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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CORE DESIGN AND NEUTRONIC ANALYSIS OF THE EUROPEAN SODIUM FAST REACTOR WITH METALLIC FUEL

The current ESFR (European Sodium Fast Reactor) design was proposed and in-depth evaluated in the frame of the past ESFR-SMART project. As a follow-up project, the ESFR-SIMPLE has been launched with the aim of challenging the current commercial-size ESFR design in terms of safety features and economic performance. Among the new safety measures to be developed and assessed in ESFR-SIMPLE, the current oxide fuel ESFR design will be challenged by a modified version of the core with metallic fuel. This intends to conclude on what types of benefits can be obtained with high-density fuel, under similar safety and design constraints. In this paper, the designing approach for enabling the use of metallic fuel in the current ESFR core is described and a preliminary neutronic evaluation is carried out. The optimal configuration is established through the optimization of key neutronic parameters aiming at the potential reduction of the plutonium inventory. The resulting core configuration serves as a basis for further safety assessment analyses, which will provide insight into the advantages and drawbacks of the two types of fuels.

Jiménez-Carrascosa, Antonio↗
DOE OSTI2020

Steady-state off-design modeling of the supercritical carbon dioxide recompression cycle for concentrating solar power applications with two-tank sensible-heat storage

Concentrating solar power researchers are evaluating the potential of the supercritical carbon dioxide recompression cycle to improve the thermal efficiency and decrease the capital costs of next-generation systems. This analysis investigates the steady-state off-design performance of a recompression cycle integrated with two-tank sensible-heat thermal energy storage as the ambient temperature and heat-transfer fluid (HTF) inlet conditions to the cycle change. This paper presents off-design component models and then cycle convergence and control models to maximize net cycle power output while constraining the high-side pressure and air-cooler fan power to their respective design values and fixing the cycle HTF outlet temperature to its design value. Results show that inventory control and air-cooler fan power are important control parameters that can be optimized to maximize off-design power output as the ambient temperature and HTF mass flow rate diverge from design. The high-side pressure and fan power constraints cause the cycle net power to degrade when the ambient temperature is warmer than the design value, and this study calculates a maximum mass flow rate for hot days above which the cycle cannot achieve the design HTF outlet temperature. Finally, the analysis shows that optimizing compressor shaft speeds can improve cold-day performance by around 1.5 percentage points and part-load performance by up to 2.5 percentage points versus a baseline case with no active compressor control.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

An Automated Medical Inventory System (AMIS) to Enable Earth-Independent Medical Operations

BACKGROUND: Inventory of medical consumables and durables (medications, treatment aids, diagnostic equipment, etc.) aboard the International Space Station is a manual process whereby crewmembers reach out to their flight surgeon to relay when items are used. Performing a full medical system inventory is time intensive. However, as exploration progresses to long duration missions with little to no resupply or evacuation capabilities, maintaining an accurate account of inventory and location for medical systems across the mission will become increasingly critical. A new system must be developed for future exploration missions to meet the need for a crew-facing, real time method of managing medical inventory. OVERVIEW: NASA’s Exploration Medical Integrated Product Team (XMIPT) is funding the AMIS project to mature the technology readiness level and to conduct a flight demonstration of a medical inventory capability. AMIS will leverage lessons learned from a Medical Consumables Tracking project previously demonstrated aboard the ISS in 2016 and 2017. Key components of AMIS include a database, supporting hardware and software, and interfaces to power, communications, or other vehicle or medical systems. Some medical inventory capability may be provided by the vehicle inventory management system which relies upon RFID-based technology and can track larger items such as medical kits or medical hardware. AMIS will augment these capabilities to enable tracking of individual medical kit contents. Efforts are underway to characterize the optimal solution trade space by comparing system specifications (e.g. mass and volume, etc.) across maintenance and operational use cases (e.g. crew time saved, total inventory automated, etc). DISCUSSION: The contents of a Mars Medical System have not been fully defined which poses challenges to defining an inventory system and requires assumptions regarding medical kit contents and medical system design. Other important considerations include minimizing crew time required, avoiding access restrictions to medical inventory in the event of an emergency, and ensuring that data is accessible to other medical system elements to enable crew autonomy in provision of medical care.

