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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗
DOE OSTI2024

Design and analysis of actively-cooled, edge-transport diagnostic for long-pulsed operation in WEST

Next step fusion devices that will operate in steady-state will require complex plasma-facing components (PFCs) that can survive the harsh environment over long timescales not common in current devices. This will require robust plasma facing surfaces that are integrated with active cooling systems. In a collaboration between CEA and ORNL, a plasma-interacting diagnostic is being designed for the W Environment in Steady-state Tokamak (WEST) in Cadarache, France which requires plasma-facing protection like those needed for steady-state PFCs. This integrated diagnostic studies edge transport and impurity migration within WEST, and is planned to include imbedded temperature Langmuir probe sensors, as well as removeable sample slots for ex-situ surface analysis of plasma-material interactions. The entire assembly is expected to move into the plasma edge for periods up to 1000 s having an energy removeable capability of ∼6 kW and seeing a peak heat flux of more than 7 MW/m2. The assembly compliments WEST high fluence campaigns that plan for multiple 1000 s pulses. Within these specifications, the assembly will require a refractory metal plasma facing surface and integral cooling in order to function within the limited space allotted for such diagnostics. Because of the limited space and linear actuator needs, additive manufacturing of the high heat flux working end of the assembly is being considered which could allow for precision cooling-channels and lighter weight designs. Conceptual design along with simulation and analysis results will be presented for this complex diagnostic with novel PFCs.

Lumsdaine, Arnold↗
DOE OSTI2024

Weak shock compaction on granular salt

This study conducted integrated experiments and computational modeling to investigate the speeds of a developing shock within granular salt and analyzed the effect of various impact velocities up to 245 m/s. Experiments were conducted on table salt utilizing a novel setup with a considerable bore length for the sample, enabling visualization of a moving shock wave. Experimental analysis using particle image velocimetry enabled the characterization of shock velocity and particle velocity histories. Mesoscale simulations further enabled advanced analysis of the shock wave’s substructure. In simulations, the shock front’s precursor was shown to have a heterogeneous nature, which is usually modeled as uniform in continuum analyses. The presence of force chains results in a spread out of the shock precursor over a greater ramp distance. With increasing impact velocity, the shock front thickness reduces, and the precursor of the shock front becomes less heterogeneous. Furthermore, mesoscale modeling suggests the formation of force chains behind the shock front, even under the conditions of weak shock. This study presents novel mesoscale simulation results on salt corroborated with data from experiments, thereby characterizing the compaction front speeds in the weak shock regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Deer Park Energy Center Natural Gas Combined Cycle Carbon Capture System Front-End Engineering Design Study (Final Scientific/Technical Report – Unlimited)

Calpine Texas CCUS Holdings, LLC (Calpine), Shell Catalysts & Technologies (SCT), Technip Energies (TEN), and Sargent & Lundy, LLC (S&L) have conducted a Front-End Engineering Design (FEED) Study to integrate a new carbon capture system at Calpine’s Deer Park Energy Center (DKEC). The DKEC facility is a nominal 1200 MW gas-fired co-generation power plant situated at the Shell Chemical Manufacturing (Shell) Facility located in Deer Park, Texas. Steam is produced for use by the adjacent Shell Chemical Manufacturing Facility as well as by the onsite steam turbine for electrical generation. The power output from DKEC is provided to the Electric Reliability Council of Texas (ERCOT) operated power grid. DKEC provides power to industrial and commercial customers via this interconnection.

03 NATURAL GAS↗
DOE OSTI2026

Assessing Uncertainty in Solar Measurements: Key Findings From NLR's SUNI Application Across 89 Stations

The Solar Uncertainty Integrator (SUNI) study was developed by the National Laboratory of the Rockies (NLR's) to provide a standardized "bulk uncertainty processing" method for solar irradiance data, which are essential for the successful deployment of solar energy systems. This poster provides an overview of key findings from NLR's SUNI application across 89 stations.

