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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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16 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Convection in Scaled Turbine Internal Cooling Passages With Additive Manufacturing Roughness

Abstract Additive manufacturing processes, such as direct metal laser sintering (DMLS), enable the creation of novel turbine cooling internal passages and systems. However, the DMLS method produces a significant and unique surface roughness. Previous work in scaled passages analyzed pressure losses and friction factors associated with the rough surfaces, as well as investigated the velocity profiles and turbulent flow characteristics within the passage. In this study, the heat transfer characteristics of scaled additively manufactured surfaces were measured using infrared (IR) thermography. Roughness panels were CNC machined from plates of aluminum 6061 to create near isothermal roughness elements when heated. Fluid resistance differences between the aluminum roughness panels and roughness panels constructed from ABS plastic using the same roughness patterns from McClain et al. (2020, “Flow in a Simulated Turbine Blade Cooling Channel With Spatially Varying Roughness Caused by Additive Manufacturing Orientation,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-16069) were investigated. Finally, the overall thermal performance enhancements and friction losses were assessed through the calculation of surface averaged “global thermal performance” ratios. The global thermal performance characterizations indicate results in-line with those found for traditional commercial roughness and slightly below traditional internal passage convection enhancement methods such as swirl chambers, dimples, and ribs. The passages investigated in this study do not include compressibility effects or the long-wavelength artifacts and channel geometric deviations observed by Wildgoose et al. (2020, “Impact of Additive Manufacturing on Internal Cooling Channels with Varying Diameters and Build Directions,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-15049). However, the results of this study indicate that, based on the roughness augmentation alone, artificial convective cooling enhancers such as turbulators or dimples may still be required for additively manufactured turbine component cooling.

Engineering↗
DOE OSTI2021

Impact of Additive Manufacturing on Internal Cooling Channels With Varying Diameters and Build Directions

Abstract The use of additive manufacturing (AM) processes, such as direct metal laser sintering, provides the design freedom required to incorporate complex cooling schemes in gas turbine components. Additively manufactured turbine components have a range of cooling feature sizes and, because of the inherent three-dimensionality, a wide range of build angles. Previous studies have shown that AM built directions influence internal channel surface roughness that, in turn, augment heat transfer and pressure loss. This study investigates the impact of AM on channel feature size and builds direction relative to tolerance, surface roughness, pressure losses, and convective cooling. Multiple AM coupons were built from Inconel 718 consisting of channels with different diameters and a variety of build directions. An experimental rig was used to measure pressure drop to calculate friction factor and was used to impose a constant surface temperature boundary condition to collect Nusselt number over a range of Reynolds numbers. Significant variations in surface roughness and geometric deviations from the design intent were observed for distinct build directions and channel sizes. These differences led to notable impacts in friction factor and Nusselt number augmentations, which were a strong function of build angle.

Engineering↗
DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗
DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Tailoring Surface Roughness Using Additive Manufacturing to Improve Internal Cooling

Abstract Surface roughness present on internal cooling channels produced with additive manufacturing has been previously shown to augment heat transfer and pressure loss to levels similar to traditionally cast turbulators. Given the ability of the surface roughness to improve the cooling performance of small cooling channels, the question arises on whether there is an optimal combination of random roughness features to maximize internal cooling performance. To investigate this question, test coupons with different surface roughness morphologies and magnitudes were manufactured by manipulating the parameters in the laser powder bed fusion additive manufacturing process. The coupons were tested to characterize the friction factor and Nusselt number of the cooling channels over a range of Reynolds numbers. Results showed that certain roughness combinations outperformed others, increasing the internal cooling performance of the channels. Additionally, manipulation of the performance using the process parameters allowed for reductions in build time, which could be useful for controlling component cost.

