Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Casting Modeling Simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Predicting Metallic Defects in Casting BrA9ZhZL Alloy Tool Electrodes

A method is proposed for modeling the lost-wax casting of tool electrodes by means of fusible BrA9ZhZL copper-based alloy. The functionality of the casting system is analyzed. The heating and cooling of a ceramic mold is taken into account in visualizing the temperature fields. Sections where shrinkage pores may form in the casting are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On the Correspondence Between Atmosphere-Only and Coupled Simulations for Radiative Feedbacks and Forcing From CO 2

Atmosphere-only experiments are widely used to investigate climate feedbacks simulated in more computationally expensive fully coupled global climate model simulations. We confirm that this remains a valid approach by comparing the radiative feedbacks and forcing between coupled and atmosphere-only simulations for the latest models taking part in the 6th phase of the Coupled Model Intercomparison Project (CMIP6). For global-mean cloud feedbacks, we find a better than previously known correspondence between these experiments, which applies even to the response of individual cloud properties (amount, altitude, and optical depth) and holds even when considering atmosphere-only simulations of only 1 yr duration. For regional cloud feedbacks, the correspondence between the two experiments is generally present at every geographic location except for the tropical Pacific but takes longer experiments to reveal. For the lapse rate and surface albedo feedbacks, the correspondence between the two experiments is weaker due to the non-uniform warming pattern and loss of sea ice in the coupled experiment. For the across-model relationship between 4xCO 2 effective radiative forcing and feedback, we find a different behavior across experiments in CMIP6 than in CMIP5, casting doubt on the physical significance of previous results that highlighted an anti-correlation between the two quantities. Overall, these results confirm the utility of atmosphere-only experiments particularly to study cloud feedbacks, which are the dominant source of inter-model spread in climate sensitivity.

58 GEOSCIENCES↗
DOE OSTI2016

Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting

Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind fore-casting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.

17 WIND ENERGY↗
DOE OSTI2017

Synchrotron measurements of local microstructure and residual strains in ductile cast iron

The local microstructure and distribution of thermally induced residual strains in ferrite matrix grains around an individual spherical graphite nodule in ductile cast iron (DCI) were measured using a synchrotron X-ray micro-diffraction technique. It is found that the matrix grains are deformed, containing dislocations and dislocation boundaries. Each of the residual strain components in the matrix grains exhibits a complex pattern along the circumferential direction of the nodule. Along the radial direction of the nodule, strain gradients from the interface to the grain interior are seen for some strain components, but only in some matrix grains. The observed residual strain patterns have been analysed by finite element modelling, and a comparison between the simulation and experiments is given. The present study of local residual stress by both experimental characterization and simulation provide much needed information for understanding the mechanical properties of DCI, and represent an important contribution for the microstructural design of new DCI materials.

Zhang, Y B↗
DOE OSTI2014

The magnetic flywheel flow meter: Theoretical and experimental contributions

The development of contactless flow meters is an important issue for monitoring and controlling of processes in different application fields, like metallurgy, liquid metal casting, or cooling systems for nuclear reactors and transmutation machines. Shercliff described in his book “The Theory of Electromagnetic Flow Measurement, Cambridge University Press, 1962” a simple and robust device for contact-less measurements of liquid metal flow rates which is known as magnetic flywheel. The sensor consists of several permanent magnets attached on a rotatable soft iron plate. This arrangement will be placed closely to the liquid metal flow to be measured, so that the field of the permanent magnets penetrates into the fluid volume. The flywheel will be accelerated by a Lorentz force arising from the interaction between the magnetic field and the moving liquid. Steady rotation rates of the flywheel can be taken as a measure for the mean flow rate inside the fluid channel. The present paper provides a detailed theoretical description of the sensor in order to gain a better insight into the functional principle of the magnetic flywheel. Theoretical predictions are confirmed by corresponding laboratory experiments. For that purpose, a laboratory model of such a flow meter was built and tested on a GaInSn-loop under various test conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Combining RAVEN, RELAP5-3D, and PHISICS for Fuel Cycle and Core Design Analysis for New Cladding Criteria

The Nuclear Regulatory Commission (NRC) has considered revision of 10 CFR 50.46C rule to account for the effects of burn-up rate in future analysis of reactor accident scenarios so that safety margins may evolve with the operation and reloading of the reactor as dynamic limits. In order to find these limiting conditions, both cladding oxidation and maximum temperature must be cast as functions of fuel exposure. It is computationally intensive to run a plant model through a long duration operational transient to the time of fuel reload, and this must be repeated for each reload until the time of the accident scenario. Moreover, fuel reload patterns may differ in many ways so that calculations with many different core configurations must be considered. To perform such new analyses in a reasonable amount of computational time with good accuracy, Idaho National Laboratory (INL) has developed new multi-physics tools by combining existing codes and adding new capabilities. The Parallel Highly Innovative Simulation INL Code System (PHISICS) toolkit for neutronic and reactor physics is coupled with the Reactor Excursion and Leak Analysis Program (RELAP5-3D) for the Loss of Coolant Accident (LOCA) analysis and RAVEN for the Probabilistic Risk Assessment (PRA) and margin characterization analysis. Expansion of code capability was also necessary. For RELAP5-3D to process a single sequence of cores in a continuous run required modification of RELAP5-3D to restart a sequence of input decks, each with a slightly modified neutronics model or thermal-hydraulic flow region and culminating in an accident scenario. A new multi-deck input processing capability was developed and verified for this analysis. In conclusion, the combined RAVEN/PHISICS/RELAP5-3D tool is used to analyze a typical Pressurized Water Reactor (PWR).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Melt-Pool Temperature and Size Measurement During Direct Laser Sintering

Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt pool in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.

