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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 127 records · Page 7

A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

14 SOLAR ENERGY↗

Nonequilibrium defect-phase nanostructures stabilized by irradiation in undersaturated Ni-Si nanocrystalline alloy

Nanocrystalline thin films of the undersaturated alloy Ni-8.5 at% Si were subjected to 2 MeV Ti irradiation at temperatures ranging from 450˚C to 550˚C. Correlative microscopy combining transmission electron microscopy (TEM), scanning-TEM and atom probe tomography (APT revealed that large dose irradiation at 450˚C of samples with initial grain sizes below 100 nm stabilized a novel nanostructure which surprisingly contained three co-existing phases, the γ face-centered-cubic (FCC) matrix, γ' L12 ordered precipitates on intragranular dislocation loops and Ni 31 Si 12 precipitates at triple junctions (TJs). In contrast, irradiation at 550˚C and irradiation of larger grain-size samples at 450˚C only produced a γ-γ' two-phase coexistence. Analysis of the three-phase nanostructure and phase field simulations indicates that radiation-induced segregation is most pronounced at TJs, thus triggering the formation of Ni 31 Si 12 precipitates. These incoherent precipitates, in turn, are expected to stabilize the grain size under irradiation. The results are generalized using the concept of driven defect-phases. It is suggested that the stabilization of driven defect-phases may impart radiation resilience by providing localized relaxation modes to the microstructure evolution during and after temporary perturbations in irradiation conditions.

36 MATERIALS SCIENCE↗

Role of the Porras factor in phase matching of high-order harmonic generation driven by focused few-cycle laser pulses

We investigate the role of the Porras factor (or laser focusing effect) on the macroscopic high-order harmonic generation (HHG) driven by a focused broadband few-cycle laser beam. By employing a non-adiabatic phase-matching analysis method, we reveal that phase mismatch due to the induced-dipole phase varies with the Porras factor, which is dominant in phase matching at low gas pressure. We also find that in a strongly ionized medium when gas pressure is high, the nonlinear propagation is dominated by a plasma effect such that the focusing effect is mitigated, resulting in similar poor phase matching of HHG regardless of the Porras factor. Our results are expected to assist experimentalists identifying optimal conditions for HHG using ultrashort laser pulses.

Optics↗

Analytical Modeling of Metal Foam Composite Phase Change Materials (PCM) in Thermal Energy Storage Using Asymptotic Analysis

The use of phase change materials (PCMs) for thermal energy storage can release or absorb a significant amount of latent heat during the freezing or melting process, offering a higher energy storage density. One of the main drawbacks of PCMs is their low thermal conductivity, resulting in poor thermal performance. Recent research has attempted to enhance heat transfer and increase the thermal conductivity of PCMs, including the use of metal foams. However, modeling the metal foam composite PCM using conventional methods is computationally expensive. This paper proposes an asymptotic solution for a Stefan-like problem subject to a convective boundary for outward solidification in a hollow cylinder, capable of predicting the freeze-melt cycle of the metal foam composite PCM. Specifically, three temporal regimes and four spatial layers are considered in the asymptotic analysis for each phase change process. The thermal conductivity is calculated by a theoretical three-dimensional tetrakaidecahedron model, while other thermophysical properties are obtained using the method of volume averaging. The results are verified with numerical data and validated against experimental data in the literature. The presented analytical modeling framework could have the potential to be applied to other types of composite PCMs with considerably lower computational costs compared with conventional methods.

analytical model↗

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗

Data-driven analysis and prediction of stable phases for high-entropy alloy design

High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.