Engineering↗
DOE OSTI2020

The hidden value of large-rotor, tall-tower wind turbines in the United States

The significant upscaling of wind turbine size (nameplate capacity, rotor diameter, and tower height) has, to date, been driven primarily by a goal of minimizing the levelized cost of energy. But with wind’s levelized cost of energy now comparable with that of other generating resources, other design considerations besides cost-minimization have grown in importance—particularly as wind’s increasing market penetration begins to impose challenges on the electric grid. We find that taller towers and larger rotors (relative to nameplate capacity) can enhance the value of wind energy to the electricity system and provide other “hidden” benefits. Specifically, in regions where wind penetration has reached around 20%, we find a boost in wholesale market value of US$2–US$3/MWh. This is augmented by transmission, balancing, and financing benefits that sum to roughly US$2/MWh. The aggregate potential value enhancement of US$4–US$5/MWh is comparable with a 10%–15% reduction in levelized costs.

17 WIND ENERGY↗
DOE OSTI2025

Computational and Experimental Investigation of Discrete “W” Turbulators for sCO2 Turbine Internal Cooling

Direct-fired supercritical CO2 (sCO2 ) cycles are of particular interest for power generation due to the potential for higher thermal efficiencies with inherent CO2 capture. Direct fired sCO2 turbines must withstand high temperatures and the density of the working fluid is much higher than conventional Brayton cycles. Based on conventional Brayton cycle applications, internal serpentine cooling channels with ribbed turbulator strips are a common approach to achieve the required cooling, while minimizing coolant utilization. Most of the previous studies of coolant channel heat transfer enhancements have focused on serpentine channels using air as the cooling media at Reynold’s numbers typical of Brayton cycles. This paper investigates the Nusselt number augmentation of coolant channels with no features, ribbed turbulators, and discrete “W” turbulators with surface roughness effects included and CO2 as the coolant. The numerical results are compared to experimental results using CO2 as the cooling media at Reynold’s numbers ranging from 100,000 to 300,000. The results show the Nusselt number augmentation plateaus with increasing Reynolds number, in contrast to the decay observed in prior publications with air as the coolant media. Additionally, the CFD results indicate the discrete “W” geometry provides a 10% increase in Nusselt number augmentation relative to the angled ribbed turbulators.

computational fluid dynamics (CFD)↗
DOE OSTI2022

Investigation of Gas Turbine Internal Cooling Using Supercritical CO 2 —Effect of Surface Roughness and Channel Aspect Ratio

In this paper, an experimental and numerical investigation of internal cooling channels with rib turbulators is presented with sCO 2 as the working fluid at process conditions (pressure-20.7 MPa and temperature up to 150 °C). The effect of channel aspect ratio up to 2:1 on thermal-hydraulic performance is explored in additively manufactured rectangular channels and square channels, both with and without 60 deg ribs on the top and bottom sides. The Wilson-plot method is employed to experimentally measure channel-averaged Nusselt number over a Reynolds number range up to 370,000. The friction factor is calculated from pressure drop and mass flow rate and additionally, the overall thermal performance factor (TPF) is reported. A companion computational fluid dynamics (CFD) simulation is performed for the rib turbulated cooling configurations reported in the experiments using the Reynolds average Navier–Stokes-based turbulence model. The objective of the numerical study is to gain insight into the local heat transfer augmentation in the ribbed channels as a result of varying the aspect ratio, channel configuration (square versus rectangular), operating conditions (Reynolds number) and the surface roughness, an inherent outcome of the additive manufacturing process. Surface roughness is simulated using sand grain roughness height (K S ) calculated from the experimental data, and a comparison is presented with the corresponding channel configuration with varying surface roughness heights starting from smooth surfaces (K S = 0). Experimental results indicate that the heat transfer augmentation is negligible in the rectangular channels with ribs on the long side compared to the square channel. However, it is enhanced by 60% in comparison to placing ribs on the shorter side. The TPF remains constant at around 1 for the entire range of Reynolds numbers consistent with prior work at the National Energy Technology Laboratory (NETL). Here, the simulation results highlight that increased surface roughness can have a favorable considerable influence on Nusselt number and overall thermal performance enhancement.