42 ENGINEERING↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
DOE OSTI2014

Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

A multiscale linear-solver framework for the pressure equation associated with flow in highly heterogeneous porous formations was developed. The multiscale based approach is cast in a general algebraic form, which facilitates integration of the new scalable linear solver in existing flow simulators. The Algebraic Multiscale Solver (AMS) is employed as a preconditioner within a multi-stage strategy. The formulations investigated include the standard MultiScale Finite-Element (MSFE) andMultiScale Finite-Volume (MSFV) methods. The local-stage solvers include incomplete factorization and the so-called Correction Functions (CF) associated with the MSFV approach. Extensive testing of AMS, as an iterative linear solver, indicate excellent convergence rates and computational scalability. AMS compares favorably with advanced Algebraic MultiGrid (AMG) solvers for highly detailed three-dimensional heterogeneous models. Moreover, AMS is expected to be especially beneficial in solving time-dependent problems of coupled multiphase flow and transport in large-scale subsurface formations.

02 PETROLEUM↗
DOE OSTI2023

Dislocation Patterning in Deforming Crystals: Theory, Computational Predictions and Validation (Final Technical Report)

This project was awarded for an initial period of three years, followed by a no-cost extension for one year and a funded one-year renewal. During the first four years, the project focused on investigating the role of dislocation reactions and dislocation correlation in dislocation patterning in FCC metals. During the fifth year, the scope of research was expanded to investigate the effects of composition inhomogeneity on the mesoscale plastic response of Body-Centered Cubic (BCC) alloys. In addition to its impact on metal hardening during deformation, dislocation patterning provides the microstructure information required to understand phenomena like fracture and recrystallization in metals. The Continuum Dislocation Dynamics (CDD) framework was the methodology used during the first four years, followed by the use of Discrete Dislocation Dynamics (DDD) during the fifth year. CDD is a density-based formalism of dislocation dynamics in which the plastic deformation of crystals is predicted together with the mesoscale dislocation patterns by tracking the space-time evolution of dislocations as driven by the applied stress, short-range and long-range interactions of dislocations, and cross slip. CDD is a crystal mechanics approach in which the plastic constitutive part is replaced with the equations of dislocation dynamics, which is driven by the internal stress via a mobility laws, while the evolution of the density gives the eigenstrain required to update the internal stress itself. The governing equations are thus those of crystal mechanics cast as an eigenstrain problem and those of dislocation transport and reactions. Our investigations during the first four years were driven by the hypothesis that that dislocation patterning is triggered by spatiotemporal dislocation density and internal stress fluctuations, and that such fluctuations influence the collective dislocation dynamic through their effects on the short-range reaction rates and the collective dislocation mobility. This hypothesis was tested by modeling the influence of the dislocation reactions and dislocation correlations on collective dislocation dynamics. The main research components during the first four years were: 1) Reformulation of the CDD framework to integrate the dislocation correlations and dislocation reactions. 2) Simulation of the dislocation correlations and quantifying their contribution to the long-range stress of complex dislocation systems. 3) Computational implementation of the updated CDD model for FCC single crystals and development of an efficient CDD code. 4) Investigation of dislocation patterning in FCC crystals based on the updated CDD model. Some key findings from these investigations were: 1) The patterning of dislocations is initiated by cross slip and internal stress fluctuations, and the refinement of the pattern results from junction formation. 2) Patterning is more prominent under high stress. 3) The correlation stress was found to be a significant part of the mean field stress in continuum representations of dislocation dynamics. During the last year of the project, we have established a method for performing dislocation dynamics in inhomogeneous alloys and demonstrated the impact of composition inhomogeneity on the characteristics of initial yielding and dislocation character in BCC alloys. We also tested this method using an irradiated ferritic alloy in which the composition and dislocation loops effects are both present. In doing so, we have considered two aspects of the role of inhomogeneity, the creation of internal coherency stress due to the dependence of the lattice parameter on the local composition, and the dependence of the dislocation mobility on the local composition. These two aspects resulted in an unexpected behavior of the dislocation system, and, in turn, the yielding behavior of BCC alloys. Key findings include: 1) The composition inhomogeneity in BCC alloys alters the well-known role of screw dislocations by forcing a level of waviness on the average dislocation character, thus destroying the screw character dominance in the yielding observed in pure or homogeneous BCC metals. 2) In the case of irradiated alloys, while composition inhomogeneity by itself and dislocation loops by themselves result in some hardening, the superposition of the two mechanisms does not result in the sum of the two contributions via any known rule. The latter result contradicts the classical works related hardening via multiple mechanisms, which state that various hardening mechanisms can be added linearly or using some Pythagorean additive rule. We were able to rationalize this unexpected result by a closer loop at the origin of the hardening mechanisms themselves, which both involved long-range elastic interactions with dislocations. We reached the conclusion that the hardening resulting from the total stress associated with these two mechanisms (current work) differs from the sum of the effects of the individual stress fields (classical literature). We have also found a major flaw in the classical theory of spinodal hardening. The latter theory never considered the impact of composition undulation on the solute hardening. We have built a new general theory accounting for the effect of solute friction together with the composition undulations on the dislocation configuration at Critical Resolved Shear Stress (CRSS), which is yielding a new definition of the spinodal hardening and new different results. This work is the first to recognize the lack of the role of solute in spinodal hardening theory of alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