Automated Medical Inventory System↗
NASA NTRSDate not supplied

Generating a 4D Global CH(4) Product by Assimilating TROPOMI column CH(4) in NASA’s GEOS GCM

Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.

Nikolay V. Balashov↗
DOE OSTI2024

Lithium inventory tracking as a non-destructive battery evaluation and monitoring method

Tracking the active lithium (Li) inventory in an electrode shows the true state of a Li battery, akin to a fuel gauge for an engine. However, non-destructive Li inventory tracking is currently unavailable. Here, in this work, we used the theoretical capacity of a transition metal oxide to convert capacity into a Li inventory analysis. The Li inventory in electrodes was tracked reliably to show how battery formulations and test methods affect performance. Contrary to capacity, Li inventory tracking reveals stoichiometric variations near the electrode–electrolyte interface. Verifiable results rationalized differences in measurements, clarifying and reducing interferences from cell formulations and experimental manipulations. By tracing four variables from formation to end-of-life, we characterize electrode and cell performance with a thermodynamic framework. Accurate rationalization of subtle differences in Li inventory utilization promises precise battery engineering, evaluation, failure analysis and risk mitigation. The method could be applicable from cell design optimization and fabrication to battery management, improving battery performance and reliability.

25 ENERGY STORAGE↗
DOE OSTI2024

Application of Process Chemical Modeling to Optimize Radioactive Waste Disposal at the Savannah River Site – 24242

The Liquid Waste Program (LWP) managed by Savannah River Mission Completion (SRMC) is responsible for the treatment and disposal of waste at the Savannah River Site (SRS). Radioactive waste at SRS is stored and processed at four key facilities – each with their respective functions to store, blend, grout, or vitrify waste. The tank farm, where waste is stored, consists primarily of legacy waste with new material incoming from the Accelerated Basin De-inventory program (ABD), which is managed by Savannah River Nuclear Solutions (SRNS). System planning is done by SRNS and SRMC to optimize ABD and LWP operations, respectively.

Georgiou, Andreas↗
DOE OSTI2025

Scoping Analysis of Pebble-Bed Reactors for the Destruction of the Transuranic Inventory of LWR Spent Nuclear Fuel

With the forecasted increase in the construction and operation of nuclear reactors, there will be a corresponding increase in the quantity of spent nuclear fuel (SNF) that requires long-term storage. In SNF, transuranic isotopes contribute the most to the long-term radiotoxicity of the fuel and pose a proliferation risk. One option that has been explored to address these issues is the removal of the transuranic isotopes from SNF and the conversion of these isotopes into transuranic fuel (TRU fuel). Here, this work sought to determine how effective a micro-modular Pebble-Bed High-Temperature Gas-Cooled Reactor (PB-HTGR); the 10-MW High Temperature Gas-cooled Test Reactor (HTR-10); and a salt-cooled small-modular pebble-bed reactor (PBR), i.e. the generic Fluoride-cooled High-temperature Reactor (gFHR), are at reducing the inventory of transuranic isotopes while still maintaining the intrinsic safety features of the PBR designs, such as negative temperature coefficients of reactivity. Optimized pebble designs utilizing TRU fuel were found for both reactors through the adjustment for the packing fraction of fuel in each pebble. The Axial Zone Equilibrium Modeling (A-ZEM) method was used in this work to help select the optimized pebble design. Once an optimized pebble design was selected and an equilibrium model was produced, the results from the deep burn (DB) HTR-10 and gFHR designs were compared to the results of two models from the literature. While both the DB gFHR and the DB HTR-10 were able to reduce the weapons-usable transuranic inventory, the performance of these reactors did not match that of the small-modular PB-HTGRs in the literature. Therefore, a need was identified for further refinement of the gFHR design using TRU fuel, as the results for this model were more promising than those of the DB HTR-10, which was strongly limited by the high leakage intrinsic to micro-modular PB-HTGRs.

Transuranic fuel↗
NASA NTRS1973

A vehicle scheduling algorithm using non-serial discrete dynamic programming with space shuttle applications

Description of the development and operation of a vehicle-scheduling algorithm which has applications to the NASA problem of assigning payloads to space delivery vehicles. The algorithm is based on a discrete, integer-valued, nonserial, dynamic-programming solution to the classical problem of developing resource utilization plans with limited resources. The algorithm places special emphasis on incorporating interpayload (precedence) relationships; maintaining optimal alternate schedule definitions (a unique feature of dynamic programming) in the event of contingencies (namely, resource inventory changes) without problem resolution; and, by using a special information storage technique, reducing the computational complexity of solving realistic problems.