14 SOLAR ENERGY↗
DOE OSTI2022

The eROSITA Final Equatorial-Depth Survey (eFEDS)

The eROSITA Final Equatorial Depth Survey (eFEDS), completed in survey mode during the calibration and performance verification phase of the eROSITA instrument on Spectrum Roentgen Gamma, delivers data at and beyond the final depth of the 4-yr eROSITA all-sky survey (eRASS:8), f 0.5–2 keV = 1.1 × 10 –14 erg s –1 cm –2 , over 140 deg 2 . It provides the first view of normal galaxy X-ray emission from X-ray binaries (XRBs) and the hot interstellar medium at the full depth of eRASS:8. We used the Heraklion Extragalactic Catalogue (HECATE) of galaxies to correlate with eFEDS X-ray sources and identify X-ray detected normal galaxies. This flux-limited X-ray survey is relatively free from selection effects and enables the study of integrated normal galaxy X-ray emission and its relation to galaxy parameters such as the stellar mass, star formation rate (SFR), and metallicity. We cross-correlated 32 646 eFEDS X-ray sources to 1181 HECATE normal galaxies and obtained 94 matches. We classified galaxies as star-forming, early-type, composite, and active galactic nuclei (AGN) using Sloan Digital Sky Survey (SDSS) and Six-degree Field (6dF) optical spectroscopy. The eFEDS field harbours 37 normal galaxies: 36 late-type (star-forming) galaxies and one early-type galaxy. There are 1.9 times as many normal galaxies as predicted by scaling relations via simulations, with an overabundance of late-type galaxies and a dearth of early-type galaxies. When compared with empirical relations, eFEDS dwarf galaxies with a high specific SFR have elevated L X /SFR at a fixed specific SFR and metallicity, indicating an increase in XRB emission due to low metallicity. We expect that eRASS:8 will detect 12 500 normal galaxies, the majority of which will be star-forming, with the caveat that there are unclassified sources in eFEDS and galaxy catalogue incompleteness issues that could increase the actual number of detected galaxies over these current estimates. eFEDS observations detected a rare population of galaxies – the metal-poor dwarf starbursts – that do not follow known scaling relations. eRASS is expected to discover significant numbers of these high-redshift analogues, which are important for studying the heating of the intergalactic medium at high redshift. Further investigation of the hot gas emission from normal galaxies and stochastic effects in the dwarf galaxy population are required to constrain their X-ray output.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Using "AI Poincare" to analyze non-linear integrable optics

This study dives into the applicability of using automated discovery of conserved quantities in dynamical systems relevant to accelerator physics. Specifically, we explore the performance of AI Poincaré in analyzing numerical trajectory data obtained using the McMillan system of non-linear integrable optics. A comprehensive evaluation of the algorithm's performance is conducted through diverse methodologies. These include the analysis of the estimated number of conserved quantities embedded in a dataset and the deviation of interpolated points on the inferred manifold with respect to points in actually in the dataset. the investigation identifies an optimal range of perturbation distances where the underlying manifold extraction algorithm inside AI Poincaré exhibits optimal performance. Additionally, an improved neural network architecture is proposed based on the observed results. Finally, we apply the algorithm to preliminary experimental data from the Integrable Optics Test Accelerator at Fermilab to successfully infer the number of conserved quantities even in the presence of fast decoherence of the measured signal.

Osmanov, Lazare [Free U. Tbilisi]↗
DOE OSTI2022

High-Entropy and Superstructure-Stabilized Layered Oxide Cathodes for Sodium-Ion Batteries

Layered transition metal oxides are appealing cathodes for sodium-ion batteries due to their overall advantages in energy density and cost. But their stabilities are usually compromised by the complicated phase transition and the oxygen redox, particularly when operating at high voltages, leading to poor structural stability and substantial capacity loss. Here, in this study, an integrated strategy combing the high-entropy design with the superlattice-stabilization to extend the cycle life and enhance the rate capability of layered cathodes is reported. It is shown that the as-prepared high-entropy Na 2/3 Li 1/6 Fe 1/6 Co 1/6 Ni 1/6 Mn 1/3 O 2 cathode enables a superlattice structure with Li/transition metal ordering and delivers excellent electrochemical performance that is not affected by the presence of phase transition and oxygen redox. It achieves a high reversible capacity (171.2 mAh g –1 at 0.1 C), a high energy density (531 Wh kg –1 ), extended cycling stability (89.3% capacity retention at 1 C for 90 cycles and 63.7% capacity retention at 5 C after 300 cycles), and excellent fast-charging capability (78 mAh g –1 at 10 C). This strategy would inspire more rational designs that can be leveraged to improve the reliability of layered cathodes for secondary-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Recent Advances in Machine Learning for Fiber Optic Sensor Applications

Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

f‐ block MOFs: A Pathway to Heterometallic Transuranics

Abstract A novel series of heterometallic f ‐block‐frameworks including the first examples of transuranic heterometallic 238 U/ 239 Pu‐metal–organic frameworks (MOFs) and a novel monometallic 239 Pu‐analog are reported. In combination with theoretical calculations, we probed the kinetics and thermodynamics of heterometallic actinide(An)‐MOF formation and reported the first value of a U‐to‐Th transmetallation rate. We concluded that formation of uranyl species could be a driving force for solid‐state metathesis. Density of states near the Fermi edge, enthalpy of formation, band gap, proton affinity, and thermal/chemical stability were probed as a function of metal ratios. Furthermore, we achieved 97 % of the theoretical maximum capacity for An‐integration. These studies shed light on fundamental aspects of actinide chemistry and also foreshadow avenues for the development of emerging classes of An‐containing materials, including radioisotope thermoelectric generators or metalloradiopharmaceuticals.

