential fuel cycle missions for which insufficient information was available to include with an illustrative case. None of the illustrative cases can be considered as a reference, baseline, or nominal set of parameters for judging performance; the assessments were designed to assess areas of option space and were not meant to be optimized. There is no implication that any of the cases or technology families are necessarily the best way to meet a given fuel cycle mission. The studies provide five examples of 1-year fuel cycle assessments of technology families. There is reasonable coverage in the five studies of the performance areas of waste management and uranium utilization. The coverage of economics, safety, and proliferation resistance and physical protection in the five studies was spotty. Some studies did not have existing or past work to draw on in one or more of these areas. Resource constraints limited the amount of new analyses that could be performed. Little or no assessment was done of how soon any of the technologies could be deployed and therefore how quickly they could impact domestic or international fuel cycle performance. There were six common R&D needs, such as the value of advanced fuels, cladding, coating, and structure that would survive high neutron fluence. When a technology family is considered for use in a new fuel cycle mission, fuel cycle performance characteristics are dependent on both the design choices and the fuel cycle approach. For example, the use of the sodium-cooled fast reactor to provide recycle in either breeder or burner mode has been studied for decades, but the SFR could be considered for once-through fuel cycle with the physical reactor design and fuel management parameters changed. In addition, the sustained recycle with Th/U-233 in LWR could be achieved with a heterogeneous assembly and derated power density. Therefore, it may or may not be adjustable for other fuel cycle missions although a reactor intended for one fuel cycle mission is built. Simple parameter adjustment in applying a technology family to a new fuel cycle mission should be avoided and, if observed, the results viewed with caution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Advancing Asset Management in Water Infrastructure Systems

Aging water system infrastructure, including drinking water, wastewater, and stormwater, poses a growing challenge for utilities and municipalities. These water systems have well documented challenges with respect to their age, condition, and level of service. ASCE annual report cards consistently rate these infrastructure systems in the United States as underfunded, overcapacity, or past service life (ASCE 2025 Report Card). For example, Chini and Stillwell (2017) estimated that the mean water loss in drinking water systems, i.e., non-revenue water, is approximately 16% across the United States. These concerns are not just relegated to the United States, with Courtenay, British Columbia, identifying 17% of their water main pipes as in a ‘poor’ condition state, defined as a category condition 5 out of 5 (City of Courtenay, 2024). These cases illustrate the challenges utilities are facing to manage extensive networks of infrastructure to deliver a consistent and high level of service. For buried infrastructure such as water systems, studies suggest that preventative interventions can lead to lower maintenance costs and fewer service disruptions (Mazumder et al, 2018; Li et al, 2014). The demonstrated need and benefit of appropriately applied asset management is juxtaposed against the relatively sparse literature that evaluates water systems within an asset management construct. Since 2020, just 37 papers specifically reference asset management in the Journal of Water Resources Planning and Management. Of those, only a few specifically look to develop strategies for improved asset management. Therefore, we highlight four key research areas that represent opportunities for advancement of asset management research for water systems. First, advances in condition assessment and forecasting are needed to better estimate asset deterioration using diverse datasets. Second, machine learning (ML) and artificial intelligence (AI) hold promise for predictive maintenance and investment prioritization, though questions of generalizability and model transparency remain. Third, applying a value of information framework can guide utilities in making cost-effective sensor deployment and data collection decisions, to direct monitoring strategies towards data-informed asset management decisions. Finally, integrated infrastructure management is critical, requiring coordinated planning with other infrastructure systems and stakeholder engagement to reduce costs and enhance service delivery.

Chini, Christopher M.↗
DOE OSTI2013

Transmutation, Burn-Up and Fuel Fabrication Trade-Offs in Reduced-Moderation Water Reactor Thorium Fuel Cycles - 13502

Multiple recycle of long-lived actinides has the potential to greatly reduce the required storage time for spent nuclear fuel or high level nuclear waste. This is generally thought to require fast reactors as most transuranic (TRU) isotopes have low fission probabilities in thermal reactors. Reduced-moderation LWRs are a potential alternative to fast reactors with reduced time to deployment as they are based on commercially mature LWR technology. Thorium (Th) fuel is neutronically advantageous for TRU multiple recycle in LWRs due to a large improvement in the void coefficient. If Th fuel is used in reduced-moderation LWRs, it appears neutronically feasible to achieve full actinide recycle while burning an external supply of TRU, with related potential improvements in waste management and fuel utilization. In this paper, the fuel cycle of TRU-bearing Th fuel is analysed for reduced-moderation PWRs and BWRs (RMPWRs and RBWRs). RMPWRs have the advantage of relatively rapid implementation and intrinsically low conversion ratios. However, it is challenging to simultaneously satisfy operational and fuel cycle constraints. An RBWR may potentially take longer to implement than an RMPWR due to more extensive changes from current BWR technology. However, the harder neutron spectrum can lead to favourable fuel cycle performance. A two-stage fuel cycle, where the first pass is Th-Pu MOX, is a technically reasonable implementation of either concept. The first stage of the fuel cycle can therefore be implemented at relatively low cost as a Pu disposal option, with a further policy option of full recycle in the medium term. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins

