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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Alternating chempolishing and electropolishing for interior and exterior surface finishing of additively manufactured (AM) metal components

Additively manufactured (AM) components’ surface finishing is crucial in adopting them for intended applications in challenging environments involving fatigue, corrosion, high temperature, and nuclear radiation. In our prior research, chempolishing (C) was utilized as an electroless etching process that uniformly smoothens complex AM components’ accessible interior and exterior surfaces (Tyagi et al. Additive Manufacturing, 25:32–38, 22). A wide range of electropolishing (E) has been demonstrated for AM surface finishing. However, electropolishing can impact a surface that can be juxtaposed to counter electrode and can yield a very smooth surface to sub-micrometer level roughness. However, a knowledge gap exists about the impact of applying both approaches on the same surface one after another and what new advantages may arise because of combining two methods. This paper uses dual-stage liquid-based surface finishing strategies produced by alternating the chempolishing (C) and electropolishing (E) steps. Two dual-stage surface finishing approaches, i.e., chempolishing followed by electropolishing (CE) and electropolishing followed by chempolishing (EC), were performed on the 316 stainless AM steel component. Impacts of EC and CE approaches were compared with single-stage C and E surface finishing approaches. An optical microscope and mechanical profilometer were utilized to investigate the wide range of surface roughness parameters. CE and EC produced Ra ~ 1.4 µm and ~ 1.6 µm, respectively. Surface roughness on CE- and EC-treated AM samples was lower than those individually treated by C and E approaches. Scanning electron microscopy provided further insights into the microstructural difference between CE- and EC-treated AM samples. This paper reports a liquid contact angle study on CE- and EC-treated AM samples to provide insights into the relative difference in surface energy that is crucial for making coatings on AM parts. A spectroscopic reflectance study was also employed to register the difference in physical properties of AM components treated with CE and EC approaches. Further, this study reveals industrially practicable interior and exterior surface finishing approaches for complex AM metal components that require minimum tooling and real-time process monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2026

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Jumpstart Opportunities to Unleash Leadership in Energy Storage (JOULES)

Current-generation Li-ion batteries with cobalt- and nickel-containing cathodes and graphite anodes are approaching performance and cost limits. In this program, 24M Technologies, Inc. (24M) is teaming with the Massachusetts Institute of Technology (MIT) and University of Michigan (UM) to develop low cost and fast charging sodium metal batteries with good low-temperature performance and high energy density, building upon previous work performed under ARPA-E programs. Key achievements include optimization of solid electrolyte and anode current collector, optimized cathode active materials, development of high-performance electrolyte formulations, and integration of these components into full cells. The cell design incorporates (1) an ultra-thick cathode (>9 mAh/cm 2 ) comprising advanced cobalt-free, sodium cathode active material, (2) advanced fast-charging electrolyte (up to 12 mS/cm) developed using machine learning and automated high-throughput screening technology by UM, and (3) ceramic modified separator that enable smooth Na transport and deposition, developed at MIT, enabling a high-energy density anode-free configuration and maximizing the energy density of sodium batteries. The team has successfully combined these approaches to sodium chemistry and paved the way to meeting the fast-charging, high-energy density, and low-cost requirements of next-generation drone, electric vertical take-off and -landing, and electric vehicle batteries. Performance for anode-free sodium cells developed under this program is more powerful than the commercial Li-ion batteries. The final deliverable cell design has achieved over 300 Wh/kg and volumetric energy density above 800 Wh/L (Table 1). Additionally, the team has achieved over (1) a lifetime of 340 cycles, (2) 80% capacity retention at -20 °C (compared 25 °C), and (3) the ability to fast charge to 80% SOC in 20 minutes.

25 ENERGY STORAGE↗
DOE OSTI2026

Developing the hybrid scenario in DIII-D and KSTAR for W-compatible long-pulse operation

