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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗
NASA NTRS2015

The Effect of Core Configuration on Thermal Barrier Thermal Performance

Thermal barriers and seals are integral components in the thermal protection systems (TPS) of nearly all aerospace vehicles. They are used to minimize heat transfer through interfaces and gaps and protect underlying temperature-sensitive components. The core insulation has a significant impact on both the thermal and mechanical properties of compliant thermal barriers. Proper selection of an appropriate core configuration to mitigate conductive, convective and radiative heat transfer through the thermal barrier is challenging. Additionally, optimization of the thermal barrier for thermal performance may have counteracting effects on mechanical performance. Experimental evaluations have been conducted to better understand the effect of insulation density on permeability and leakage performance, which can significantly impact the resistance to convective heat transfer. The effect of core density on mechanical performance was also previously investigated and will be reviewed. Simple thermal models were also developed to determine the impact of various core parameters on downstream temperatures. An extended understanding of these factors can improve the ability to design and implement these critical TPS components.

flow tests↗
DOE OSTI2024

Scale effects on core design, fuel costs, and spent fuel volume of pressurized water reactors

The desire to improve the economic competitiveness and deployment pace of nuclear energy through modularization, manufacturing, and series production had led to the development of smaller size reactors. As the standard 17x17 fuel technology is mainly maintained in the pressurized water reactors (PWRs) category, this translates into a lower number of fuel assemblies in the core and sometimes a reduced fuel height. To assess the impact of such scale change in core design on fuel cycle cost and spent fuel volume, a scoping analysis tool is developed based on infinite lattice calculations, leakage, fuel management reduced models, and levelized unit cost of electricity (LCOE) estimate. As such, cost dynamics driven by fuel specific power, burnup, core leakage, feed, cycle length, fuel assembly height as well as uranium market data are captured with consistent set of assumptions and analysis methods. A selection of 5 reactor designs representative of leading PWR developers is assessed and compared. Pursuing higher specific powers and optimal burnups are highlighted as the main fuel cost reduction drivers, nevertheless, practical limitations and opportunities must be evaluated to establish the feasibility of such enhanced fuel operation. In consequence, a detailed core design is performed using SIMULATE3 code for 5 PWR variations including natural and forced coolant circulation modes, two reactor scales, power densities of 73, 112, and 123 kW/l and higher discharge burnups. Design and optimization are performed at the lattice level, for the reflector, and at the core loading level. Satisfactory steady-state operation including power distribution, coolant operating limits, and reactivity requirements are analyzed and reported in this paper. The fuel economics of the detailed core designs confirm the scoping analysis findings. Despite the unlocked power uprates in small PWRs, the achievable burnup for a given fuel specific power requires more enrichment and shorter fuel height results in higher fabrication costs per mass of fuel, which makes scaling down core size a more expensive endeavor on the fuel cycle front. Spent fuel volumes are reported for the PWRs designed in this paper. Furthermore, these volumes are driven by the core average discharge burnup regardless of the scale in consideration. Additional cost and core performance aspects related to heavy reflector gains, fuel-reflector substitution, and disposal cost policy in the U.S. are examined.

42 ENGINEERING↗
DOE OSTI2017

Python in the NERSC Exascale Science Applications Program for Data

We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codes vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices

Ronaghi, Zahra↗
DOE OSTI2022

Framework for Optimization, Quantification of Uncertainty and Surrogates – Updated Capabilities

This poster presents updated capabilities within the FOQUS Toolset, covering core features as well as project-based applications. Specifically, the poster highlights advancements in FOQUS integration with cloud-based clients, plugin support for machine learning tools and external simulations, sequential design of experiments, and advanced support for dynamic process models. The applications demonstrate the breadth of FOQUS predictive capabilities for chemical, energy and economic system analysis.

