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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Prediction of thermal conductivity in dielectrics using fast, spectrally-resolved phonon transport simulations

We present a new method for predicting effective thermal conductivity in materials, informed by ab initio material property simulations. Using the Boltzmann transport equation in a self-adjoint angular flux formulation, we performed simulations in silicon at room temperatures over length scales varying from 10 nm to 10 micron and report temperature distributions, spectral heat flux and thermal conductivity. Our implementation utilizes a Richardson iteration on a modified version of the phonon scattering source. In this method, a closure term is introduced to the transport equation which acts as a redistribution kernel for the total energy bath of the system. This term is an effective indicator of the degree of disorder between the spectral phonon radiance and the angular phonon intensity of the transport system. In conclusion, we employ polarization, density of states and full dispersion spectra to resolve thermal conductivity with numerous angular and spatial discretizations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Using optical fibers to examine thermal mixing of liquid sodium in a pool-type geometry

Sodium fast reactors (SFR) are poised to be a leading candidate for the next generation of commercial nuclear reactor deployment. Companies are commissioning designs for SFR increasing the need for experimental and computational analysis to improve the economics and safety of these reactors. Analysis of SFR behavior during reactor transients directly informs the understanding of reactor safety. Particularly, investigating the thermal transients associated with the reactor loss of flow transient allows for informed design decisions to be made regarding reactor safety. During loss of flow transients the flow rate of the coolant is significantly reduced, but not necessarily stopped. The reduction in flow rate results in coolant temperatures exiting the reactor core that can be drastically different than the coolant in upper pool. When these different temperature fluids interact, thermally stratified layers can form causing cyclic thermal fatigue on the reactor vessel potentially leading to pre-material failure. Past experimental studies have lacked high resolution temperature measurements. This research focuses on demonstrating the reliability of novel techniques for acquiring high resolution temperature measurements in a scaled liquid sodium facility. Tests are conducted that simulate postulated loss of flow transients and provide unprecedented spatial temperature distribution measurements.

42 ENGINEERING↗
DOE OSTI2020

Analytical solution for partial heating on the exterior of the pipe with application to measuring fluid flow rate

An analytical model using Green’s functions for partial external heating of a pipe is developed, which results in an exact mathematical solution for the radial and axial temperature distribution in the pipe wall. Partial heating consists of a constant heat flux function imposed over a small section of the exterior of a pipe and for a limited time duration. The solution comprises steady-state and transient parts, and an algebraic identity is used to decrease the number of summation terms in the slowly-converging steady- state part. Intrinsic verification principles are used to verify the solution. As an example application, this transient solution is applied toward the development of a simple, noninvasive method for in-field measurement of the flow rate in pipes. Furthermore, to simulate this application, a pulse of energy is imposed to the wall of the pipe, and the developed mathematical solution is used to find the flow rate of the fluid inside the pipe. An optimal experiment is designed to find the best measurement location and time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Alternating conduction and convection drying of paper – an experimental analysis with a continuous data acquisition approach

In conventional multi-cylinder drying of paper and board, both conductive drying from steam-heated dryer cylinders and convective drying by flowing air over the paper surface in the pockets are used. Conductive drying from steam-heated drying cylinders is a critical component in providing the necessary thermal energy to paper and board as they dry. Steam temperature and internal and external resistances at the contacting surface are critical process parameters influencing the conductive drying process. An experimental setup was developed to study the alternating conductive and convective drying of paper and board. Paper sheet moisture, temperature, and temperature distribution within the heated platen and the instantaneous heat flux as the sheet was being dried were measured. The instantaneous heat flux, contact heat transfer coefficient, and drying rates were determined as drying proceeds. Experimental results, as well as comparisons to literature and commercial data, are presented. The conductive heat transfer coefficients determined were compared to traditional correlations normally used in the modeling of paper drying. Similarly, the convective heat and mass transfer coefficients are also determined and compared to literature data. In addition to the evaluation of alternating conductive and convective drying characteristics of paper and board, the potential inclusion of auxiliary energy components will also be included. Experimental results from the conduction and convection drying system are presented. Furthermore, this data will be useful in process development, intensification of manufacturing processes, and modeling and simulation of paper drying processes.

