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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Efficient Thermal Energy Storage with Radial Flow in Packed Beds

Thermal energy storage (TES) is a way to store excess heat in order to generate power later. These types of systems are valuable in the solar industry, where power production can still occur when sunlight is not available. This not only increases system flexibility, it drives down the cost of electricity. One option to store thermal energy is with a packed bed where the storage media resides in a cylindrical container. Flow from one end of the cylinder to the other deposits or recovers heat (axial flow). While a promising technology in terms of energy storage, it exhibits a high pressure drop that lowers overall system efficiency. This project seeks to flow the heat transfer fluid through the storage media in the radial direction. This system offers the potential to retain reasonable thermal performance while substantially lowering the pressure drop. The overall goal was to assess the performance of radial flow experimentally and numerically. Three main designs were considered in this work. The first system utilized a central pipe and four receiving pipes near the wall. The second system utilized a central pipe and an annulus with holes near the wall. The last approach considered segmenting the bed so only select zones would receive flow in the radial direction. In a high-aspect ratio system, the hole patterns in the piping are important for ensuring even flow into the bed, and a major design effort was testing holes patterns to promote even flow. The four pipe system was shown to be not feasible, as preferential flow paths occur that do not allow even and full heating of the packed bed. The annular system can lead to even flow, but the results show this is better accomplished through larger piping instead of considering variations in the hole pattern along the axial length of the pipe. Segmenting the bed can lead to similar exergetic performance when compared to axial or radial flow. However, the pressure drop in the segmented design is likely too high for practical implementation. A baseline commercial design showed exergetic efficiencies for axial, radial, and radial segments of 81.6%, 82.8%, and 80.2%, respectively. Pressure drop for the axial and radial results were 2.36 psi and 2.45 psi, respectively, with segments being nearly an order of magnitude higher. At these large scales, the aspect ratio of the system is important. From a baseline of 0.64, an aspect ratio of 0.32 for radial flow showed an exergetic efficiency of 86% but a pressure drop of 5.39 psi. All of these results provide new insights into packed bed thermal energy storage with radial flow. Competing effects must be considered when designing a radial system, and results show a radial design can show strong thermal results at the expense of system efficiencies from pressure drop. The COMSOL models used in this analysis are available to the public and other researchers. Public benefits include a potential increase in the efficiency of packed bed thermal energy storage. Higher efficiency in storage promotes green energy technologies while reducing costs.

14 SOLAR ENERGY↗
DOE OSTI2025

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗
DOE OSTI2023

Computationally Guided Design of Multiple Impurities Tolerant Cathode for Solid Oxide Fuel Cell Applications

Solid oxide fuel cells (SOFCs) have been recognized as promising candidates in the demand of reducing the dependence on fossil fuels, which is one of the solutions to the threat of global warming. It was reported that the direct chemical-to-electrical energy conversion in SOFCs comes with negligible emission of greenhouse gases and up to 60% working efficiency. SOFC has unique advantages over traditional power generation technologies and other types of fuel cells due to the use of relatively inexpensive materials, low sensitivity to poisoning impurities in fuels, relatively high conversion efficiency, and fuel flexibility (like carbon-based fuels). However, during the SOFC operation, the cathode is exposed to intrinsic and extrinsic airborne contaminants at high temperatures (600–900°C), leading to their reaction with electrode materials, irreversible chemical and structural changes, and electrochemical performance degradation. of which CO2, SO2, Cr6+ and H2O are known to be concerns. Thus, developing a comprehensive understanding of the multiple impurities poisoning of SOFC cathodes in the presence of single or multiple impurities is necessary to address the long-term degradation of the SOFC cathode systems at operating conditions. An integrated computational and experimental approach has been utilized in the current work aiming at the comprehensive investigation of the cathode materials under single or multiple impurities poisoning effects, understanding the multiple impurities poisoning mechanism(s), and improving the long-term durability of the SOFC cathodes to develop better performing impurity-tolerant cathode materials. We first examined the agreement between the simulation approach and the experimental observations at various atmospheric and temperature conditions to confirm the reliability of CALPHAD for poisoning simulations in these cathodes. Then, using this approach, we investigated the accelerated testing protocol, which has become the standard method for conducting impurity poisoning experiments involving these cathode materials. We found our simulation approach is able to predict in which systems, i.e., cathode material and treatment environment, the accelerated testing protocols reflect actual operating conditions. Finally, in-depth simulations were done for these three candidate cathodes under different experimental conditions and suggested directions toward alternative cathode materials that have superior impurity tolerance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Demand Response in Bangalore: Implications for Electricity System Operations

