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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Experimental study and demonstration of pilot-scale, dry feed, oxy-coal combustion under pressure

In this paper, we discuss how pressurized oxy-combustion is a promising technology for low-carbon, fossil fuel utilization. It has the potential of improved efficiency and economics compared with conventional atmospheric pressure oxy-combustion. Washington University in St. Louis has proposed a new pressurized oxy-combustion process, namely Staged Pressurized Oxy-Combustion, which has the potential to improve further the plant efficiency, operational flexibility, and economics. This process burns pulverized coal in a pressurized, oxy-combustion environment, which has not been demonstrated in a pilot-scale system before. To address this gap, a 100 kWth pressurized oxy-combustion facility was designed and constructed. This facility has a unique burner and furnace design featuring a co-axial, low-mixing flow field, which is drastically different from conventional coal-fired boiler designs where strong mixing is sought by introducing swirl or recirculating flows. This work aims to present the first pilot-scale experimental results of a dry-feed, pressurized oxy-combustion system. The tests focused on exploring flame stability and shape, char burnout, and fine particulate matter formation. Testing results suggest that the burner has excellent flame stability. The flame shape is consistent with the design philosophy and agrees with large eddy simulations. Importantly, complete char combustion can be achieved with an oxygen mole fraction in the flue gas of only 0.8%, as opposed to a required value of ~3% for conventional atmospheric pressure air-fired or oxyfuel combustion, which reduces the costs of both oxygen generation upstream and oxygen removal downstream. The testing results show promise for dry-feed, pressurized oxy-combustion, and the new burner and furnace design.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

A novel machine learning based identification of potential adopter of rooftop solar photovoltaics

With the proliferation of rooftop solar photovoltaic installations, there is a need to proactively predict consumer potential for solar photovoltaic adoption, for improved electric utility planning and operation. Traditional analytical modeling approaches are limited to a few survey features and a larger part of the survey would remain untouched by the decision model. This article presents a novel, data-driven modeling approach that strategically prunes a large set of consumer profile features using a machine learning framework to train a model for predicting potential solar adoption. The approach utilizes the Gradient Boosting Decision Tree model through a Light Gradient Boosting framework that improves significantly over the poor prediction accuracy of the existing approaches. Model training using focal-loss based supervision is used to overcome the difficulty in identifying the potential adopters that is inherent in conventional data-driven models. In addition, to overcome possible data sparsity in a limited survey sample, a Generative Adversarial Network is presented to create synthetic user samples and its effectiveness on model performance is assessed. A Bayesian optimization approach is used to systematically arrive at the hyperparameters of the proposed model. Validation of the presented approach on a survey data collected by the National Rural Electric Cooperative Association in Virginia in 2018 demonstrates the excellent predictive capability of the machine learning based approach to modeling solar adoption reliably.

14 SOLAR ENERGY↗
DOE OSTI2021

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. In this work, ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Design of a 2 MW ZrC/W-based molten-salt-to-sCO 2 PCHE for concentrated solar power

To increase the power cycle efficiency and lower the levelized cost of electricity (LCOE) of concentrated solar power (CSP) plants, printed circuit heat exchangers (PCHEs) capable of operating above 700 °C with molten chloride salt and a sCO 2 -based fluid are needed. In this paper, the design of a high-pressure, high-temperature, 2 MW PCHE comprised of a thermomechanically-robust, zirconium carbide/tungsten (ZrC/W) composite is conducted for CSP plants. The ZrC/W composite is a material with high thermal conductivity, high stiffness, and high failure strength at high temperatures, along with excellent resistance to thermal cycling and thermal shock. In this work, a thermomechanical design analysis was conducted to select appropriate material thicknesses of the ZrC/W plates, and to determine the geometrical dimensions and the thermal performance of the PCHE. The influences of the plate number and heat exchanger length on power density and pressure drop have also been systematically investigated. Economic analyses were conducted to compare the cost of ZrC/W-based PCHEs to those comprised of IN740H (a state-of-the-art, nickel-based superalloy) and 316 stainless steel (316SS). Finally, at a sufficiently high plate production rate, the manufacturing cost of ZrC/W-based PCHEs can be significantly lower, while achieving a much higher power density, compared with state-of-the-art, nickel alloy-based and stainless steel-based PCHEs.