42 ENGINEERING↗
DOE OSTI2025

Additional considerations in analytical solution for time-dependent heat conduction in a three-dimensional multilayer sphere

This work presents an analytical method to solve the heat conduction equation in three dimensions for problems consisting of multilayer concentric spheres. The method can be used to treat time-varying heat conduction problems where the heat source that drives the transient is time-invariant. Equally applicable to all Poisson-type problems with concentric spherical geometry, the method consists of representing the solution as a summation of weighted eigenfunctions. The weights for each eigenfunction are computed algebraically. Previous work has already established the core constituents of the methodology. The current work augments the existing methods by including consideration of nonzero interface resistance between layers and explicit discussion on the boundary condition homogenization required to treat inhomogeneous problems. Also, two demonstration problems are presented. One demonstration problem is based on the method of manufactured solutions and therefore allows for comparison with exact expressions for the solution temperature distribution. The second, more complex, demonstration problem relies on the finite element method for comparisons. The expected convergence behavior is observed for both demonstration problems.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

In situ measurement of temperature and reduction of rutile titania using energy dispersive x-ray diffraction

Using in situ energy dispersive x-ray diffraction (EDXRD) the average specimen temperature of TiO 2 in the steady state of flash is experimentally determined. Comparison of the microstructure for flash sintering and conventional sintering in addition to the temperature determined from calibration of the unit cell expansion indicates that rapid Joule heating during flash sintering causes densification and grain growth comparable with conventional sintering. An average temperature approximation model is proposed to account for greybody radiation and thermal conduction. In conclusion, the inhomogeneity of the grain growth across the sample length is confirmed to correlate with inhomogeneity in temperature distribution and this suggests a current induced Peltier effect in n-type TiO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2019

LaserOrigami (LO) of three-dimensional (3D) components: Experimental analysis and numerical modeling-part II

The present work explores how the choice of the scanning patterns can affect the final shapes of 3D components manufactured by laser-origami with a High-Power Diode Laser (HPDL). The experimental approach allowed the achievement of high bending angles, also avoiding any distortion on the surface of AISI 304 stainless steel workpiece. Optimization of the operational parameters led to the best prototype of the 3D components, with the closest respect of the strictest dimensional and geometrical tolerances. In addition, a thermo-mechanical model to predict the final shape of the 3D components was developed. The numerical model, implemented by Finite Element Method (FEM), was discovered to be a reliable tool in predicting the final shape of the prototypes, matching with a great deal of accuracy the experimental results. Specifically, the model allowed the estimation of the temperature distribution and nodal displacements of the components varying both the setting of the laser parameters and the choice of the scanning patterns.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Impact of reduced dimensionality on the correlation length and magnetization dynamics of the spin chain cobaltite Ca 3 Co 2 O 6

We have recently applied the magnetic field and temperature dependence of magnetic entropy change as a probe of the magnetic states of a single crystal of Ca 3 Co 2 O 6 to establish a more comprehensive magnetic phase diagram for this exotic system. The results are consistent with the spin-density wave description of the ground state and indicate the suppression of the modulated state in favor of a ferrimagnetic up-up-down arrangement of the spin chains with the application of a moderate field. We demonstrate, in this study, that the features of the static magnetic phase diagram are preserved when the grain size of Ca 3 Co 2 O 6 is reduced to 440 nm (below the maximum c-axis correlation length of ~550 nm in Ca 3 Co 2 O 6 ), although the polycrystalline materials show a non-saturating behavior, rounded steps, and reduced magnetization when compared to the single crystal. Our new finding of the multiple low-temperature magnetization steps in the 440 nm sample, together with conflicting reports concerning such steps in nanostructured samples, suggests that correlations in the ab plane are more important than correlations along the c-axis in the appearance of the plateaus. The relaxation processes in the system are studied through the decay of remanent magnetization, ac susceptibility, and Argand diagrams. The introduction of grain boundaries in Ca 3 Co 2 O 6 weakens the slow-dynamic state, widens the low-temperature distribution of relaxation times, and lowers activation energies within the Arrhenius-like relaxation regime.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal loading analysis of the ring injection dump for the Spallation Neutron Source facility