Recent Greening the Grid studies for India highlight the benefits of flexible resources for integrating variable renewable energy onto India’s electricity system. India’s ambitious renewable energy targets, which are particularly focused on renewable resource states such as Karnataka, will face fewer challenges when combined with new planning and operational strategies and technologies. This report explores one such strategy - demand response - by which the system operator shifts load throughout a day to minimize system wide production costs. To explore this strategy, we added demand response resources to Karnataka’s electricity system in a production cost model of India, using load shifting potential analyzed by Lawrence Berkeley National Labs. We then investigated the impacts of increasing demand response capacity under several renewable resource scenarios. Our results show the addition of demand response enables fuel shifting from high-marginal-cost and emissions-intensive subcritical coal and diesel generation to zero-marginal-cost and emissions-free renewable generation. Accordingly, the value that demand response provides to the system increases as the renewable penetration increases. In addition to reducing production costs and emissions, demand response reduces the time that thermal generators spend at their minimum output levels, which typically represents a less efficient and costlier operational state. Agricultural load shifting provides greater value to the system than residential, commercial, or industrial loads. Agricultural demand response is more flexible than other sectors because it is not exposed to subdaily operational constraints and it can operate for more hours per day without impacting customer satisfaction. Further, the first increment of demand response that is added to a system provides the greatest value; further additions provide additional benefits but have a decreasing impact. The insights we discuss could be leveraged by system planners and operators in other jurisdictions, particularly those facing significant renewable energy penetrations, to develop their own demand response programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Experimental Validation of a High-Temperature Test Facility for Future Additive Manufactured Supercritical Carbon Dioxide Turbine Testing

For next-generation power plants to achieve high cycle efficiencies consistent with the Department of Energy's 65% efficiency target, turbomachinery capable of operating within high-temperature power cycles must be demonstrated. Pairing additively manufactured superalloy turbines with the supercritical carbon dioxide (sCO 2 ) power cycle could enable turbine inlet temperatures approaching 1300 °C while providing flexibility in turbine cooling strategies. Development of test facilities to characterize and validate such systems is crucial. In this study, a turbine test facility capable of achieving inlet conditions of 800 °C, 11 MPa, and 0.43 kg/s while accommodating complex auxiliary cooling flow requirements has been designed and constructed to support future testing of a Haynes 282 additively manufactured 30 kW turbine-generator system with advanced cooling channels. This facility enables characterization of aerodynamic performance, leakage, and windage losses. Details of the facility's construction and operation are presented, along with experimental validation tests using an orifice as an expansion device in place of the turbine. These tests confirm that the facility can reach the required conditions, distinguish regions of achievable steady and pseudo-steady conditions, and identify the heater power required for each point in the upcoming turbine campaign. The campaign confirmed that ISO 5167-2 can reliably predict orifice mass flow rates in extreme supercritical carbon dioxide conditions with deviations of 0.5–7.5%.

42 ENGINEERING↗
DOE OSTI2021

Transient Efficiency Flexibility and Reliability Optimization of Coal-Fired Power Plants (Model-Based Estimation Library Report)

This document pertains to the reporting requirements of DOE contract FE-0031767. The document covers the development of a model-based estimation (MBE) library for generating digital twins of coal-fired power plants (CFPPs). The models used by the MBE are transient and physics-based. Model classes in the library that correspond to different components in CFPPs are presented with physical explanations and representative results. MBE library provides Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF) algorithms. The MBE library is generic and can be used to represent a variety of CFPPs. A digital twin of a CFPP will be created as the reduced-order model of that CFPP is embedded in the developed MBE architecture.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evolutionary flexibility and rigidity in the bacterial methylerythritol phosphate (MEP) pathway

Terpenoids are a diverse class of compounds with wide-ranging uses including as industrial solvents, pharmaceuticals, and fragrances. Efforts to produce terpenoids sustainably by engineering microbes for fermentation are ongoing, but industrial production still largely relies on nonrenewable sources. The methylerythritol phosphate (MEP) pathway generates terpenoid precursor molecules and includes the enzyme Dxs and two iron–sulfur cluster enzymes: IspG and IspH. IspG and IspH are rate limiting-enzymes of the MEP pathway but are challenging for metabolic engineering because they require iron–sulfur cluster biogenesis and an ongoing supply of reducing equivalents to function. Therefore, identifying novel alternatives to IspG and IspH has been an on-going effort to aid in metabolic engineering of terpenoid biosynthesis. We report here an analysis of the evolutionary diversity of terpenoid biosynthesis strategies as a resource for exploration of alternative terpenoid biosynthesis pathways. Using comparative genomics, we surveyed a database of 4,400 diverse bacterial species and found that some may have evolved alternatives to the first enzyme in the pathway, Dxs making it evolutionarily flexible. In contrast, we found that IspG and IspH are evolutionarily rigid because we could not identify any species that appear to have enzymatic routes that circumvent these enzymes. The ever-growing repository of sequenced bacterial genomes has great potential to provide metabolic engineers with alternative metabolic pathway solutions. With the current state of knowledge, we found that enzymes IspG and IspH are evolutionarily indispensable which informs both metabolic engineering efforts and our understanding of the evolution of terpenoid biosynthesis pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Power Generation Cycle with RELAP-7

Balance of plant of a High-Temperature gas-cooled Reactor – Pebble bed Module (HTR-PM) is modeled using RELAP-7. The model includes the primary helium loop where the heat produced by the core is transferred to a helical-coil steam generator and the secondary loop where super-heated steam is fed to a turbine to extract power. The steam is then condensed to subcooled water and pumped back into the steam generator. Results demonstrate that RELAP-7 has the capability to model different regimes encountered in two-phase flow with wall boiling, superheated steam, subcooled liquid and condensation. RELAP-7 also has the capability of modeling different fluids with their own specific models in a very flexible way, without any code change. This also demonstrates the capability of modeling the transfer of fission power into electrical power.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗
DOE OSTI2023