Park, Kyoung Chul↗
DOE OSTI2022

f‐ block MOFs: A Pathway to Heterometallic Transuranics

Abstract A novel series of heterometallic f ‐block‐frameworks including the first examples of transuranic heterometallic 238 U/ 239 Pu‐metal–organic frameworks (MOFs) and a novel monometallic 239 Pu‐analog are reported. In combination with theoretical calculations, we probed the kinetics and thermodynamics of heterometallic actinide(An)‐MOF formation and reported the first value of a U‐to‐Th transmetallation rate. We concluded that formation of uranyl species could be a driving force for solid‐state metathesis. Density of states near the Fermi edge, enthalpy of formation, band gap, proton affinity, and thermal/chemical stability were probed as a function of metal ratios. Furthermore, we achieved 97 % of the theoretical maximum capacity for An‐integration. These studies shed light on fundamental aspects of actinide chemistry and also foreshadow avenues for the development of emerging classes of An‐containing materials, including radioisotope thermoelectric generators or metalloradiopharmaceuticals.

Park, Kyoung Chul↗
DOE OSTI2023

SyReNN: A tool for analyzing deep neural networks

Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motivated recent work in formally analyzing the properties of such DNNs. Furthermore, this paper introduces SyReNN, a tool for understanding and analyzing a DNN by computing its symbolic representation. The key insight is to decompose the DNN into linear functions. Our tool is designed for analyses using low-dimensional subsets of the input space, a unique design point in the space of DNN analysis tools. We describe the tool and the underlying theory, then evaluate its use and performance on three case studies: computing Integrated Gradients, visualizing a DNN’s decision boundaries, and repairing buggy DNNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)

First-mile last-mile (FMLM) mobility services that connect riders to public transit can lead to improved transit accessibility and network efficiency if such services are convenient and reliable. However, many current FMLM services are inefficient and costly because they are inflexible (e.g., fixed supply of shuttles) and do not leverage collected data for optimized decision making. At the same time, new forms of shared mobility can provide added flexibility and real-time analytics to FMLM systems when carefully integrated. This study evaluates performance and cost implications of public/private coordination between transit shuttles and transportation network companies (TNC) in the FMLM context. A real-time operations model was developed to simulate daily operations for an existing FMLM system using real-world demand data. Three supply strategies were tested with varying levels of flexibility: (1) Status Quo (two 23-passenger on-demand shuttles), (2) Hybrid (one 23-passenger on-demand shuttle + TNC), and (3) TNC Only (exclusively use TNC services). Results indicated that the added flexibility of the Hybrid service design (using shuttles and TNCs) improved service performance (a 7.7% improvement), reduced daily operating costs (– 6.0%), and improved service reliability (95th percentile travel times decreased by up to 40% during peak periods). In addition, the Hybrid service design was more robust to variations in demand. Here, the Hybrid service was significantly cheaper to operate (– 31.6%) at reduced demand levels (50% of normal), and improved service performance (a 10.2% improvement) when demand levels were increased (150% of normal). These findings emphasize the importance of flexibility in FMLM service designs, especially when demand is sparse and variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Advances in in situ/operando techniques for catalysis research: enhancing insights and discoveries

Abstract Catalysis research has witnessed remarkable progress with the advent of in situ and operando techniques. These methods enable the study of catalysts under actual operating conditions, providing unprecedented insights into catalytic mechanisms and dynamic catalyst behavior. This review discusses key in situ techniques and their applications in catalysis research. Advances in in situ electron microscopy allow direct visualization of catalysts at the atomic scale under reaction conditions. In situ spectroscopy techniques like X-ray absorption spectroscopy and nuclear magnetic resonance spectroscopy can track chemical states and reveal transient intermediates. Synchrotron-based techniques offer enhanced capabilities for in situ studies. The integration of in situ methods with machine learning and computational modeling provides a powerful approach to accelerate catalyst optimization. However, challenges remain regarding radiation damage, instrumentation limitations, and data interpretation. Overall, continued development of multi-modal in situ techniques is pivotal for addressing emerging challenges and opportunities in catalysis research and technology.