Long-pulse, high-performance operation with tungsten plasma-facing components is a crucial challenge for achieving steady-state (SS) goals in ITER and future fusion devices. This paper presents a joint international effort between the DIII-D and KSTAR tokamaks aimed at demonstrating the compatibility of the high q 95 ~ 6 hybrid scenario with a tungsten divertor and superconducting coils. A DIII-D hybrid scenario recipe is successfully tailored to KSTAR’s operational constraints, which facilitates cross-device studies. The results show successful 30 s long-pulse operation in KSTAR at a normalized beta (β N = 2.4) with a benign m/n = 4/3 mode and effective mitigation of tungsten accumulation. Despite this success, the KSTAR scenario exhibits a greater than 25% reduction in thermal confinement compared to the DIII-D reference. To investigate this discrepancy, we performed a predictive TGYRO validation study, which suggests that the difference is likely caused by a weaker temperature pedestal in the KSTAR discharge due to a higher and narrower density pedestal. In addition, such lower thermal confinement leads to higher impurity accumulation, possibly due to a change in neoclassical transport with increased inward pinch, which further degrades global confinement. We also report that stationary, long-pulse operation with sustained thermal confinement requires consistent fueling and wall conditioning. These findings highlight the importance of optimized fueling and real-time wall conditioning in achieving a high temperature pedestal and strong global confinement during stable long-pulse operation. We propose potential approaches toward fully SS, long-pulse operation, including real-time wall conditioning using an impurity dropper in KSTAR and future tokamaks.

DIII-D↗
DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗
DOE OSTI2020

A lightweight method for evaluating in situ workflow efficiency

Performance evaluation is crucial to understanding the behavior of scientific workflows. In this study, we target an emerging type of workflow, called in situ workflows. These workflows tightly couple components such as simulation and analysis to improve overall workflow performance. To understand the tradeoffs of various configurable parameters for coupling these heterogeneous tasks, namely simulation stride, and component placement, separately monitoring each component is insufficient to gain insights into the entire workflow behavior. Through an analysis of the state-of-the-art research, we propose a lightweight metric, derived from a defined in situ step, for assessing resource usage efficiency of an in situ workflow execution. By applying this metric to a synthetic workflow, which is parameterized to emulate behaviors of a molecular dynamics simulation, we explore two possible scenarios (Idle Simulation and Idle Analyzer) for the characterization of in situ workflow execution. In addition to preliminary results from a recently published study [11], we further exploit the proposed metric to evaluate a practical in situ workflow with a real molecular dynamics application, i.e., GROMACS. Here, experimental results show that the in transit placement (analytics on dedicated nodes) sustains a higher frequency for performing in situ analysis compared to the helper-core configuration (analytics co-allocated with simulation).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Plan 2 (PIP-II) centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line. It is a critical system that defines the ideal path for the beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40 C. Utilizing an actively regulated heating system, a metal-oxide-semiconductor field-effect transistor (MOSFET) based power control circuit which provides input to a controller; forming a closed-loop system that maintains the desired setpoints with high precision.

Mosher, Alexander [U. Illinois, Chicago]↗
DOE OSTI2025

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.

Mosher, Alexander [Fermilab]↗
DOE OSTI2023

The influence of subhaloes on host halo properties

Within the ΛCDM cosmology, dark matter haloes are composed of both a smooth component and a population of smaller gravitationally bound subhaloes. These components are often treated as a single halo when properties, such as density profiles, are extracted from simulations. Recent work has shown that density profiles change substantially when subhalo mass is excluded. In this paper, we expand on this result by analysing three specific host halo properties – concentration (cNFW), spin (λB), and shape (c/a) – when calculated only from the smooth component of the halo. This analysis is performed on both Milky Way-mass haloes and cluster-mass haloes in high-resolution zoom-in N-body simulations. We find that when subhaloes are excluded, the median value of (1) cNFW is enhanced by $\approx 30\pm 11$ and $\approx 77\pm 8.1~{{\ \rm per\ cent}}$ for Milky Way-mass ($10^{12.1}\, \text{M}_\odot$) and cluster-mass ($10^{14.8}\, \text{M}_\odot$) haloes, respectively, (2) λB is reduced for Milky Way-mass by $\approx 11\pm 4.9~{{\ \rm per\ cent}}$ and cluster-mass haloes by $\approx 27\pm 3.5~{{\ \rm per\ cent}}$. Additionally, with the removal of subhaloes, cluster-mass haloes tend to become more spherical as the ratio of minor-to-major axis, c/a, increases by $\approx 11\pm 3.6~{{\ \rm per\ cent}}$, whereas Milky Way-mass haloes remain approximately the same shape with c/a changed by $\approx 1.0\pm 5.8~{{\ \rm per\ cent}}$. Fractional changes of each of these properties depend primarily on the amount of mass in subhaloes and, to a lesser extent, mass accretion history. Our findings demonstrate that the properties of the smooth components of dark matter haloes are biased relative to the total halo mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Theoretical Understanding of Effects of Operating Modes on the Performance Durability of Solid Oxide Cells: A Comparison between Potentiostatic and Galvanostatic Operations