The ring injection dump (RID) is the largest beam dump in the Spallation Neutron Source facility at Oak Ridge National Laboratory and accepts a fraction of the beam from the ring that is not captured in the ring during injection. Thermo-fluid modeling of the RID components was performed during the initial design by using the software ANSYS CFX to characterize the power rating for the RID. From the calculations, the power rating was lowered from 200 kW to 150 kW, at 1.3 GeV beam energy due to concerns regarding the heating of the concrete structure. The Proton Power Upgrade project scope included reevaluating the power limit to the RID in anticipation that increasing it would provide more operational flexibility. The focus was on the shielding because it was the limiting factor, and data collected from thermocouples installed on the structure were used to benchmark the analysis. A three-stage process was adopted in the latest study. First, the already existing steady-state calculations were validated and extended with the latest Monte Carlo N-Particle source term calculations. Second, transient calculations were conducted to capture the dynamic state of the system in response to the energy dumped to the RID during the following operational period of the beam from 2005–2019 (14 years), and sensitivity analyses of crucial parameters were performed to benchmark the model with reasonable accuracy. Finally, an idealized transient cycle analysis was conducted with realistic duty factors to predict the temperature distribution at higher beam powers. Overall, the results confirmed the accuracy of the original steady state model but allowed the development of a new validated transient model with higher accuracy for future analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Multiscale modelling of the phénix dissymmetric test benchmark

The Phenix sodium-cooled fast reactor contains two pools in which characteristic 3D effects like thermal stratification and jets play a significant role. One of the two active heat exchanger sets fails in the dissymmetric test, leading to changes in the thermal stratification and asymmetric conditions in the reactor. Therefore 3D modelling using Computational Fluid Dynamics codes (CFD) is required to model this transient in sufficient detail. However, several aspects of the reactor, like the core and the secondary side of the heat exchanger, can be modelled more efficiently by System Thermal-Hydraulics codes (STH). Therefore multiscale models are developed by coupling CFD and STH codes, exploiting the strengths of both codes in terms of modelling options and computational costs. The results provide insight in the local flow patterns and the temperature distribution during the dissymmetric transient. The results and modelling choices of the participants are compared in this paper and the main findings are discussed in the light of lessons learned from the blind phase of the benchmark and providing recommendations for future modelling of pool-type liquid metal-cooled reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Application of predictive data analytics to model daily hydrocarbon production using petrophysical, geomechanical, fiber-optic, completions, and surface data: A case study from the Marcellus Shale, North America

Predicting gas production from stimulated unconventional reservoirs has always been a challenge to oil and gas companies because the physics of fluid flow through such reservoirs is not well understood. On the other hand, modeling gas production from shale reservoirs is a complex multi-variate problem that requires proper integration of data from multiple disciplines, such as geology, petrophysics, geomechanics, completions, and surface-based measurements, etc. Here this study demonstrates the application of data-driven machine learning algorithms, integrating geoscientific, distributed acoustic sensing (DAS), distributed temperature sensing (DTS) fiber-optic, completions, flow scanner production log, and surface data to model daily gas production from a 28-stage stimulated horizontal well drilled in the Marcellus Shale of the Appalachian basin in North America. In addition, this study aims to utilize the data from a fiber-optic monitoring system, such as DAS and DTS to evaluate the well performance. We build supervised data-driven machine learning models using Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM) algorithms to understand the well performance and forecast the daily gas production. The study compares the forecasted results, tests the level of accuracy, and addresses different issues with these machine learning algorithms. A spatio-temporal database is constructed and used to perform sensitivity analyses to identify the key drivers for gas production. The results show that RF and ANN algorithms can be used to predict daily gas production with significantly high accuracy; however, RF algorithm is the best predictor in terms of highest accuracy (96%), less computational time and cost. Based on sensitivity analysis, it appears that Poisson's ratio, minimum horizontal stress, DAS, casing pressure, gamma log are the most important parameters to predict gas production.