36 MATERIALS SCIENCE↗

Industry Partnerships & Their Role In Reducing Natural Gas Supply Chain Greenhouse Gas Emissions – Phase 2

This analysis is the product of collaboration between Our Nation’s Energy Future (ONE Future) and the United States (U.S.) Department of Energy (DOE) National Energy Technology Laboratory (NETL). This analysis is an update to Phase 1 of the collaboration between ONE Future and NETL. Phase 1 had three objectives: 1. Calculate a greenhouse gas (GHG) emission profile representative of ONE Future’s supply chain, including methane (CH 4 ) emission rates. 2. Compare ONE Future’s emission profile to the emission profile for the U.S. natural gas supply chain. 3. Evaluate specific emission reduction opportunities. Phase 2 has two key enhancements over Phase 1: 1. The reporting year of the data is updated from 2016 to 2017. 2. The emission profiles and the specific emission reduction opportunities are regionalized for the ONE Future supply chain. The ONE Future supply chain is based on data provided by ONE Future members for all their U.S. onshore assets. ONE Future’s data are mostly representative of their participation in the Greenhouse Gas Reporting Program (GHGRP) administered by the Environmental Protection Agency (EPA) and is supplemented by ONE Future facilities that are not required to report to GHGRP. The U.S. scenario is based on NETL’s life cycle analysis (LCA) of natural gas extraction and power generation, which also uses data from the GHGRP (but does not include non-GHGRP facilities). In addition to the data from these sources, NETL accounted for uncertainty due to data variability, data limitations, and variability in liquids unloading frequency and event duration. This report is a re-issue of the 2020 study (published on July 28, 2020). It revises the device count in the mitigation strategy “pipeline pump-down before maintenance” in the Marginal Abatement Cost (MAC) Analysis section of the report (Section 7). Please see the addendum for more details on this revision and resultant changes. This revision does not change most of our conclusions and recommendations. It only changes the total methane reduced from all the mitigation opportunities (low cost and high cost) from 6.5 Bcf CH 4 /yr to 4.8 Bcf CH 4 /yr.

03 NATURAL GAS↗

Theoretical analysis of the saturation phase of the 1/1 energetic-ion-driven resistive interchange mode

The aim of the present study is to analyze the saturation regime of the energetic-ion-driven resistive interchange mode (EIC) in the LHD plasma. In this work, a set of nonlinear simulations are performed by the FAR3d code that uses a reduced MHD model for the thermal plasma coupled with a gyrofluid model for the energetic particle (EP) species. The hellically trapped EP component is introduced through a modification of the averaged drift velocity operator to include their precessional drift. The nonlinear simulation results show similar 1/1 EIC saturation phases with respect to the experimental observations, reproducing the enhancement of the n/m = 1/1 resistive interchange modes (RIC) amplitude and width as the EP β increases, the EP β threshold for the 1/1 EIC excitation, the further destabilization of the 1/1 EIC as the population of the helically trapped EP increases and the triggering of burst events. The frequency of the 1/1 EIC calculated during the burst event is 9.4 kHz and the 2/2 and 3/3 overtones are destabilized, consistent with the frequency range and the complex mode structure measured in the experiment. In addition, the simulation shows the inward propagation of the 1/1 EIC due to the nonlinear destabilization of the 3/4 and 2/3 energetic particle modes, leading to the partial overlapping between resonances during the burst event. Finally, the analysis of the 1/1 EIC stabilization phase shows the excitation of the 1/1 RIC as soon as the flattening induced by the 1/1 EIC in the pressure profile vanishes, leading to the retrieval of the pressure gradient at the plasma periphery and the overcoming of the RIC stability limit.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficient and robust stability analysis in the internal energy, volume, and moles (UVN) space

Hydrodynamic simulation of fluids in vessels is often based on the internal energy (U), volume (V), and the number of moles of all components ( re N = N 1 , N 2 , ..., N n ) as the working variables to determine the thermodynamic state by finding the global maximum of entropy. The procedure of finding the equilibrium state may be divided into two steps: stability analysis and phase-split computations. Stability analysis is performed first, and the phase-split computation proceeds if the system is unstable. Most of the past work on UVN space has been based on phase-split computations, while the stability analysis is barely investigated. Furthermore, previous studies for the stability analysis use only Newton's method to solve the non-linear algebraic equations. We present an efficient and robust approach for stability analysis where UVN is specified. The successive substitution iteration (SSI) is used to provide good initial guesses for Newton's method. The proposed approach results in a reduced number of unknowns and does not require a large number of iterations to achieve convergence in Newton's method. Overall, our proposed formulation is compatible with different equations of state and is applicable to both pure component and multi-components. The robustness and efficiency of the algorithm for stability analysis are demonstrated in various examples.