14 SOLAR ENERGY↗
DOE OSTI2024

A high-performance intermediate temperature reversible solid oxide cell with a new barrier layer free oxygen electrode

The best solution to address the critical durability issue of solid oxide electrolytic cells (SOECs) for high-efficiency and high-rate H 2 production is to lower the operating temperature without sacrificing the performance. Developing high performance oxygen electrodes (OEs) is a key to capitalizing this solution. Here, in this paper, we report on a highly active OE for intermediate temperature ZrO 2 -based SOECs without a CeO 2 barrier layer. The new barrier-layer-free (BLF) OE is a composite of two materials, (Bi 0.75 Y 0.25 ) 0.93 Ce 0.07 O 1.5±δ (BYC) that exhibits high oxide-ion conductivity and La 0.8 Sr 0.2 MnO 3 (LSM) that possesses a high electronic conductivity to enable fast oxygen reduction/evolution reactions (ORR/OER). Featuring a microscale porous BYC scaffold decorated with high surface area LSM nanoparticles (NPs), the new BLF-OE exhibited a low area specific resistance (ASR) of 0.10 Ω cm 2 at 650 °C in air. With 50%H 2 -50%H 2 O as a feed to hydrogen electrode (HE) and air to OE, the single cell performance achieved 588 mA cm -2 at 0.80 V in the fuel cell mode and 688 mA cm -2 at 1.30 V in the electrolytic mode at 650 °C. Our in-house testing showed that this level of performance was ~3.5x higher than the cell with the benchmark La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ -Ce 0.9 Gd 0.1 O 2-δ OE. The long-term durability testing under alternating fuel cell and electrolytic modes showed a low degradation rate of 0.10 mA cm -2 h -1 over 550 hours. These encouraging results showed the great promise of the newly developed BYC-LSM to be an excellent OE candidate for intermediate temperature SOECs.

25 ENERGY STORAGE↗
DOE OSTI2025

Explainable multi-fidelity Bayesian neural network for distribution system state estimation

Distribution System State Estimation (DSSE) is frequently constrained by limited real-time measurements, the uncertainties introduced by distributed energy resources, and the presence of bad data. To address them, this paper proposes an enhanced Multi-Fidelity Bayesian Neural Network (MFBNN) DSSE approach. A low-fidelity layer based on a Deep Neural Network (DNN) is first pre-trained on pseudo-measurement data to learn fundamental state features. Subsequently, a high-fidelity Bayesian Neural Network (BNN) layer leverages limited but high-quality real-time measurements to refine these features, thereby achieving accurate DSSE. Additionally, the deep SHapley Additive exPlanation (SHAP) is developed to quantify the influence of measurement data on DSSE through dual perspectives of global feature importance and local nodal contributions, establishing a hierarchical explainability framework for machine learning-based DSSE. Comparative studies conducted on the IEEE 13-bus system and a real-world 2135-node system from Dominion Energy demonstrate that the proposed method excels in estimation accuracy, even under situations of high noise levels, bad data, and missing data. Further comparisons with Weighted Least Squares (WLS) and other machine learning-based DSSE approaches verify that the proposed framework offers higher accuracy, improved interpretability, and enhanced robustness.