02 PETROLEUM↗
DOE OSTI2022

Dynamic heterogeneity and nanophase separation in rubber-toughened amine-cured highly cross-linked polymer networks

Solid state nuclear magnetic resonance (NMR) spectroscopy and small-to wide-angle X-ray scattering (SWAXS) methods were used to characterize the heterogeneous dynamics and polymer domain structure in rubber modified thermoset materials containing the diglycidyl ether of bisphenol A (DGEBA) epoxy resin and a mixture of Jeffamine reactive rubber and 4,4-diaminodicyclohexylmethane (PACM) amine curing agent. The polymer chain dynamics and morphologies as a function of the PACM/Jeffamine ratio were determined. Using dipolar-filtered NMR experiments, the resulting networks are shown to be composed of mobile and rigid regions that are separated on nanometer length scales, along with a dynamically immobilized interface region. Proton NMR spin diffusion experiments measured the dimensions of the mobile phase to range between 9 and 66 nm and varied with the relative PACM concentration. Solid state 13 C magic angle spinning NMR experiments show that the highly mobile phase is composed entirely of the dynamically flexible polyether chains of the Jeffamine rubber, the immobilized interface region is a mixture of DGEBA, PACM, and the Jeffamine rubber, with the PACM cross-linked to DGEBA predominantly residing in the rigid phase. The SWAXS results showed compositional nanophase separation spanning the 11–77 nm range. These measurements of the nanoscale compositional and dynamic heterogeneity provide molecular level insight into the very broad and controllable glass transition temperature distributions observed for these highly cross-linked polymer networks.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Detailed modeling of hydrogen release and particle shrinkage during pyrolysis of inhomogeneous wood

Hydrogen release during pyrolysis of woody biomass is studied considering anisotropicity and inhomogeneity of wood structure. A new anisotropic shrinkage model is proposed based on the decomposition of main wood constituents, i.e., cellulose, hemicellulose, and lignin. The new shrinkage model can predict the temporal evolution of the wood structure, and the differences between axial and radial shrinkage during pyrolysis. The model agrees very well with several experimental data from the literature. Based on particle temperature during conversion, the pyrolysis is partitioned into four stages, and the hydrogen release and H 2 formation from each stage are investigated. Stage (IV) of pyrolysis, from 1000 to 1273 K, is found to be efficient for H 2 production owing to the production of considerable mass of H with a minimal amount of tar species. Furthermore, the char quality is found to be different at the end of stages (II), (III), and (IV), where around 67.7, 80.5, and 93.4% wt. of solid residue is made of carbon, respectively. The model is also used to explain how the heating rate affects the temperature distribution inside the particle and how it shifts the peak of hydrogen release. Finally, the pyrolysis of two inhomogeneous wood samples — a beech twig with bark and a beech dowel with growth rings — are investigated. The bark can affect the pyrolysis rate, products, and flow pattern inside the particle. The growth rings do not have a considerable effect on the pyrolysis rate and products, but they have a significant impact on the flow pattern. This has an important implication for char conversion studies where the internal surface area and porosity field distribution have a significant effect on the gasification and oxidation rates.