Dupnick, E.↗
DOE OSTI2024

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗
DOE OSTI2021

Optimization of battery swapping infrastructure for e-commerce drone delivery

Drone delivery is widely-researched to alter the current e-commerce delivery convention for providing short delivery lead times. Yet, flight range of drones, constrained by the available battery technology, sets a milestone toward realizing the sole-drone delivery. To tackle with the flight range limitation, locating automated battery swapping machines (ABSM) have been proposed and a few studies modeled the problem. Using the ABSMs, drones can be loaded with fully-charged batteries along the route to a demand location. Here, we introduce a mixed-integer nonlinear program to model the problem. The objective of the program is to optimally select ABSM locations, determine the delivery-mode choices (drone-only, truck-only, and mixed delivery) of demand locations, find drone delivery routes, and approximate the baseline requirements for the number of drones and batteries needed. The program minimizes the overall delivery system costs including: ABSM, delivery, drone ownership, battery inventory, and service congestion. A cutting-plane method is developed to find exact solutions in finite iterations. Computational experiments showed that the method quickly yields the optimal solution to instances with less than 60 ABSM candidates and 20 demand locations. A case study shows that the optimal drone delivery infrastructure can save almost 20% cost compared to the conventional truck-only delivery. Sensitivity analyses were conducted to reveal the impact of key parameters in the decision-making and found that a decrease in the ABSM and drone costs highly affect the system cost.

25 ENERGY STORAGE↗
NASA NTRS1981

Crop-phenology and LANDSAT-based irrigated lands inventory in the high plains

Crop calendars for 1979 and 1980 were investigated in support of an effort to develop techniques for mapping the High Plains aquifer region. Optimal LANDSAT image dates for 1980 were preliminarily identified based on ESS weekly crop weather reports and 1979 ESS agricultural statistics were entered into the computer. A questionnaire was compiled and sent to ASCS county agents with the approval of the Extension Directors in each state involved. Data from returning questionnaires were tabulated and development started on a set of computer programs to allow the preparation of computer assisted graphic displays of much of the collected data.

Martinko, E. A.↗
DOE OSTI2026

Strategies for Enhancing Battery Life Under Fast Charging: Insights from NMC-Based Cell Cycling

Fast charging improves the usability of consumer electronics and electric vehicles (EVs) by reducing range anxiety and downtime but accelerates battery degradation and raises safety concerns. Optimizing operational conditions during fast-charging is critical to mitigating aging and ensuring safety. This study evaluated multilayer Gr/NMC811 cells under various conditions, including depths of discharge (DODs of 68%, 84%, and 100%), upper charge cutoff voltages (4.1–4.2 V), and post-charge rest periods (2–30 min), using a 20 min fast charging protocol for up to 500 cycles (up to 150,000 miles of EV use assuming 3.3 mi/kWh vehicle level energy efficiency). Surprisingly, higher DODs under fast charging improved battery life and performance compared to lower DODs. Reducing the upper charge cut-off voltage helped mitigate degradation. A brief 2 min rest period after charging further reduced aging effects. The primary aging modes were loss of lithium inventory and cathode active material. Although minor lithium plating was observed within 500 cycles, it did not affect performance significantly. These findings suggest that, with optimized conditions, cells can sustain hundreds of fast charge cycles—equivalent to over 100,000 miles of EV use—without significant adverse effects on performance or longevity.