Chen, Linfeng↗
DOE OSTI2020

Simulation of axial tensile well deformation during reservoir compaction in offshore unconsolidated methane hydrate-bearing formation

Sand production encountered in the 2013 offshore field gas production tests at the Nankai Trough, Japan, could be attributed to well failure during reservoir compaction. In this study, well integrity under various reservoir compaction patterns for the Nankai Trough case is examined using a well-formation finite element model. Here, the modelling details include the inclusion of a cement sheath as well as the modelling of construction processes (such as cement shrinkage). Well elongation in the overburden layer becomes significant when the reservoir subsidence is localized near the wellbore under large depressurization. Results show that the maximum plastic deviatoric strain level in the cement could reach 0.7% when the maximum reservoir subsidence reaches 0.85 m and cement shrinkage is limited. When cement shrinkage rises to 0.75%, the maximum plastic deviatoric strain increases to 2.4% as the cement accumulates additional plastic strain during shrinkage due to its deformation being constrained by the casing. In order to prevent the cement from failure, it might be effective to hold the pressure drawdown at a low level (e.g., several MPa) until the hydrate dissociation front advances to a certain radius from the well (e.g., a couple of tens of metres).

58 GEOSCIENCES↗
DOE OSTI2021

High-speed synchrotron X-ray phase-contrast imaging for evaluating microscale damage mechanisms and tracking cracking behaviors inside cross-ply GFRCs

In this study, we integrated the high-speed synchrotron X-ray phase-contrast imaging (PCI) with a modified Kolsky compression bar loading platform to visualize the dynamic failure processes of cross-ply glass fiber reinforced composites (GFRCs). Four S-2 glass/SC-15 composite specimens were prepared, having similar thicknesses but different stacking sequences, namely as [0 12 /90 12 ], [90 12 /0 12 ], [0 8 /90 8 /0 8 ], and [90 8 /0 8 /90 8 ]. Three-dimensional synchrotron X-ray computed tomography and scanning electron microscopy (SEM) were employed to examine the microstructures and quantify the fiber volume fractions. Each specimen was notched and subjected to a dynamic three-point flexural loading. The onset of cracking close to the notch tip, crack propagation in 0° or 90° plies and their interface, crack opening, and ultimately failure of the specimen were captured by high-speed synchrotron X-ray PCI. Additional dynamic experiments were performed to determine the average time when the stress wave propagated through the specimen and correlate the X-ray images with the specimen's force-deflection response. Finally, the surface morphology of each specimen after the dynamic loading was imaged by SEM. Comparison between real-time X-ray images and post-fracture SEM images demonstrated the capability of the X-ray method to record damage evolution inside composites. Furthermore, the high spatial and temporal resolutions of the X-ray setup and edge enhancement by PCI enabled the identification of microscale damage features within 1 μs. Two damaging processes were identified, crack growth was quantified, and fracture toughness of the composites was evaluated. The method is deemed useful to reveal microscale damage mechanisms and track cracking behaviors inside cross-ply GFRCs under dynamic loading in real time.

42 ENGINEERING↗
DOE OSTI2025

Supercritical water desalination and oxidation (SCWDO): Effectiveness on complex solutions, technoeconomic, and CO 2 impact for produced water treatment

The modern energy-economy is increasingly causing the production of highly saline brines, including from produced water. Supercritical water desalination can concentrate and extract minerals from these brines, but the effects of mixed salt interactions, organic degradation with additives, and the technology's economics are not well understood at supercritical condition. The present study evaluated and experimentally studied an integrated supercritical water desalination and oxidation (SCWDO) process for treating real-produced water samples from oil/natural gas field. The complex interactions between the various anions and cations in produced water were extensively evaluated. Most of the divalent and trivalent ions were extracted below 250 °C while the majority of the monovalent salt were removed between 380 to 410 °C. The treated real produced water was of drinking water quality, with <500 mg/l of total dissolved solid (TDS) and with 100% organics removal. Furthermore, the heat liberated during the organic oxidation could be utilized internally and for electricity generation for enhanced the energy efficiency and lower cost of produced water treatment. With system optimization, the proposed SCWDO process can essentially be made a net zero energy process. A novel process flow diagram for the commercial scale self-powered hybrid SCWDO technology was proposed as a cost-effective produced water treatment to mitigate the environmental crises. Techno-economic analysis showed that produced water treatment cost with SCWDO can be reduced to 2–3 $/m 3 and can be up to 60 % cheaper to traditional deep well reinjection. Additionally, the proposed SCWDO process could achieve net negative CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