Paul, Brandon↗
DOE OSTI2026

Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers (Final Technical Report)

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB) and GTI Energy (GTI) for award “DE-FE0031969: Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers” sponsored by the U.S. Department of Energy (DOE). The objective of this project is to develop an innovative sorbent structure of trapped small amines in HNC embedded in PEF for DAC. This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An innovative sorbent structure of trapped small amines in hierarchical nanoporous capsules (HNC) embedded in porous electrospun fibers (PEF) was developed for direct air capture (DAC). This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An interfacial polymerization process was developed, which utilized loaded amines inside mesoporous silica and trimesoyl chloride (TMC) dissolved in organic solvents as the precursors, to generate a polyamide (PA) coating layer on mesoporous silica and thus trap amines. Reaction conditions, including TMC concentration, organic solvents, reaction time, etc., for interfacial polymerization were optimized to effectively trap loaded amines, and cyclic heating-cooling operation was conducted to evaluate the coating quality. Larger pore volume mesoporous silica was also synthesized to increase amine loading and thus increase CO 2 capacity. The optimized sorbent material exhibited CO 2 capacity as high as 4.88 mmol/g under humid DAC conditions and negligible loss (<1%) during 10 cyclic heating-cooling operations. The optimized PA-coated sorbent also showed fast adsorption and desorption kinetics, with <20% t1/2 increase compared to uncoated sorbent. PEF fabrication conditions, including organic solvents for dissolving core and shell polymers, voltage, distance from the nozzle to the collection panel, etc. were adjusted to better incorporate HNC. After incorporating the optimized sorbent material into PEF, the structured sorbent had a CO 2 capacity of approximately 4.0 mmol/g under humid DAC conditions, with capacity loss of 0.17% per cycle and t1/2 increase less than 10%. A techno-economic analysis (TEA) for the process design for a DAC system based on our developed sorbent structure of trapped small amines in HNC embedded in PEF was conducted. The process design included process description and major equipment sizing and energy and mass balances in addition to scale-up research results and estimated capture cost. Aspen Adsorption Simulator was used to fit the experimentally measured breakthrough curves and extract equilibrium and kinetic data of the optimized sorbent. Our results indicated that for a DAC plant with CO 2 productivity of 3,000 tonne/year, the levelized cost of CO 2 capture was $\$$612/tonne, with the largest contribution of 44.33% from the fixed operation cost. Increasing CO 2 productivity, while maintaining similar fixed operation cost, is expected to significantly reduce the CO 2 capture cost. A sensitivity study was also conducted to understand the influence of total plant cost, sorbent cost, CO 2 concentration in the feed, sorbent mat lifetime, sorbent regeneration electricity, and adsorption blower pressure drop on the levelized cost of CO 2 capture, revealing a capture cost range of $\$$520-870/tonne.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology↗
DOE OSTI2021

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. Furthermore, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Collaborative Research: Improved Efficiency and Coupling of the Radiation Code in the ACME Earth System Model. Final Report

This final report details all work performed on the project by both project partners. This project provided support to properly couple RTE+RRTMGP, a high-performance broadband radiation code, within DOE’s Energy Exascale Earth System Model (E3SM). RTE+RRTMGP is a successor to the RRTMG radiation code, which has been widely accepted for its speed and accuracy by the global modeling community, and has been in use in the NCAR CESM for many years and was implemented in the initial version of E3SM. However, the computational cost of RRTMG remains high relative to other components in part due to its complexity and to its inefficient use of modern optimization strategies, issues that were rectified by the development of RTE+RRTMGP. Many of the accomplishment in this project necessitated significant collaboration with the E3SM development team. One focus of the project was to enhance the code’s optimization on the limited number of emerging computing systems on which the model is expected be used, including Many Integrated Core (MIC) architectures and Graphics Processing Unit (GPU) hardware. We also developed additional capabilities for RTE+RRTMGP that E3SM scientists identified as important for the planned applications of the model. The result of our project was optimization of a key physical component (radiative transfer calculations) of E3SM, directly supporting E3SM’s overarching global modeling objectives. More broadly, this project provided overall advancements in the use of radiative transfer calculations in atmospheric modeling and simulation, particularly for climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

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

Maximizing the Catalytic Performance of Pd@Au x Pd 1- x Nanocubes in H 2 O 2 Production by Reducing Shell Thickness to Increase Compositional Stability