Bad data↗
DOE OSTI2025

A high-order computational framework for particle-resolved simulations of disperse multiphase flows

This work presents a high-order numerical approach for particle-resolved simulations of disperse multiphase flows, where the Navier-Stokes equations for fluid flow are solved using a high-order spectral element method in the Eulerian framework, and the particle phase is directly simulated with a discrete element method. The coupling between particles and fluids is explicitly handled using an adapted direct-forcing immersed boundary method. Unlike the conventional schemes, a high-order barycentric Lagrange interpolation method and a Gaussian projection kernel are used to ensure accurate momentum exchange between local boundary points and surrounding fluid nodes in the framework of high-order fluid solver. Benchmark tests of increasing complexity are conducted to demonstrate the accuracy and efficiency of our method. Here, it is found that our approach exhibits an excellent convergence performance, as the fluid element/grid is refined and the number of boundary points increases. Compared to conventional low-order methods, the proposed high-order framework enables the use of substantially larger fluid elements while maintaining high accuracy in modeling fluid-particle interactions, owing to the enhanced resolution of high-order basis functions. Moreover, since the primary unknowns are stored at element or grid nodes, the high-order approach offers improved efficiency in both CPU memory usage and total computational cost.

42 ENGINEERING↗
DOE OSTI2020

Generalized synthesis of high surface area mesoporous metal titanates as efficient heterogeneous catalysts

A novel metal dissolution coupled with reverse micelle formation approach is used as a generalized synthesis method for a series of high surface area metal titanates where the metals used are Bi, Mg, V, Mn, Fe, Co, Ni, Cu, Zn, Mo, W, and Ce. This study reports the highest surface areas published so far. The homogeneous distributions of the metals and titanium are observed in SEM-EDX and TEM mapping. The synthesized materials were comprehensively characterized using PXRD, Raman, nitrogen adsorption isotherms, SEM; EDX, TEM, TEM mapping, TGA, and XPS. The green catalytic oxidation of aniline to nitrosobenzene occurs within 30 min at room temperature when mesoporous W/Ti binary metal oxide is used as the catalyst. The radical mediated catalytic reaction gives excellent yields and the catalyst is reusable up to 4 reaction cycles without losing significant activity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Flame-retardant cellulose-aerogel composite from agriculture waste for building insulation

Bio-based thermal insulation materials are in high demand due to their availability, reproducibility, and carbon-sequestration nature. However, high flammability, moisture condensation, and high thermal conductivity of biogenic material are major concerns for sustainable building applications. In this study, we report the fire-retardant cellulose aerogel insulation nanocomposites derived from wheat straw and silica aerogel, in which sodium bicarbonate improves its fire retardancy. We combined blended straw fibers and hammermilled straw fibers to create a structural hierarchy composite. The blended straw, with its longer and thicker size, served as reinforcement, while the hammermilled straw fibers acted as filler. This hierarchical structure was further integrated with aerogel for applications in green buildings. The as-prepared materials show a low thermal conductivity of 24.1 mW/m.K, high flexural modulus of 736 MPa, hydrophobicity with a water contact angle of 110.42°, and excellent fire retardancy. Altogether, this work provides an effective method for the synthesis of fire-retardant biogenic thermal insulation materials and shows a promising way for next-generation bio-based insulation materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theoretical modeling of a bottom-raised oscillating surge wave energy converter structural loadings and power performances

Here, this study presents theoretical formulations to evaluate the fundamental parameters and performance characteristics of a bottom-raised oscillating surge wave energy converter (OSWEC) device. Employing a flat plate assumption and potential flow formulation in elliptical coordinates, closed-form equations for the added mass, radiation damping, and excitation forces/torques in the relevant pitch-pitch and surge-pitch directions of motion are developed and used to calculate the system's response amplitude operator and the forces and moments acting on the foundation. The model is benchmarked against numerical simulations using WAMIT and WEC-Sim, showcasing excellent agreement. The sensitivity of plate thickness on the analytical hydrodynamic solutions is investigated over several thickness-to-width ratios ranging from 1:80 to 1:10. The results show that as the thickness of the benchmark OSWEC increases, the deviation of the analytical hydrodynamic coefficients from the numerical solutions grows from 3% to 25%. Differences in the excitation forces and torques, however, are contained within 12%. While the flat plate assumption is a limitation of the proposed analytical model, the error is within a reasonable margin for use in the design space exploration phase before a higher-fidelity (and thus more computationally expensive) model is employed. A parametric study demonstrates the ability of the analytical model to quickly sweep over a domain of OSWEC dimensions, illustrating the analytical model's utility in the early phases of design.

