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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measurement of Deformation Heterogeneity During Shale Swelling Using Digital Image Correlation

Abstract Rock-fluid interactions in shale formations are one of the main sources of wellbore instability issues and inadequate stimulation performance. For better planning of fracturing operations and optimizing production from these reservoirs, it is important to understand the mechanisms behind these interactions. These issues are especially prevalent in clay-rich shales, such as Tuscaloosa Marine Shale, which is the subject of this study. Conventional techniques to quantify these shale-fluid interactions comprise of measuring swelling in powdered rock grains or measurement of deformation in the whole pieces of the core using a linear variable differential transformer and strain gages. However, the contribution from individual laminae to overall deformation cannot be evaluated using these methods. In this study, we developed an experimental setup to evaluate the spatial deformation in shale during interaction with water using digital image correlation (DIC). Deformation of two shale samples, with 34 wt% to 51 wt% clay content, was studied. White paint was used to generate a random speckle pattern on the specimen and then immersed in deionized water. The deformation process was captured using a digital camera and images were analyzed using DIC to quantify the deformation. The implementation of the DIC technique enables the visualization and quantification of spatial deformation in the specimen during interacting with water. The results show the localization of large strains in select laminations. The results provide a better understanding of shale deformation when interacting with water in comparison to traditional measurements that can provide only an average strain value.

Energy & Fuels↗
DOE OSTI2021

Power Generation and Oxygen Transfer Analyses for Micro Hydro-Turbine Installed in Wastewater Treatment Aeration Tank

This study targets one of the major energy consumers in the U.S. It suggests a new mechanical system that can recover a portion of the energy in Wastewater Treatment Plants (WWTPs). The proposed system entails a hydro-turbine installed above the air diffuser in the aeration tank to extract the water-bubble current’s kinetic energy and converts it to electricity. Observing the optimum location of the turbine required multiple experiments where turbine height varies between 35% and 95% (water height percentages above the diffuser), while varying the airflow between 1.42 L/s (3 CFM) and 2.12 L/s (4.5 CFM) with a 0.24 L/s (0.5 CFM) increment. Additionally, three water heights of 38.1 cm (15*), 53.4 cm (21*), and 68.6 cm (27*) were considered to study the influence of the water height. It was noticed that the presence of the system has an adverse effect on the standard oxygen transfer efficiency (SOTE). Therefore, a small dual-blade propeller was installed right above the diffuser to directly mix the water in the bottom of the tank with the incoming air to enhance the SOTE. The results showed that the maximum reclaimed power was obtained where the hydro-turbine is installed at 65–80% above the diffuser. A reduction of up to 7.32% in SOTE was observed when the setup was placed inside the tank compared to the tank alone. The addition of the dual-blade propeller showed an increase in SOTE of 7.27% with a power loss of 6.21%, ensuring the aeration process was at its standards.

Energy & Fuels↗
DOE OSTI2021

Optimizing Power Reclamation of Micro Hydro Turbines in WWTPs Aeration Basins

Abstract This study investigates the optimum operating conditions and design configurations that can optimize the power reclaimed by small hydro turbines derived by the rising water-bubble current. The rising current is generated by the compressed air introduced by the diffusers at the bottom of aeration basins of Wastewater Treatment Plants (WWTPs). While optimizing the power production, the standard oxygen transfer efficiency (SOTE) is monitored since it is a significant parameter that cannot be sacrificed in the operation of WWTPs. Using one set of turbine blades, it was found out that the highest velocity is obtained in the upper half of the water column (70% - 80%). In contrast, the lowest velocities were obtained just above the air diffuser and at the water surface. Testing started with using a single turbine (ST) to determine the location of the optimum power reclaimed at each tested airflow (1.18, 1.42, 1.65, and 1.89 L/s). Then using double turbine (DT) and triple turbine (TT) to compare their performance to the ST’s maximum power increased power reclamation. The maximum percentage of increase in power reclamation for DT is 19.59%, while it is 20.24% in the case of TT. At a commonly used airflow in WWTPs (1.42 L/s), the optimum configurations of DTs and TTs were selected to investigate the effect of having the proposed setup on the SOTE. For membrane diffusers, DTs and TTs limited the dispersion of the air bubbles in the tank, therefore, reducing the SOTE (8.3% for DT and 3.7% for the TT). The ceramic and sharp-nub diffusers were also tested versus rubber membrane ones to determine the effect of using the ceramic and sharp-nub diffusers on the power reclamation and SOTE. Ceramic diffusers neither achieve higher power reclamation than the membrane nor increases the SOTE. In contrast, sharp-nub diffusers increase the SOTE for all configurations compared to membranes, but this came into account of power reclamation, where sharp-nub diffusers cause a DT and a TT to produce less power than ST does.