This project titled “Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins” evolved in response to the Department of Energy’s (DOE) Funding Opportunity Announcement (FOA) Number DE-PS26-07NT43119. Also referred to as the Fort Collins Renewable and Distributed System Integration (RDSI) Project, the effort was undertaken by a diverse group of local government, higher education and business organizations; and was driven by three overarching goals: I. Fulfill the requirements of the DOE FOA’s Area of Interest 2: Renewable and Distributed System Integration; most notably, to demonstrate the ability to reduce electric system distribution feeder peak load by 15% or more through the coordinated use of Distributed Energy Resources (DER). II. Advance the expertise, technologies and infrastructure necessary to support the long term vision of the Fort Collins Zero Energy District (FortZED) and move towards creating a zero energy district in the Fort Collins “Old Town” area. III. Further the goals of the City of Fort Collins Energy Policy, including the development of a Smart Grid-enabled distribution system in Fort Collins, expanded use of renewable energy, increased energy conservation, and peak load reduction. Through the collaborative efforts of the partner organizations, the Fort Collins RDSI project was successful in achieving all three of these goals. This report is organized into two distinct sections corresponding to the two phases of the project: • Part 1: Feeder Peak Load Reduction and the FortZED Initiative. • Part 2: Forming and Operating Utility Microgrids and Managing Load and Production Variability The original project scope addressed the Part 1 feeder peak load reduction. That work took place from 2009 through 2011 and was largely complete when the project scope was amended to include a demonstration of microgrid operations. While leveraging the assets, partner relationships, and lessons learned from Part 1, Part 2 was managed and executed as a distinct and substantially independent sub-project during the spring and summer of 2013. Both Parts 1 and 2 of the overall RDSI project can be viewed as cohesive stand-alone bodies of work and are presented as such within this report. In addition to the narratives, this document includes two Appendices that were compiled to supplement information about the various aspects of activities performed during Parts 1 and 2 of the project. Moreover, these Appendices are organized (as outlined below) so as to directly relate to the narratives in Part 1 and 2 of this report. • Appendix - Part 1: describes the roles of each project participant in regards to the feeder peak load reduction effort, and • Appendix - Part 2: deals with the microgrid research/demonstration.

14 SOLAR ENERGY↗
DOE OSTI2024

Li-Ion Battery Thermal Characterization for Thermal Management Design

Battery design efforts often prioritize enhancing the energy density of the active materials and their utilization. However, optimizing thermal management systems at both the cell and pack levels is also key to achieving mission-relevant battery design. Battery thermal management systems, responsible for managing the thermal profile of battery cells, are crucial for balancing the trade-offs between battery performance and lifetime. Designing such systems requires accounting for the multitude of heat sources within battery cells and packs. This paper provides a summary of heat generation characterizations observed in several commercial Li-ion battery cells using isothermal battery calorimetry. The primary focus is on assessing the impact of temperatures, C-rates, and formation cycles. Moreover, a module-level characterization demonstrated the significant additional heat generated by module interconnects. Characterizing heat signatures at each level helps inform manufacturing at the design, production, and characterization phases that might otherwise go unaccounted for at the full pack level. Further testing of a 5 kWh battery pack revealed that a considerable temperature non-uniformity may arise due to inefficient cooling arrangements. To mitigate this type of challenge, a combined thermal characterization and multi-domain modeling approach is proposed, offering a solution without the need for constructing a costly module prototype.

25 ENERGY STORAGE↗
DOE OSTI2019

Imaging post-stereotactic body radiation therapy responses for hepatocellular carcinoma: typical imaging patterns and pitfalls

Stereotactic body radiation therapy (SBRT) has increased utility in the management of hepatocellular carcinoma (HCC) ranging from local therapy in early-stage HCC not suitable for other focal therapies to end-stage HCC. As the indications for the use of SBRT in HCC expand, diagnostic imaging is being increasingly used to assess response to treatment. The imaging features of tumor response do not parallel those of other focal therapies such as radiofrequency ablation or trans-arterial chemoembolization that immediately devascularize the tumor. The tumor response to SBRT on imaging takes much longer and often shows gradual changes including the reduction of enhancement and size over several months. It is essential to recognize the typical imaging patterns of response, as well as the appearance of focal liver reaction in the non-target liver that can confound image interpretation. The timing of treatment response assessment imaging is fundamental to minimize the potential for false negative response. The purpose of this article is to review the variable post-SBRT imaging features of HCC and adjacent liver parenchyma and discuss the potential pitfalls of imaging evaluation after SBRT for HCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