In solid oxide cells (SOCs), the choice between galvanostatic (constant current) and potentiostatic (constant voltage) modes does not significantly affect the performance of SOCs as long as the cell components remain unchanged and intact. However, the degradation of cell components, which leads to changes in electrochemical and physical properties of the cell, elevates the importance of the selected operating mode. This paper aims to investigate the effects of galvanostatic and potentiostatic operating modes on the evolving properties of SOCs and their subsequent influence on performance durability. Employing non-equilibrium thermodynamic analysis, a crucial approach for understanding the degradation phenomena within an active electrochemical system, this study aims to provide in-depth insights into how these operating modes affect the longevity and efficacy of SOCs. Key findings include: In cases where oxygen electrode (OE) degradation is accelerated by higher partial pressure of oxygen ( p O 2 ), operating under constant voltage electrolysis can mitigate the high p O 2 at the OE|electrolyte (OE|EL) interface. Conversely, if OE degradation occurs more rapidly under a lower p O 2 , constant current electrolysis is more effective in suppressing degradation by achieving a high p O 2 at the OE|EL interface. For degradation of the fuel electrode (FE) due to higher p O 2 , constant current electrolysis is beneficial for more stable performance, which helps maintain low p O 2 at the FE|EL interface. When FE degradation is accelerated by lower p O 2 , constant voltage electrolysis can avert low p O 2 at the FE|EL interface. In practical scenarios, more complex degradation mechanisms come into play, especially when p O 2 significantly deviates from initial conditions. Degradation in one electrode can influence p O 2 in the other electrode, a phenomenon more pronounced in potentiostatic than in galvanostatic electrolysis.

Electrochemistry↗
DOE OSTI2021

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. This paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗
DOE OSTI2022

Solid Phase Processing of Lead-Free Brass with Carbon Additives

Currently, “lead-free” brass alloys (like C27450/C27451/C6930), used extensively in drinking water fixtures and automotive, electrical, and electronic applications contain maximum 0.25% lead to maintain mechanical performance and machinability. Adding graphite to brass as an alternative to lead, using casting, powder metallurgy, and extrusion methods, has been explored previously. However, all these methods have proven to be energy-, time-, and resource-intensive, while not enabling performance equivalent to that of C36000 brass. In this project, we developed a one-step approach using friction extrusion and ShAPE to make lead-free brass/graphite components such as wires, rods and tubes with mechanical performance equivalent to commercial lead-free brass alloys. Manufacturing temperatures were maintained ~550-730 °C with feed rates ranging between 4 – 25 mm/min. Results show larger grains at the center of the rods and wires with smaller grains developing at the edges. Graphite particles were sheared in the direction of extrusion with higher strains observed towards the edges. Hardness of the brass/graphite samples was over 25% higher than that of the corresponding brass-only samples (rods and wires), also friction extruded. Our results show that the sub-micron graphite plays an important role in limiting process temperature and restraining grain growth during friction extrusion, thus reducing grain size in composites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Performance evaluation of an air conditioning system based on quasi isothermal dehumidifcation

This work presents a first study of novel air conditioning system based on quasi isothermal dehumidification combined with dew-point evaporative cooling through the Maisotsenko cycle (M-Cycle). The dehumidification process is realized in desiccant coated heat exchanger with heat rejection system. The key idea behind the solution is to maximize the cooling effectiveness by creating favourable conditions for dehumidification and evaporative cooling process. This is achieved by rejecting the heat of sorption in the desiccant system and providing cold and dry air for M-Cycle air cooler, which allows the system to be powered by using low-grade heat energy at 50 °C. The analysis is performed on the basis of experimentally validated numerical models of each component combined in a unified model of the system. The goal of the study is to determine the performance of the solution under different operational conditions. In addition two types of M-Cycle air coolers (i.e. cross-flow and regenerative unit) are compared to establish which unit is more suitable as the source of cooling energy for the system. It was established that proposed system is able to provide comfortable room parameters (supply air temperature equal 17 °C and humidity ratio equal 0.010 kg/kg-da) for outdoor air temperatures ranging from 28 to 36 °C and outdoor air humidity ranging from 0.010 to 0.018 kg/kg-da. This means that the proposed solution is able to provide comfortable conditions in temperate and humid climates. Results also indicate that the system consisting of the regenerative M-Cycle HMX allows better cooling load management, offers higher thermal Coefficient of Performance (COP th ) and uses less water compared to the system with the cross-flow HMX. However, the system with cross-flow heat and mass exchanger (HMX) has a relatively greater electrical Coefficient of Performance (COP el ) in most cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