13 HYDRO ENERGY↗
DOE OSTI2024

Piston geometry and stroke optimization for high efficiency propane spark ignition engines

Propane has unique properties and offers interesting characteristics for high-efficiency spark ignition engines. Its high volatility reduces or completely eliminates fuel-wall wetting and facilitates fuel air mixing. Furthermore, propane has a research octane number of 112 and a high octane sensitivity of 15. Finally, its laminar flame speed is on the same order as that of conventional gasoline, and it exhibits high dilution tolerance. Modern spark ignition internal combustion engines rely on fast combustion rates and high dilution to achieve high brake thermal efficiencies. To accomplish this, high stroke-to-bore ratios and high geometric compression ratios have been used in new engine designs. Therefore, propane’s relatively high laminar flame speeds, high knock resistance, and dilution tolerance make it an excellent candidate fuel for modern spark ignition engines. The objective of this work is to co-optimize the piston geometry and the engine stroke to maximize the efficiency of a spark-ignition engine fueled with propane. 3D computational fluid dynamics (CFD) simulations employing the extended coherent flamelet model were used to study the parametric effects of piston shape and stroke length. A piston geometry based on high performing pistons was parameterized using four controlling parameters. The piston geometry and engine stroke design space was explored using deterministic and quasi-random sampling techniques. In conclusion, a Gaussian process regression model was built using the simulation data to explain the results observed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Characterization of 244 Cm Neutron Sources

There is a need to find a replacement for the 252 Cf sources currently used in Standards-based performance testing of neutron instrumentation. This is a result of its relatively short half-life, concerns about future availability and recent increases in cost. A potential replacement source, 244 Cm is evaluated in this study where two commercially available sources have been acquired and their neutron emission spectra measured using a pair of spectrometers. Both instruments showed the 244 Cm spontaneous neutron spectrum to be fully consistent with a MCNP6®-calculated spectrum using published Watt fission parameters for 244 Cm. In addition, the emission rate of the weaker 244 Cm source was established through a direct count rate comparison against a calibrated and similarly encapsulated 252 Cf source. The 244 Cm source emission rate was found to be in excellent agreement with value stated on the manufacturer's source certificate. It is concluded that 244 Cm would be an ideal replacement for 252 Cf based on its longer half-life (18.1 y) and its essentially identical neutron emission spectrum. In addition, 244 Cm sources are commercially available at reasonable cost.

244Cm↗
DOE OSTI2025

127 Xe quantification method development and intercomparison exercise

Monitoring of the atmosphere for fission products ( 131m Xe, 133m Xe, 133 Xe, and 135 Xe) is performed by various laboratories to detect nuclear explosions. Quantification of 127 Xe is not routinely performed by laboratories measuring atmospheric radioxenon because it is not a fission product. 127 Xe was recently detected by a ground-based beta-gamma air monitoring system. When measured using beta-gamma coincidence detector systems, such as those in use on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), 127 Xe can interfere with the quantification of fission product radioxenon due to overlap of the 127 Xe beta-gamma coincidence signatures with those of fission product radioxenon. Here, this work demonstrates quantification of 127 Xe at different laboratories with different measurement techniques. Production and purification of 127 Xe was performed by neutron activation of enriched 126 Xe. The purified 127 Xe was then split between laboratories, and detection and quantification methods were developed. At Idaho National Laboratory, a quantification method involving high purity germanium detectors was devised that included self-attenuation correction. At AWE, a beta-gamma coincidence counting method, as used in support of the IMS, was modified to enable the measurement and analysis of the 127 Xe samples. Corrections were made for self-attenuation, which showed a strong xenon volume dependency, for some coincidence signatures. The gas sample activity concentration was used as the comparison metric and it showed excellent agreement between the methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