Energy & Fuels↗
DOE OSTI2022

Autonomous Closed-Loop Experimental Characterization and Dynamic Model Validation of a Scaled Underwater Kite

This paper presents the closed-loop experimental framework and dynamic model validation for a 1/12-scale underwater kite design. The pool-based tow testing framework described herein, which involves a fully actuated, closed-loop controlled kite and flexible tether, significantly expands upon the capabilities of any previously developed open-source framework for experimental underwater kite characterization. Specifically, the framework has allowed for the validation of three closed-loop flight control strategies, along with a critical comparison between dynamic model predictions and experimental results. In this paper, we provide a detailed presentation of the experimental tow system and kite setup, describe the control algorithms implemented and tested, and quantify the level of agreement between our multi-degree-of-freedom kite dynamic model and experimental data. Finally, we also present a sensitivity analysis that helps to identify the most influential parameters to kite performance and further explain the remaining mismatches between the model and data.

42 ENGINEERING↗
DOE OSTI2022

Novel Tube Design for Superheater Heat Exchanger Enabled Via Additive Manufacturing

Superheater tubes are critical boiler components that operate at relatively higher temperatures and pressure. Amongst the primary concerns for these tubes is the deposition of ash particles on the tube surface, leading to the reduced thickness of the tube due to material corrosion, consequently causing early creep failure of the component. In this research, a novel tube design has been proposed which resembles a teardrop or ogive shape to reduce the drag and concurrently improve the creep life of the superheater tubes. To administer the practicality of novel tubes, metal additive manufacturing (AM), for instance, laser-powder bed fusion (L-PBF), has been proposed. These unconventional designs were assessed and compared with the baseline circular tube design for mechanical design requirements (hoop stress and creep life) and the particle and flue gas flow characteristics around the differently shaped tubes. A thermomechanical finite element (FE) analysis was performed for hoop stress calculations. This study also emphasizes on effect of circumferential thermal variation on hoop stress distribution in tubes. Therefore, a detailed two-dimensional (2D) thermal simulation has been performed to report the circumferential thermal variation on the tube. A computational fluid dynamics (CFD) analysis coupled with particle tracing was performed for gas flow visualization and particle tracing around the proposed shapes and baseline circular-shaped tube design. The Schlieren optic setup was built and leveraged for qualitative validation of the proposed design. The complete design methodology established in the paper shows teardrop-shaped tubes better in terms of drag and creep life in contrast to the circular-shaped tube.

42 ENGINEERING↗
DOE OSTI2023

High-Fidelity Energy Deposition Ignition Model Coupled with Flame Propagation Models at Engine-like Flow Conditions

With the heightened pressure on car manufacturers to increase the efficiency and reduce the carbon emissions of their fleets, more challenging engine operation has become a viable option. Highly dilute, boosted, and stratified charge, among others, promise engine efficiency gains and emissions reductions. At such demanding engine conditions, the spark-ignition process is a key factor for the flame initiation propagation and the combustion event. From a computational standpoint, there exist multiple spark-ignition models that perform well under conventional conditions but are not truly predictive under strenuous engine operation modes, where the underlying physics needs to be expanded. In this paper, a hybrid Lagrangian-Eulerian spark-ignition (LESI) model is coupled with different turbulence models, grid sizes, and combustion models. The ignition model, previously developed, relies on coupling Eulerian energy deposition with a Lagrangian particle evolution of the spark channel, at every time-step. The spark channel is attached to the electrodes and allowed to elongate at a speed derived from the flow velocity. The LESI model is used to simulate spark ignition in a nonquiescent crossflow environment at engine-like conditions, using converge commercial computational fluid dynamics (CFD) solver. The results highlight the consistency, robustness, and versatility of the model in a range of engine-like setups, from typical with Reynolds-averaged Navier-Stokes (RANS) and a larger grid size to high fidelity with large-eddy simulation (LES) and a finer grid size. The flame kernel growth is then evaluated against Schlieren images from an optical constant volume ignition chamber with a focus on the performance of flame propagation models, such as G-equation and thickened flame model, versus the baseline well-stirred reactor model. Finally, future development details are discussed.