42 ENGINEERING↗
DOE OSTI2024

Evaluating community solar as a measure to promote equitable clean energy access

Rooftop and community solar are alternative product classes for residential solar in the United States. Community solar, where multiple households buy solar from shared systems, could make solar more accessible by reducing initial costs and removing adoption barriers for renters and multifamily building occupants. Here we test whether community solar has expanded solar access in the United States. On the basis of a sample of 11 states, we find that community solar adopters are about 6.1 times more likely to live in multifamily buildings than rooftop solar adopters, 4.4 times more likely to rent and earn 23% less annual income. In this study, we do not find that community solar expands access in terms of race. These differences are driven, roughly evenly, by inherent differences between the two solar products and by policies to promote low-income community solar adoption. The results suggest that alternative solar products can expand solar access and that policy could augment such benefits.

14 SOLAR ENERGY↗
DOE OSTI2022

Measurement of Charged Current Inclusive $\bar{V}_\mu$ Interactions and 2p2h Contribution Using the NOvA Near Detector

More precise measurements of the scattering of antineutrinos on nuclei in the few GeV region of incident energy, $E_{\nu}$, can reveal new aspects of $v/\bar{v}$ interactions and of nuclear structure, while providing information crucial to continued progress by neutrino oscillation experiments. This Thesis reports an investigation of charged current $\bar{v}_\mu$ interactions in the predominantly hydrocarbon medium of the NOvA Near Detector. The data are obtained with the detector exposed to a narrow-band $\bar{v}$ µ beam with spectral peak at E ν = 2.0 GeV, for a total accumulated exposure of 12.5×10$^{20}$ protons-on-target. The analysis expresses results in terms of three-momentum transfer,|$\vec{q}$| and available hadronic energy, $E$ avail . These variables approximate (q 0 , |$\vec{q}$|), the variables used in theoretical treatments of lepton scattering on multi-nucleon systems such as in 2-particle-2-hole (2p2h) processes. This Thesis delivers two core measurements: Firstly, the double-dierential cross section $d^2σ/d|\vec{q} |dE_{avail}$ for inclusive CC $\bar{v}_\mu$ interactions in the NOvA detector medium is obtained. The cross section has a roughly gaussian shape in its projection onto |$\vec{q}$|, while being largely concentrated at values of $E$ avail below 100 MeV. The single diferential cross sections dσ/d|$\vec{q}$| and dσ/dE avail are also obtained, and are compared to predictions based on the GENIE v3.0.6 neutrino generator augmented with four different implementations of 2p2h reactions. Secondly, the contribution of 2p2h reactions to the CC inclusive scattering sample is determined. Its presence is characterized in terms of double-differential and single-differential cross sections. The latter 2p2h distributions are compared to predictions from two experimental data-tune models and from two theory-based models, namely the SuSAv2 model and the Valencia model. Both of the theoretical models underpredict the measured cross-section strength and predict a shape for dσ/d|$\vec{q}$| that is flatter than the measured shape. Thus, this Thesis provides new information about CC antineutrino-nucleus scattering in the vicinity of Eν ~ 2 GeV, and it highlights improvements that are needed in theoretical treatments of 2p2h reactions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Size and Shape Constraints of (486958) Arrokoth from Stellar Occultations

We present the results from four stellar occultations by (486958) Arrokoth, the flyby target of the New Horizons extended mission. Three of the four efforts led to positive detections of the body, and all constrained the presence of rings and other debris, finding none. Twenty-five mobile stations were deployed for 2017 June 3 and augmented by fixed telescopes. There were no positive detections from this effort. The event on 2017 July 10 was observed by the Stratospheric Observatory for Infrared Astronomy with one very short chord. Twenty-four deployed stations on 2017 July 17 resulted in five chords that clearly showed a complicated shape consistent with a contact binary with rough dimensions of 20 by 30 km for the overall outline. A visible albedo of 10% was derived from these data. Twenty-two systems were deployed for the fourth event on 2018 August 4 and resulted in two chords. The combination of the occultation data and the flyby results provides a significant refinement of the rotation period, now estimated to be 15.9380 ± 0.0005 hr. The occultation data also provided high-precision astrometric constraints on the position of the object that were crucial for supporting the navigation for the New Horizons flyby. This work demonstrates an effective method for obtaining detailed size and shape information and probing for rings and dust on distant Kuiper Belt objects as well as being an important source of positional data that can aid in spacecraft navigation that is particularly useful for small and distant bodies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Associative memories using complex-valued Hopfield networks based on spin-torque oscillator arrays