High surface area magnetic double perovskite La 2 AlFeO 6 as an efficient and stable photo-Fenton catalyst under a wide pH range

Photo-Fenton process is an efficient way to treat the organic pollutants in wastewater. However, the efficiency is limited by serious leaching of iron ion, separation of spent catalyst from reaction system for facile recycling, low (pH<4) reaction environment. Herein, we report a preparation of a novel magnetic double perovskite photocatalyst La2AlFeO6, and refractory organic pollutants like phenol, etc. were used as probes to test the efficiency of catalyst. The results showed that the catalytic material retained high surface area and high ratio of Fe 3+ on its surface, and the generated ·OH, ·O 2 - and 1 O 2 lead to a highly photocatalytic efficiency even at neutral pH condition. In addition, the as prepared double perovskite photocatalyst La 2 AlFeO 6 also exhibits excellent stable and magnetic properties. There is no iron ion leaching detected during the courses of the reaction. Furthermore, the spent catalyst can be separated by magnetic field easily, and thus can be reused after simple air drying without any further treatment or calcination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Helium tribology of Inconel 617 subjected to laser peening for high temperature nuclear reactor applications

Inconel 617 is among the best candidates for utilization in high temperature gas cooled reactor tribo-components. However, the combined effects of sliding contact, along with intermittent idle times and very high temperature material degradation, deteriorates the alloy tribological performance, especially under a helium atmosphere. Laser peening is a surface treatment technique which can enhance the properties at the surface and subsurface by generating deep residual stresses and enhanced microstructure. In this work, we report the tribological behavior of regular laser peened as well as thermally-engineered laser peened Inconel 617 under helium and air atmospheres at 800 °C. In addition to friction and wear studies, the specimens are characterized by different analytical techniques to further understand the mechanisms involved in the peening process and sliding contact. Regardless of the peening process and post-process treatment types, it is observed that laser peening improves the tribological characteristics of Inconel 617. Interestingly, laser peening followed by helium thermal aging shows highly enhanced tribological behavior. This is attributed to the strengthening effect of the laser peening on the surface oxides providing an excellent and lasting protective and lubricating film under helium exposure.

42 ENGINEERING↗
DOE OSTI2022

Super-porous Pt/CuO/Pt hybrid platform for ultra-sensitive and selective H 2 O 2 detection

A super-porous Pt/CuO/Pt hybrid electrode is demonstrated with extremely high sensing performance parameters for the hydrogen peroxide (H 2 O 2 ) detection. A unique physiochemical approach is adapted for the fabrication of 3-D super-porous Pt/CuO/Pt sensing platform. Here, the super-porous Pt/CuO/Pt hybrid platform demonstrates a superior sensitivity of 16,694 µA mM -1 cm -2 with a limit of detection of 2.91 nM (S/N = 3). It also demonstrates an excellent selectivity against the interfering molecules such as NaCl, fructose, ascorbic acid, citric acid, dopamine and glucose with a wide linear range. The demonstrated performance ranks the Pt/CuO/Pt hybrid platform as one of the best H 2 O 2 sensors as summarized in the Table 2. The super-porous CuO layer is fabricated by a dynamic hydrogen bubbling technique of electrochemical deposition and metallic Pt NP decoration is achieved by the physical vapor deposition (PVD) and post-annealing. The super-porous CuO layer offers a drastically improved electrochemical active surface area, and the Pt NP decoration offers a significantly improved conductivity and improved charge accumulation for the H 2 O 2 reduction. The DFT simulations confirm the predominance of CuO over Cu 2 O and Pt over Pd for the H 2 O 2 detection based on the adsorption energy, density of states and charge accumulation calculations.

36 MATERIALS SCIENCE↗