Orthogonal Gelations to Synthesize Core–Shell Hydrogels Loaded with Nanoemulsion‐Templated Drug Nanoparticles for Versatile Oral Drug Delivery

Hydrophobic active pharmaceutical ingredients (APIs) are ubiquitous in the drug development pipeline, but their poor bioavailability often prevents their translation into drug products. Industrial processes to formulate hydrophobic APIs are expensive, difficult to optimize, and not flexible enough to incorporate customizable drug release profiles into drug products. Here, a novel, dual-responsive gelation process that exploits orthogonal thermo-responsive and ion-responsive gelations is introduced. This one-step “dual gelation” synthesizes core–shell (methylcellulose-alginate) hydrogel particles and encapsulates drug-laden nanoemulsions in the hydrogel matrices. In situ crystallization templates drug nanocrystals inside the polymeric core, while a kinetically stable amorphous solid dispersion is templated in the shell. Drug release is explored as a function of particle geometry, and programmable release is demonstrated for various therapeutic applications including delayed pulsatile release and sequential release of a model fixed-dose combination drug product of ibuprofen and fenofibrate. Independent control over drug loading between the shell and the core is demonstrated. This formulation approach is shown to be a flexible process to develop drug products with biocompatible materials, facile synthesis, and precise drug release performance. This work suggests and applies a novel method to leverage orthogonal gel chemistries to generate functional core–shell hydrogel particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Pollution to products: recycling of ‘above ground’ carbon by gas fermentation

Climate crisis and rapid population growth are posing some of the most pressing challenges to mankind and have intensified the need for the deployment of carbon recycling and carbon capture and utilization (CCU) technologies. Gas fermentation offers a solution using carbon-fixing chemolithoautotrophic microorganisms. After a decade of scale up, the technology has recently been commercialized with the first plant operating successfully since 2018 and additional units under construction. Gas fermentation offers unique feedstock and product flexibility when compared to other available gas-to-liquid technologies. Advancements in process technology and synthetic biology enable a broad range of feedstocks including emissions from industry or syngas generated from any biomass resource to be converted into a wide range of molecules realizing a circular economy.

09 BIOMASS FUELS↗
DOE OSTI2025

Multistep catalytic abiotic CO2 conversion to sugars through C1 intermediates

Carbon dioxide (CO2) to multicarbon (Cn) upgrading for commodity chemicals, fuel production, or artificial food synthesis using renewable energy input is a golden target for researchers in sustainable carbon emission reduction. Here, we explore and analyze a flexible modular roadmap for the task, utilizing sequential electro-, photo-, and organocatalysis to develop a strategy for CO2 conversion using the key and elusive formaldehyde precursor of interest for sugar generation. We study the electrochemical carbon dioxide reduction reaction to methanol in a flow cell and its discontinuous photooxidation to formaldehyde (PMOR) with excellent selectivity. Utilizing a highly active N-heterocyclic carbene catalyst enables tunable generation of C4-C6 aldoses without undesirable byproducts, with carbon conversion yield reaching 60 to 80% for desired pentose, tetrose, and triose product mixtures and over 20% for hexose. This approach presents a roadmap for CO2 valorization, aiming to bridge carbon waste streams with sustainable sugar synthesis and opening broad avenues for green chemical production.

CO2 valorization↗
DOE OSTI2022

Small-Signal Stability Support from Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems

The growth of inverter-based resources (IBRs) in modern power systems can challenge system stability since they do not natively provide inertia, prompting a need to develop new methods to address the potential instabilities. In this paper, a dynamically configurable grid-forming (GFM) and grid-following (GFL) control is proposed, which enables inverters to flexibly transition to support system needs. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small-signal stability margin. In addition, a holistic and detailed small-signal model for a distribution feeder that captures the dynamics from both synchronous generators (SGs) and IBRs is also derived and used to evaluate the effectiveness of the proposed GFM/GFL controls to augment the system small-signal stability margin. Case studies with varying levels of IBRs were implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach.

grid-following control↗
DOE OSTI2023

Integrating Learning and Physics based Computation for Fast Online Transient Analysis

In this work, a novel method that integrates learning and physics based computation is developed for greatly accelerating the simulation of full power system transient trajectories. To solve the dynamic algebraic equations, the method replaces the time-consuming dynamic computation for generator dynamics with trained predictors, while retaining the time-efficient algebraic computation of solving AC-power flow (PF) for power systems. In particular, a predictor is trained for each generator, and the system trajectories are computed by alternating steps of calling the predictors and solving AC-PF. The proposed method also allows fully parallelizable training strategies and a flexible trade-off between training time and testing accuracy. Comprehensive evaluations of the proposed method for transient/dynamic contingency analysis of the New York/New England 16-machine 68-bus power systems demonstrate excellent performance and significant acceleration of computation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