09 BIOMASS FUELS↗
DOE OSTI2023

Deposition-controlled phase separation in CuNb metallic alloys

Vapor co-deposited metal nanocomposites with immiscible components have shown to have several superior properties including mechanical performance, radiation tolerance, and enhanced functionalities. The morphology and structural design of these nanocomposites are important in determining the expression of these properties. The conditions used to deposit thin film nanocomposites are the governing factors in determining the final nanostructure. In this work, we link the effects of process gas pressure, substrate temperature, and sputtering target power on resultant Cu/Nb thin film nanostructures. Here, we find that for films with equiatomic phase fractions of Cu and Nb, inhomogeneous precipitate segregation dominated the structure at lower substrate temperature depositions while higher temperatures distributed the Cu and Nb phases more uniformly. Increasing process gas pressure during deposition lead to a spatially homogeneous, nanocrystalline structure of Cu/Nb. In situ annealing of this sample shows that the phase separated morphology of the two immiscible materials depends on the initial composition. Finally, compositions of Cu and Nb that were highly disparate lead to interface segregation of the minority phase. The morphological evolution observed in the Cu/Nb system is compatible with modified structural zone models for immiscible thin film systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On-chip sensing of hotspots in superconducting terahertz emitters

Intrinsic Josephson junctions in high-temperature superconductor Bi 2 Sr 2 CaCu 2 O 8+δ (BSCCO) are known for their capability to emit high-power terahertz photons with widely tunable frequencies. Hotspots, as inhomogeneous temperature distributions across the junctions, are believed to play a critical role in synchronizing the gauge-invariant phase difference among the junctions, so as to achieve coherent strong emission. In this paper, we demonstrate an on-chip in situ sensing technique that can characterize hotspot distributions on BSCCO. This is achieved by fabricating a series of micro-nanosized "sensor" junctions on top of an "emitter" junction and measuring the critical current on the sensors versus the bias current applied to the emitter. Furthermore, this fully electronic on-chip design can enable efficient close-loop control of hotspots in BSCCO junctions and significantly enhance the functionality of superconducting terahertz emitters.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Design and Integration of Flexible Sensor Matrix for in Situ Monitoring of Polymer Composites

Sensory polymer composites are highly desirable for applications such as in situ and real-time production processes and structural health monitoring, and for technologies that include human–machine interfaces for the next generation of Internet of Things. However, the development of these materials is still in its infancy: these materials have been reported, but large-scale fabrication of polymer composites with versatile and customizable sensing capabilities has yet to be demonstrated. Here, we report on a scalable fabrication strategy that enables such materials by designing and integrating PCB technology-inspired large-area flexible sensor matrices into polymer composites. The integrated sensor matrices successfully monitored in situ the production processes and structural health of an industrial polymer composite: from the application of vacuum, resin flow and polymerization, production defects, and temperature distribution. Our results demonstrate that the proposed strategy is a simple and effective solution as a distributed monitoring platform for polymer composites and shows the potential towards next generation of sensory polymer composites.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

High-Resolution Measurement of Soil Thermal Properties and Moisture Content Using a Novel Heated Fiber Optics Approach

Hydrological parameters are scale dependent. Efficient monitoring techniques capable of measuring hydrological parameters, such as soil moisture content (θ), over a wide range of spatial scales are essential for understanding the complexity of water and energy movement across the landscape. Techniques to measure θ over spatial scales in the range from centimeters to thousands of meters, however, are sorely lacking. Recent improvements in the distributed temperature sensing (DTS) technology supported the development of novel techniques to fill that gap. However, improvements in the accuracy and applicability of DTS techniques are still needed. This study investigates the possibility of improving the accuracy of the fiber optics dual-probe heat-pulse (FO-DPHP) DTS technique by using a new design to maintain the spacing between the FO-DPHP probes and by introducing a novel data interpretation approach. The accuracy of the novel FO-DPHP design was tested at different θ in a sand column experiment. The FO-DPHP measurements obtained using traditional and novel data interpretation approaches were compared against independent measurements from several calibrated soil water content (EC5) sensors. Monte-Carlo analyses were also performed to assess the impact of DTS measurement errors on the accuracy achieved using the data interpretation approaches. The novel design and data interpretation approach allowed for accurate measurements of soil thermal properties and θ without the need to perform a hard-to-achieve soil-specific calibration. Measured θ had mean errors and standard deviations <0.03 and <0.01 m 3 m -3 , respectively, for moisture conditions ranging from dry to near saturation. The standard deviation in the measured heat capacity was <0.01 MJ m -3 K -1 .

42 ENGINEERING↗