Abstract Simulations of complex-valued Hopfield networks based on spin-torque oscillators can recover phase-encoded images. Sequences of memristor-augmented inverters provide tunable delay elements that implement complex weights by phase shifting the oscillatory output of the oscillators. Pseudo-inverse training suffices to store at least 12 images in a set of 192 oscillators, representing 16 × 12 pixel images. The energy required to recover an image depends on the desired error level. For the oscillators and circuitry considered here, 5% root mean square deviations from the ideal image require approximately 5 μ s and consume roughly 130 nJ. Simulations show that the network functions well when the resonant frequency of the oscillators can be tuned to have a fractional spread less than 10 −3 , depending on the strength of the feedback.

Prasad, Nitin (ORCID:0000000180880164)↗
DOE OSTI2021

Surface Roughness Effects on Heat Transfer in Additively Manufactured sCO 2 Cycle Heat Exchangers

An experimental study was performed to consider the impact of surface roughness on heat transfer and pressure drop to supercritical carbon dioxide (sCO 2 ) in additively manufactured channels. All tests were performed in the Heat Exchange and Experimental Testing (HEET) rig at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia. Four test articles were considered. The first was a hydrodynamically smooth, drawn tube. The other three were additively manufactured channels with square and rectangular cross sections, which were characterized by sand-grain roughness to hydraulic diameter ratios spanning 0.0029 to 0.0073. Friction factors were determined by measuring the tube mass flow rate and pressure drop. The tube side heat transfer coefficient was measured using the Wilson plot technique. It was found that the friction factor results were 8% greater than the Colebrook correlation. Greater deviation was observed between the heat transfer results and the correlations. The Gnielinski correlation overpredicted the experimental points by nominally 30% and the Norris correlation overpredicting the experimental points by nominally 25%. A thermal performance factor was formed from the friction factor augmentation and Nusselt number augmentation results. These results indicated a 10% improvement in heat duty for a heat exchanger constructed utilizing a tube with ϵ/D_h =0.0073 relative to a heat exchanger utilizing a smooth, conventional tube.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Background-Oriented Schlieren Velocimetry of Helium Coolant Flow in Additively Manufactured Channels

High-pressure helium gas cooling is an attractive solution for thermal management of the fusion blanket first wall, as this coolant is chemically and neutronically inert and separable from hydrogenic species. However, due to the low thermal mass of helium, geometric optimization of these channels is required to provide sufficient cooling at manageable flow rates and pumping burdens. Increasingly, analysis and optimization of these coolant channels rely on computational fluid dynamics (CFD) simulations, and these require relevant experimental data for turbulence model validation. Toward this end, a high-pressure helium gas flow visualization system has been employed to image the flow of helium in flow channels with one-sided heating, mimicking the blanket first wall environment. Flow of helium at 4 MPa pressure and flow rates up to 68 g/s (Reynolds number 57 000) is supplied to rectangular channel test sections, with uniform heating applied to the bottom wall of the channel at heat fluxes varied between roughly 50 and 130 kW/m2. A high-speed camera is used to image index of refraction (IOR) gradients in the fluid via background-oriented schlieren (BOS), and temperature and pressure instrumentation are used to characterize thermal-hydraulic performance of each channel. Cross correlation of time-resolved BOS images is then used to calculate time-averaged 2-D helium velocity fields. Flow in additively manufactured (AM) channels is examined in this manner, including both featureless channels and those containing baffling as a heat transfer enhancement. The flow distribution seen in the featureless case differs significantly from that seen in prior simulations, whereas the flow in the baffled case shows the predicted behavior of flow forced along the heated wall. This augmented flow distribution is seen to increase the heat transfer coefficient in the baffled test section. Here, strategies are discussed for ongoing and future validation of these simulations, with the aim of model deployment for blanket cooling design and optimization.