25 - ENERGY STORAGE↗
DOE OSTI2023

Tuning the Legacy Survey of Space and Time (LSST) Observing Strategy for Solar System Science

Abstract The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multiband wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of over five million small bodies. The final survey strategy chosen for LSST has direct implications on the discoverability and characterization of solar system minor planets and passing interstellar objects. Creating an inventory of the solar system is one of the four main LSST science drivers. The LSST observing cadence is a complex optimization problem that must balance the priorities and needs of all the key LSST science areas. To design the best LSST survey strategy, a series of operation simulations using the Rubin Observatory scheduler have been generated to explore the various options for tuning observing parameters and prioritizations. We explore the impact of the various simulated LSST observing strategies on studying the solar system’s small body reservoirs. We examine what are the best observing scenarios and review what are the important considerations for maximizing LSST solar system science. In general, most of the LSST cadence simulations produce ±5% or less variations in our chosen key metrics, but a subset of the simulations significantly hinder science returns with much larger losses in the discovery and light-curve metrics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Modeling Radionuclide Inventories in MSR Off-Gas Systems with Radiochemical Transport Analysis

Molten salt reactors (MSR) contain unique characteristics that may require enhancements to modeling tools to accurately predict phenomena. One characteristic that may be advantageous to leverage during normal operation is on-line processing of the circulating fuel salt, such as an off-gas system (OGS) to remove volatile fission products. Therefore, new modeling tools must be developed to integrate spatial resolution and chemistry effects into fuel depletion tools to be able to account for these non-core sources of radioactivity. Such types of radiochemical transport analysis tools were used to estimate the removal rates for 12 elements within a flow model of the Molten Salt Reactor Experiment (MSRE) by optimizing against legacy experimental data of the gas-borne (GB) percentages of 12 nuclides. The removal rates were used in a depletion model to calculate the FP inventory that enters the MSRE OGS. Calculations are in good agreement with the empirical GB percentages reported for the 12 nuclides, which validates the approach and verifies each tool’s treatment of the radiochemical flow effects. The OGS inventory is discussed in terms of the largest nuclide contributors to activity, dose consequence, decay heat, and elemental composition. Finally, insights from the study allow recommendations to be made for future code development activities.

Shahbazi, Shayan↗
DOE OSTI2023

Advanced Tritium Process Analytics and Optimization via a Digital Twin, SRNL-TR-2023-00550

Improving the process knowledge and understanding of TCAP can be achieved by incorporating advanced tools. This project addresses “Advanced analytics for modeling, forecasting, & optimization of the tritium refinement process” and is being applied to the TCAP process. The value of digitization and advanced analytics for TCAP data are tracking of gas mixtures & inventories is presently a manual effort that is rather cumbersome. Incorporating some automation into the data capture will reduce errors and storing data in an accessible database that can be used for tracking as well as process improvements. In addition, the database approach will enable longer term history to be maintained rather than the current practice of deleting data after six months. The digitized and automated data will allow for models to be developed for the process and will enable the forecasting and optimization.

Korinko, Paul S.↗
DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Analysis of thermal and mechanical properties with inventory level of the molten salt storage tank in central receiver concentrating solar power plants

Molten salt thermal energy storage (TES) tanks ensure steady power output of concentrating solar power (CSP) plants; however, recent tank failures have highlighted the need for further analysis. Current studies primarily focus on analyzing the molten salt flow, heat transfer, and thermal efficiency. Additionally, research on the latest tank structures is limited and lacks newest experimental validation. This study measures temperature and molten salt inventory levels in the high-temperature tank at a 50 MW central receiver CSP plant, connected to the power grid in 2019. A multi-physics model was developed to evaluate thermal and mechanical properties of TES tanks by combining computational fluid dynamics and finite element modeling using real plant data. Heat loss, temperature, displacement, and stress distribution of the tank at different inventory levels were investigated. Results show that ambient air velocity near the tank roof reaches 2.14 m/s, much higher than 0.2 m/s near the wall. The temperatures of inventory fluid and tank are close, varying slightly at different levels due to thermal conduction and radiation. Because the heat loss strongly depends on temperature, the total tank loss remains nearly constant across inventory levels. Larger temperature gradients and thermal stresses are primarily localized along the tank floor edge and the air-salt interface. Notably, the maximum thermal stress at the tank edge is three times higher than that at the interface. The magnitude of total stress changes by less than 5 MPa with and without thermal load, indicating that high temperatures exert only a minor impact on tank stress. In contrast, thermal load significantly affects tank deformation, particularly at the roof edge, where values exceed 150 mm. Despite the large variation in molten salt levels, tank wall temperatures and displacements present a minor change, suggesting a weak correlation with inventory levels. In conclusion, the findings obtained in this study provide important insights on the TES tank that could be used to optimize tank design and operation strategies.

14 SOLAR ENERGY↗