Advanced ignition modeling↗
DOE OSTI2023

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Here, real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

42 ENGINEERING↗
DOE OSTI2024

Process damping identification using Bayesian learning and time domain simulation

Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. However, existing methods for identifying process damping models experimentally require specialized setups and/or multiple cutting tests. While the phenomenon is well known, the modeling challenges limit pre-process parameter selection that leverages the potential increases in material removal rates. This paper proposes a physics-informed Bayesian method that can identify the cutting force and process damping models from a limited set of test cuts without requiring direct measurements of cutting force or vibration. The method uses time domain simulation to incorporate process damping and provide a basis for test selection. Here, new strategies for efficient sampling and dimensionality reduction are applied to lower computation time and minimize the effect of model error. The proposed method is demonstrated and the identified cutting and damping force coefficients are compared to values obtained using machining tests and least-squares fitting.

42 ENGINEERING↗
DOE OSTI2025

Microbead Encapsulation for Protection of Electronic Components

Here, this study investigates the application of microbeads as an innovative encapsulation technique to protect electronic components from harsh mechanical strain. Traditional encapsulation methods using hard epoxy provide substantial mechanical support but create thermal expansion mismatch issues, potentially leading to electronic component failure. We explore the use of finely powdered microbeads to achieve protective structures combining stiffness and energy absorption. The research focuses on key variables, including microbead size, microbead roughness, compaction of microbeads, and circuit board mounting in the encapsulation, all of which influence the encapsulation’s effectiveness. Experimental setups and testing protocols were developed to assess the performance of various microbead materials under different impact conditions. Results demonstrate that microbead encapsulation significantly reduces strain on circuit boards, minimizing the risk of damage during mechanical shocks. However, challenges remain, such as optimizing microbead characteristics and modeling their behavior within large-scale circuit board assemblies. Despite these challenges, the findings suggest that microbead encapsulation offers a promising alternative to conventional methods, enhancing the durability and reliability of electronic components in high-stress environments.

42 ENGINEERING↗
DOE OSTI2025

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗
DOE OSTI2023

Multiphase Modeling in a Parallel Plate Fluidized Bed Receiver for Concentrating Solar Power

A novel high temperature particle solar receiver is developed by using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a packed bed at the lower end, leaving the system from the bottom at a constant flow rate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built and a near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2K.

CSP↗
DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗
DOE OSTI2021

High resolution depth profiling using near-total-reflection hard x-ray photoelectron spectroscopy

By adjusting the incidence angle of incoming x rays near the critical angle of x-ray total reflection, photoelectron intensity is strongly modulated due to the variation of x-ray penetration depth. Photoelectron spectroscopy combined with near-total reflection exhibits tunable surface sensitivity, providing depth-resolved information. In this Review, we first describe the experimental setup and specific data analysis process. We then review three different examples that show the broad application of this method. Furthermore, the emphasis is on its applications correlated to oxide heterostructures, especially quantitative depth analyses of compositions and electronic states. In the last part, we discuss the limitations of this technique, mostly in terms of the range of samples that can be studied.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Epitaxial oxide thin films for oxygen electrocatalysis: A tutorial review

Epitaxial thin films can offer unprecedented definition of an electrocatalyst surface, defining the crystallographic orientation, interaction with a current collector, and providing an atomically flat surface for quantitative spectroscopy yielding mechanistic insight. This review introduces experts in thin films to the important parameters of electrochemical setups, techniques, and methods for quantifying electrocatalytic activity and comparing it across the literature. Examples are drawn from the literature measuring oxygen electrocatalysis on epitaxial oxide thin films. Furthermore, we share best practices in the robust measurement of intrinsic activity of thin films, including methods of electrical contact and assessment of charge transport in situ. We conclude by highlighting recent insights from epitaxial films in understanding oxygen electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Operando XPS in reactive plasmas: The importance of the wall reactions

In this article, advancements in differential pumping and electron optics over the past few decades have enabled x-ray photoelectron spectroscopy (XPS) measurements at (near-)ambient pressures, bridging the pressure gap for characterizing realistic sample chemistries. Recently, we have demonstrated the capabilities of an ambient pressure XPS setup for in situ plasma environment measurements, allowing plasma-surface interactions to be studied in operando rather than using the traditional before-and-after analysis approach. This new “plasma-XPS” technique facilitates the identification of reaction intermediates critical for understanding plasma-assisted surface processes relevant to semiconductor nanomanufacturing, such as physical vapor deposition, etching, atomic layer deposition, and many other plasma applications. In this paper, we apply the plasma-XPS approach to monitor real-time surface chemical changes on a model Ag(111) single crystal exposed to oxidizing and reducing plasmas. We correlate surface-sensitive data with concurrent gas-phase XPS measurements and residual gas mass-spectrum analysis of species generated during plasma exposure, highlighting the significant role of plasma-induced chamber wall reactions. Ultimately, we demonstrate that plasma-XPS provides comprehensive insights into both surface and gas-phase chemistry, establishing it as a versatile and dynamic characterization tool with broad applications in microelectronics research. Finally, we outline potential enhancements and future metrology directions to advance plasma-XPS investigations further.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthesis and characterization of electron beam irradiation-induced damage in polycrystalline metal thin films