Additive manufacturing↗
DOE OSTI2022

Evaluating Tropical Precipitation Relations in CMIP6 Models with ARM Data

Abstract A set of diagnostics based on simple, statistical relationships between precipitation and the thermodynamic environment in observations is implemented to assess phase 6 of the Coupled Model Intercomparison Project (CMIP6) model behavior with respect to precipitation. Observational data from the Atmospheric Radiation Measurement (ARM) permanent field observational sites are augmented with satellite observations of precipitation and temperature as an observational baseline. A robust relationship across observational datasets between column water vapor (CWV) and precipitation, in which conditionally averaged precipitation exhibits a sharp pickup at some critical CWV value, provides a useful convective onset diagnostic for climate model comparison. While a few models reproduce an appropriate precipitation pickup, most models begin their pickup at too low CWV and the increase in precipitation with increasing CWV is too weak. Convective transition statistics compiled in column relative humidity (CRH) partially compensate for model temperature biases—although imperfectly since the temperature dependence is more complex than that of column saturation. Significant errors remain in individual models and weak pickups are generally not improved. The conditional-average precipitation as a function of CRH can be decomposed into the product of the probability of raining and mean precipitation during raining times (conditional intensity). The pickup behavior is primarily dependent on the probability of raining near the transition and on the conditional intensity at higher CRH. Most models roughly capture the CRH dependence of these two factors. However, compensating biases often occur: model conditional intensity that is too low at a given CRH is compensated in part by excessive probability of precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Electronic Structure Correspondence of Singlet-Triplet Scale Separation in Strained Sr2RuO4

At a temperature of roughly 1 K, Sr 2 RuO 4 undergoes a transition from a normal Fermi liquid to a superconducting phase. Even while the former is relatively simple and well understood, the superconducting state has not even been understood after 25 years of study. More recently, it has been found that critical temperatures can be enhanced by the application of uniaxial strain, up to a critical strain, after which it falls off. In this work, we take an “instability” approach and seek divergences in susceptibilities. This provides an unbiased way to distinguish tendencies to competing ground states. We show that in the unstrained compound, the singlet and triplet instabilities of the normal Fermi liquid phase are closely spaced. Under uniaxial strain, electrons residing on all orbitals contributing to the Fermiology become more coherent, while the electrons of the Ru-dxy character become heavier, and the electrons of the Ru d x z , y z characters become lighter. In the process, Im χ(q,ω) increases rapidly around q = ( 0.3 , 0.3 , 0 ) 2 π / a and q = ( 0.5 , 0.25 , 0 ) 2 π / a , while it gets suppressed at all other commensurate vectors, in particular at q = 0, which is essential for spin-triplet superconductivity. We observe that the magnetic anisotropy under strain drops smoothly, which is concomitant with the increment in singlet instability. Thus, the triplet superconducting instability remains the lagging instability of the system, and the singlet instability enhances under strain, leading to a large energy-scale separation between these competing instabilities. However, since this happens even without spin-orbit coupling, we believe it is primarily the enhancement in the spin fluctuation glue around quasi-anti-ferromagnetic vectors that drives the Cooper pairing instead of the magnetic anisotropy. At large strain, an instability to a spin density wave overtakes the superconducting one. The analysis relies on a high-fidelity, ab initio description of the one-particle properties and two-particle susceptibilities, based on the quasiparticle self-consistent GW approximation augmented by dynamical mean field theory. This approach is described and its high fidelity confirmed by comparing to observed one- and two-particle properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