O'Neill, Mary M. F. (ORCID:0000000221455165)↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Preliminary Component Design and Cost Estimation of a Novel Electric-Thermal Energy Storage System Using Solid Particles

Energy storage will become indispensable to complement the uncertainty of intermittent renewable resources and to firm the electricity supply as renewable power generation becomes the mainstream new-built energy source and fossil fuel power plants are phased out to meet carbon-neutral utility targets. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system is projected to have promising cost and performance characteristics to meet the future growing energy storage needs. This paper introduces the system and components required for particle TES to become technically and economically competitive. The system integrates electric particle heaters, particle TES within insulated concrete silos, and an efficient air-Brayton combined-cycle power system to provide power for storage durations up to several days via low-cost, high-performance storage cycles. Design specifications and cost estimation of major components in a commercial-scale system are presented in this paper. A techno-economic analysis based on preliminary component designs and performance indicates that particle TES integrated with an air-Brayton combined-cycle power system has a path to achieve the targeted levelized cost of storage of 5 ¢/kWh-cycle at a round-trip efficiency of 50% when taking low-cost energy-specific components and leveraging basic assets from existing thermal power plants. The cost model provides insights for further development and economic potentials for long-duration energy storage.

14 SOLAR ENERGY↗
DOE OSTI2020

Understanding water management in platinum group metal-free electrodes using neutron imaging

Platinum group metal-free (PGM-free) catalysts are a low-cost alternative to expensive PGM catalysts for polymer electrolyte fuel cells. However, due to the low volumetric activity of PGM-free catalysts, the catalyst layer thickness of the PGM-free catalyst electrode is an order of magnitude higher than PGM based electrodes. The thick PGM-free electrodes suffer from increased transport resistance and poor water management, which ultimately limits the fuel cell performance. This manuscript presents the study of water management in the PGM-free electrodes to understand the transport limitations and improve fuel cell performance. Here, in-operando neutron imaging is performed to estimate the water content in different components across the fuel cell thickness. Water saturation in thick PGM electrodes, with similar catalyst layer thickness to PGM-free electrodes, is lower than in the PGM-free electrodes irrespective of the operating conditions, due to high water retention by PGM-free catalysts. Improvements in fuel cell performance are accomplished by enhancing water removal from the flooded PGM-free electrode in three ways: (i) enhanced water removal with a novel microporous layer with hydrophilic pathways incorporated through hydrophilic additives, (ii) water removal through anode via novel GDL in the anode, and (iii) lower water saturation in PGM-free electrode structures with increased catalyst porosity.

25 ENERGY STORAGE↗
DOE OSTI2023

Prediction and uncertainty quantification of shale well performance using multifidelity Monte Carlo

Uncertainty quantification is an integral component of reservoir management, especially considering the inherent uncertainty in subsurface systems. While a standard practice to estimate the uncertainty, Monte Carlo (MC) simulation is computationally intense when the sampling population comprises high-fidelity simulations. Alternatively, the Multi-fidelity Monte Carlo (MFMC) simulation overcomes this computational intensity by integrating low- and high-fidelity simulations. Our goal is to minimize the number of expensive high-fidelity simulations while maintaining accuracy and using numerous fast and cheap low-fidelity simulations to efficiently sample to input parameter space of interest. We selected gas production from unconventional wells to demonstrate the potential speedups and accuracy of the MFMC approach. The model fidelity usually determines the trade-off between accuracy and efficiency. While the high-fidelity model is more accurate, the low-fidelity model is more efficient. Our high-fidelity simulation includes reservoir simulations of a hydraulically fractured well. On the other hand, our low-fidelity model comprises the parallel-plate flow model. We used differential programming to efficiently solve the 1D flow model, where automatic differentiation is used to efficiently compute the gradients. We matched the production profile of high-fidelity simulations with our low-fidelity simulations. Then, we used a support vector regression to map the high- and low-fidelity input parameters. The mapping function is essential to tune the low-dimensional parameter space of the low-fidelity model to the high-dimensional parameter space of the high-fidelity model. We found that we can use a combination of 9 high fidelity and 10,000 low fidelity simulations to efficiently and accurately simulate pressure management. This method is at least two orders of magnitude faster than only using high-fidelity simulations. Finally, from a broader perspective, MFMC could efficiently estimate the uncertainty of various systems and models, integrating low- and high-fidelity models.

04 OIL SHALES AND TAR SANDS↗