02 PETROLEUM↗

Electric Vehicles at Scale - Phase II - Distribution Systems Analysis

The use of electric vehicles (EVs) in the United States has grown significantly during the last decade, posing benefits to the environment but also potential challenges to our grid. To better understand this scenario , the Department of Energy (DOE) asked Pacific Northwest National Laboratory (PNNL) to perform an authoritative study of the impacts of EVs at scale on the electric grid. The Phase I study focused on the bulk power electricity impacts . This EV-at-scale Phase II work addresses key questions of interest to DOE related to the impacts of EV in the distribution systems: 1. When (which year), where, and how many EVs will be adopted and how will they be charged? 2. Given some prospective answers to the above question, what would be the EV hosting capability of a distribution system circuit? 3. How could the hosting capability be expanded to accommodate more EVs and what would be the potential measures and cost? This report documents the methodologies developed as part of this project and provides EV adoption modeling examples using distribution system circuit data provided by industry partner, Southern California Edison (SCE).

24 POWER TRANSMISSION AND DISTRIBUTION↗

New methodology for measuring electron density perturbations caused by plasma coherent modes using profile reflectometry: Magnitudes and radial profiles in DIII-D

New capabilities of fast-sweep frequency-modulated profile reflectometry are explored to measure electron density ne perturbation magnitudes and radial profiles due to plasma coherent modes in DIII-D. The first approach is based on the frequency analysis of phase perturbations associated with high frequency (~MHz) Alfvén eigenmodes (AEs). The measurement of ~5.5 MHz fast-ion-driven global Alfvén eigenmodes (GAEs) is demonstrated in a neutral beam-heated DIII-D plasma. The GAE induced a broad radial distribution of phase perturbations in the profile reflectometer data. Analysis of these data determined the effective cutoff location displacement and the estimated ne fluctuation profile. In the second approach, high resolution ne profiles are used directly to determine the radial structure of ne perturbations due to a neo-classical tearing mode. These new measurements broaden the application of profile reflectometry and advance the development of AE spectroscopy as a tool for non-invasive diagnosis of fast-ion-driven modes in DIII-D and burning plasmas such as ITER.

47 OTHER INSTRUMENTATION↗

Coulomb phase corrections to the transverse analyzing power AN(t) in high energy forward proton-proton scattering

Study of the polarized proton-proton elastic scattering in the Coulomb Nuclear interference region allows one to measure forward hadronic spin-flip amplitude including the phase. However, in a precision experimental data analysis, a phase shift correction δC due to the long distance Coulomb interaction should be taken into account. For the unpolarized scattering, δC is commonly considered as well established. Here, we evaluate the Coulomb phase shifts for the spin-flip electromagnetic and hadronic amplitudes. The difference between spin-flip and non-flip Coulomb phase shifts was found to be negligible for current experimental accuracy in the high energy transverse spin elastic pp measurements. However, effective alteration of the hadronic spin-flip amplitude by the long distance electromagnetic corrections can be noticeable.

43 PARTICLE ACCELERATORS↗

Improving Real-world Measurement-based Phase Identification in Power Distribution Feeders with a Novel Reliability Criteria Assessment

This paper is concerned with solving the phase identification problem in a real-world smart grid project; where there is only a few smart meters available on each of the five power distribution feeders in the test site in Riverside, CA. The main idea is to develop and use two reliability criteria that can identify the most reliable components in a broken-down phase identification analysis; thereby significantly improving the accuracy of phase identification. The proposed method consists of three steps. The results from field implementation reveal the accuracy and consistency of the proposed method in practice, in correctly and reliability identifying the phase connectivity.