We report a simple route based upon seed-mediated growth to the synthesis of Pd@Au x Pd 1-x (0.8≤x≤1) core–shell nanocubes. Benefiting from the well-defined {100} facets and an optimal Au/Pd ratio for the surface, the nanocubes bearing a shell made of Au 0.95 Pd 0.05 work as an efficient electrocatalyst toward H 2 O 2 production, with high selectivity of 93–100 % in the low-overpotential region of 0.4–0.7 V. When the Au 0.95 Pd 0.05 alloy is confined to a shell of only three atomic layers in thickness, the electrocatalyst is able to maintain its surface structure and elemental composition, endowing continuous and stable production of H2O2 during oxygen reduction at a high rate of 1.62 mol g( Pd+Au ) -1 h -1 . This work demonstrates a versatile route to the rational development of active and durable electrocatalysts based upon alloy nanocrystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Transport and spatial energy deposition of relativistic electrons in copper-doped fast ignition plasmas

Fast electron transport and spatial energy deposition are investigated in integrated cone-guided Fast Ignition experiments by measuring fast electron induced copper K-shell emission using a copper tracer added to deuterated plastic shells with a geometrically reentrant gold cone. Experiments were carried out at the Laboratory for Laser Energetics on the OMEGA/OMEGA-EP Laser where the plastic shells were imploded using 54 of the 60 OMEGA60 beams (3ω, 20 kJ), while the high intensity OMEGA-EP (BL2) beam (1 ω, 10 ps, 500 J, I peak > 10 19 W/cm 2 ) was focused onto the inner cone tip. Here, a retrograde analysis using the hybrid-PIC electron transport code, ZUMA, is performed to examine the sensitivity of the copper Kα spatial profile on the laser-produced fast electrons, facilitating the optimization of new target point designs and laser configurations to improve the compressed core areal density by a factor of 4 and the fast electron energy coupling by a factor of 3.5.

42 ENGINEERING↗
DOE OSTI2017

Search for excited states in O 25

Theoretical calculations suggest the presence of low-lying excited states in 25 O. Previous experimental searches by means of proton knockout on 26 F produced no evidence for such excitations. We search for excited states in 25 O using the 24 O(d,p) 25 O reaction. The theoretical analysis of excited states in unbound 25,27 O is based on the configuration interaction approach that accounts for couplings to the scattering continuum. We use invariant-mass spectroscopy to measure neutron-unbound states in 25 O. For the theoretical approach, we use the complex-energy Gamow Shell Model and Density Matrix Renormalization Group method with a finite-range two-body interaction optimized to the bound states and resonances of 23–26 O, assuming a core of 22 O. Here we predict energies, decay widths, and asymptotic normalization coefficients. Our calculations in a large spdf space predict several low-lying excited states in 25 O of positive and negative parity, and we obtain an experimental limit on the relative cross section of a possible J π = 1/2 + state with respect to the ground state of 25 O at σ 1/2+ /σ g.s. = 0.25$^{+1.0}_{-0.25}$. We also discuss how the observation of negative parity states in 25 O could guide the search for the low-lying negative parity states in 27 O. Previous experiments based on the proton knockout of 26 F suffered from the low cross sections for the population of excited states in 25 O because of low spectroscopic factors. In this respect, neutron transfer reactions carry more promise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A detailed study of CO 2 -brine capillary trapping mechanisms as applied to geologic carbon storage. Final Report