High-energy physics research, industrial sterilizing, and material processing depend extensively on electron beam accelerators. Exit windows are crucial components of such electron accelerator systems, maintaining vacuum integrity inside the machine while providing mechanical strength, thermal stability, and radiation resistance at the beam-target interface. In this study, thin metallic films of Ni, Ti, Cr, and V were explored for use in electron beam exit windows, and their properties were compared with the properties of their bulk counterparts. Simulation results of metal foils predicted Ti to exhibit less beam power dissipation compared to Ni. However, Ni possesses superior mechanical and structural properties compared to Ti. The performance of these films under electron beam irradiation was examined by depositing thin layers of these films on silicon and metallic substrates using magnetron sputtering and exposing them to e-beam irradiation in a controlled setup. The deposited films were subjected to a dose of approximately 66 kGy at a beam energy of 10 MeV and characterized prior to and postexposure to the beam using field emission scanning electron microscopy, atomic force microscopy, x-ray diffraction (XRD), and nanoindentation. Particular emphasis was given to characteristics like the grain structure, surface morphology, dislocation density, and hardness. XRD patterns revealed irradiation-induced changes in peak intensities, while the crystallinity remained largely unchanged. Nanoindentation results showed that the pristine and irradiated Ti and Ni films were twice as hard when compared to bulk Ti and Ni samples, regardless of the substrate type used (Si or bulk Ti, or Ni). These results emphasize the superior mechanical properties of thin metal films compared to their bulk counterparts. In conclusion, this study advances the optimization of thin film materials for robust and efficient e-beam applications, ensuring improved durability and operational reliability.

AFM↗
DOE OSTI2021

A Survey of Thermal Sensing Application in Additive Manufacturing

Industry 4.0 represents a significant change in manufacturing with the inclusion of such technologies as additive manufacturing and data analytics. In support of these changes, infrared thermal imaging (IR) and very-near infrared (VNIR) have proven invaluable in numerous applications related to additive manufacturing. In this review, these applications will be presented as they relate to polymer and metal-based additive manufacturing processes. Applications including in-situ characterization, post-build analysis, experimental setups, modeling, and machine learning will be covered. With a general overview complete, the review will conclude with a discussion of challenges identified throughout the literature and thoughts on future trends.

Borish, Michael↗
DOE OSTI2022

NIR fluorescence lifetime macroscopic imaging with a time-gated SPAD camera

The performance of SwissSPAD2 (SS2), a large scale, widefield time-gated CMOS SPAD imager developed for fluorescence lifetime imaging, has recently been described in the context of visible range and fluorescence lifetime imaging microscopy (FLIM) of dyes with lifetimes in the 2.5 – 4 ns range. Here, we explore its capabilities in the NIR regime relevant for small animal imaging, where its sensitivity is lower and typical NIR fluorescent dye lifetimes are much shorter (1 ns or less). We carry out this study in a simple macroscopic imaging setup based on a compact NIR picosecond pulsed laser, an engineered diffuser-based illumination optics, and NIR optimized imaging lens suitable for well-plate or small animal imaging. Because laser repetition rates can vary between models, but the synchronization signal frequency accepted by SS2 is fixed to 20 MHz, we first checked that a simple frequency-division scheme enables data recording for different laser repetition rates. Next, we acquired data using different time gate widths, including gates with duration longer than the laser period, and analyzed the resulting data using both standard nonlinear least-square fit (NLSF) and phasor analysis. We show that the fixed synchronization rate and large gate widths characterizing SS2 (10 ns and over) are not an obstacle to accurately extracting lifetime in the 1 ns range and to distinguishing between close lifetimes. As a result, SS2 and similar very large gated SPAD imagers appear as a versatile alternative to other widefield time-resolved detectors for NIR fluorescence lifetime imaging, including preclinical molecular applications.

FLIM↗