Phase identification Data-driven method Sliding wi↗

Theoretical and experimental analysis of the modulated phase grating X-ray interferometer

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated phase grating (MPG) interferometer is a recently developed grating interferometry system capable of generating a directly resolvable interference pattern using a relatively large period grating envelope function that is sampled at a pitch that is small enough that X-ray spatial coherence can be achieved by using a microfocus X-ray source or G0 grating. We present the theory of the MPG interferometry system for a 2-dimensional staggered grating, derived using Fourier optics, and we compare the theoretical predictions with experiments we have performed with a microfocus X-ray system at Pennington Biomedical Research Center, LSU. The theoretical and experimental fringe visibility is evaluated as a function of grating-to-detector distance. Additionally, quantitative experiments are performed with porous carbon and alumina compounds, and the mean normalized dark-field signal is compared with independent porosimetry measurements. Qualitative analysis of attenuation and dark-field images of a dried anchovy are shown.

47 OTHER INSTRUMENTATION↗

Determination of asymptotic normalization coefficients for the channel 16 O→ α+ 12 C: excited state 16 O(0 + ; 6.05 MeV)

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In the present paper, we treat the ANC C for the virtual decay 16 O(0 + ; 6.05 MeV)→ α+ 12 C(g.s.), the known values of which are characterized by a large spread (0.29 - 1.65) × 10 3 fm -1/2 . The ANC C is found by analytic continuation in energy of the α 12 C s-wave scattering amplitude, known from the phase-shift analysis of experimental data, to the pole corresponding to the 16O bound state and lying in the unphysical region of negative energies. To determine C, two different methods of analytic continuation are used. In the first method, the scattering data are approximated by the sum of polynomials in energy in the physical region and then extrapolated to the pole. The best way of extrapolation is chosen on the basis of the exactly solvable model. Within the second approach, the ANC C is found by solving the Schrödinger equation for the two-body α 12 C potential, the parameters of which are selected from the requirement of the best description of the phase-shift analysis data at a fixed experimental binding energy of 16 O(0 + ; 6.05 MeV) in the α+ 12 C channel. The values of the ANC C obtained within these two methods lie in the interval (886–1139) fm -1/2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗

Combined DSC/TGA Analysis to Rationalize the As-Sintered Microstructure in Binder Jet Additively Manufactured H13 Tool Steel

In this study, a combined DSC/TGA analysis has been used to rationalize the constant liquid channel width at higher sintering temperatures in H13 tool steel manufactured by binder jet additive manufacturing. Using enthalpy conservation along with coupled DSC + TGA analysis, the phase fractions of liquid and austenite phases during heating and cooling respectively were estimated. The estimates from the DSC/TGA analysis were compared with equilibrium phase fraction predictions from ThermoCalc. The resulting phase evolution was correlated to the as-sintered microstructure to rationalize the unexpected lack of change in liquid channel width at higher sintering temperatures.

Kannan, Rangasayee↗

Performance analysis of single-phase immersion cooling system of data center using FC-40 dielectric fluid

Immersion cooling technologies have become an emerging cooling method for data center cooling. The studies available in open literature dealt with immersion cooling performance of data servers using mineral oil, EC-100, and Opticool 872552, but the studies focusing on the performance of FC-40 dielectric fluid is not available. Therefore, this study aimed to develop a single-phase liquid immersion cooling system using FC-40 dielectric fluid for a 1U (44.45 mm height) data server. The present study experimentally investigated the influence of different design and operating parameters, including the inlet/outlet port configuration (T and Z configurations), the bypass effect, the flowrate (1–3 LPM), the heating load (200–600 W), the inlet fluid temperature (15–35 °C), the presence of suction fan with various arrangements, and different heat sink bases (solid base, vapor chamber and heat pipe base). The results showed that the T-configuration could provide a 12.6% and 0.5–2.8 °C reduction in thermal resistance and case temperature compared to the Z-configuration, respectively. Additionally, the heat sink with heat pipe and vapor chamber base offered a minimum case temperature of 56.7 °C and 55.2 °C against the 60 °C experienced in the heat sink with flat plate base, respectively.

42 ENGINEERING↗