The proposed research focuses on improved fundamental understanding of the efficiency of physical trapping mechanisms, and as such will provide the basis for subsequent upscaling efforts. The overarching hypothesis of the proposed research is that capillary pressure plays a significant role in capillary trapping of CO 2 , especially during the water imbibition stage of the sequestration process. We posit that the relevant physics of the sequestration process is more complex than is currently captured in relative permeability models, which are often based on so-called trapping models to represent relative permeability hysteresis. Our 4 main questions, guiding the 4 main tasks of the proposed research, are as follows: (1) What is the morphology of capillary trapped CO 2 at the pore scale as a function of temperature, pressure, brine concentration, interfacial tension, and pore-space morphology under injection and subsequent imbibition? (2) Is it possible to describe the capillary trapping process using formation-dependent, but otherwise unique continuum-scale functions in permeability-capillary pressure, interfacial area and saturation space, rather than hysteretic functions in permeability-saturation or capillary pressure-saturation space? (3) How do continuum-scale relationships between kr-Pc-S-Anw developed based on pore-scale observations compare with traditional models incorporating relative permeability hysteresis (such as Land’s and other models,) and with observations at the core (5-10cm) scale? (4) How can trapped CO 2 volume be optimized via engineered injection and sweep strategies, and as a function of formation type (incl. heterogeneity)?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SPND Sensitivity Calculations Using MCNP and Experimental Data from ACRR

The use of the Monte Carlo N-Particle Transport Code (MCNP) to calculate detector sensitivity for Self-Powered Neutron Detectors (SPNDs) in the Annular Core Research Reactor (ACRR) could be a vital tool in the effort to optimize the design of next-generation SPNDs. Next-generation SPND designs, which consider specific materials and geometry, may provide experimenters with capabilities for advanced mixed field dosimetry. These detectors will need to be optimized for configuration, materials, and geometries and the ability to model and iterate must be available in order to decide on the ideal. SPND design. SPNDs were modeled in MCNP which closely resembled the dimensions and location of actual detectors used in the ACRR. Tallies were used to calculate detector sensitivity. Using metrics from a previous report, oscilloscope data from pulses were manipulated in a Matrix Laboratory computing environment (MATLAB) script to calculate experimental detector sensitivity. This report outlines the process in which experimental data from ACRR pulses verified results from tallies in an MCNP ACRR model. The sensitivity values from experiments and MCNP calculations agreed within one standard deviation. Parametric studies were also performed with MCNP to investigate the effects of materials and dimensions of different SPNDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Real-Time Monitoring of Temperature Rises of Energized Transformer Cores With Distributed Optical Fiber Sensors

Real-time temperature mapping that solves local overheating problems is important for obtaining an optimized thermal design for high-efficiency power transformers. Internal temperature monitoring of operating power transformers can also be leveraged for asset monitoring applications targeting at fault detection enabling condition-based maintenance. Transformers present a variety of challenging sensing environments such as high levels of electromagnetic interference and limited space for conventional sensors to operate. Immersion of power transformers in insulation oils for thermal management during operation and the presence of relatively large and time-varying electrical and occasional magnetic fields make sensing technologies requiring electrical wires or active power at sensing locations highly undesirable. In this work, we investigate thermal response of a standard telecom fiber instrumented on compact transformer cores by using an optical frequency-domain reflectometry scheme. As a result, correlation between conventional temperature sensing methods and fiber-optic sensing results as well as tradeoffs between spatial resolution and temperature measurement accuracy is discussed and spatially resolved real-time monitoring of temperatures in energized transformers is experimentally demonstrated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Formation and mechanism of nanocrystalline AZ91 powders during HDDR processing

Grain sizes of AZ91 alloy powders were markedly refined to about 15 nm from 100 to 160 μm by an optimized hydrogenation-disproportionation-desorption-recombination (HDDR) process. The effect of temperature, hydrogen pressure and processing time on phase and microstructure evolution of AZ91 alloy powders during HDDR process was investigated systematically by X-ray diffraction, optical microscopy, scanning electron microscopy and transmission electron microscopy, respectively. The optimal HDDR process for preparing nanocrystalline Mg alloy powders is hydriding at temperature of 350 °C under 4 MPa hydrogen pressure for 12 h and dehydriding at 350 °C for 3 h in vacuum. A modified unreacted core model was introduced to describe the mechanism of grain refinement of during HDDR process. - Highlights: • Grain size of the AZ91 alloy powders was significantly refined from 100 μm to 15 nm. • The optimal HDDR technology for nano Mg alloy powders is obtained. • A modified unreacted core model of grain refinement mechanism was proposed.

36 MATERIALS SCIENCE↗