The final-parsec problem in nonspherical galaxies revisited

We consider the evolution of supermassive black hole binaries at the center of spherical, axisymmetric, and triaxial galaxies, using direct N-body integrations as well as analytic estimates. We find that the rates of binary hardening exhibit a significant N-dependence in all the models, at least for N in the investigated range of 10{sup 5} ≤ N ≤ 10{sup 6}. Binary hardening rates are also substantially lower than would be expected if the binary 'loss cone' remained 'full', as it would be if the orbits supplying stars to the binary were being efficiently replenished. The difference in binary hardening rates between the spherical and nonspherical models is less than a factor of two even in the simulations with the largest N. By studying the orbital populations of our models, we conclude that the rate of supply of stars to the binary via draining of centrophilic orbits is indeed expected to be much lower than the full-loss-cone rate, consistent with our simulations. We argue that the binary's evolution in the simulations is driven in roughly equal amounts by collisional and collisionless effects, even at the highest N-values currently accessible. While binary hardening rates would probably reach a limiting value for large N, our results suggest that we cannot approach that rate with currently available algorithms and computing hardware. The extrapolation of results from N-body simulations to real galaxies is therefore not straightforward, casting doubt on recent claims that triaxiality or axisymmetry alone are capable of solving the final-parsec problem in gas-free galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

LLNL FESP Theory Highlights: October 2024

I. Novikau, I. Y. Dodin, E. A. Startsev, I. Joseph, Quantum algorithms for simulating dissipative linear and nonlinear dynamics of plasmas. Invited talk at the 66th Annual Meeting of the APS Division of Plasma Physics, Atlanta, Georgia. Novikau I., Dodin I.Y., Startsev E.A., Encoding of linear kinetic plasma problems in quantum circuits via data compression, Journal of Plasma Physics. 2024;90(4):805900401, doi:10.1017/S0022377824000795. We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation to be solved by using the quantum signal processing algorithm. The latter requires encoding of a matrix in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The Effect of Rolling As-Cast and Homogenized U-10Mo Samples on the Microstructure Development and Recovery Curves

Over the past several years Pacific Northwest National Laboratory (PNNL) has been actively involved in supporting the U.S. Department of Energy National Nuclear Security Administration Office of Material Management and Minimization (formerly Global Threat Reduction Initiative). The U.S. High- Power Research Reactor (USHPRR) project is developing alternatives to existing highly enriched uranium alloy fuel to reduce the proliferation threat. One option for a high-density metal fuel is uranium alloyed with 10 wt% molybdenum (U-10Mo). Forming the U-10Mo fuel plates/foils via rolling is an effective technique and is actively being pursued as part of the baseline manufacturing process. The processing of these fuel plates requires systematic investigation/understanding of the pre- and post-rolling microstructure, end-state mechanical properties, residual stresses, and defects, their effect on the mill during processing, and eventually, their in-reactor performance. In the work documented herein, studies were conducted to determine the effect of cold and hot rolling the as-cast and homogenized U-10Mo on its microstructure and hardness. The samples were homogenized at 900°C for 48 h, then later annealed for several durations and temperatures to investigate the effect on the material’s microstructure and hardness. The rolling of the as-cast plate, both hot and cold, was observed to form a molybdenum-rich and -lean banded structure. The cold rolling was ineffective, and in some cases exacerbated the as-cast defects. The grains elongated along the rolling direction and formed a pancake shape, while the carbides fractured perpendicularly to the rolling direction and left porosity between fractured particles of UC. The subsequent annealing of these samples at sub-eutectoid temperatures led to rapid precipitation of the ' lamellar phase, mainly in the molybdenum-lean regions. Annealing the samples above the eutectoid temperature did not refine the grain size or the banded microstructure. However, annealing the samples led to quick recovery in hardness as evidenced by a drop in Vickers hardness of 20%. Hot rolling was performed at 650 and 800°C. The hot-rolling mill loads (load separation force) were approximately 40 to 50% less than the cold-rolling for the same reduction and thickness. It was observed that hot rolling the samples with 50% or more reduction in thickness were responsible for dynamic recrystallization in the hot-rolled samples and led to grain refinement. Unlike the cold-rolled samples, the hot-rolled samples did not fracture the carbides and appeared to heal the casting defects. The recovery phenomenon was similar to the cold-rolled samples above the eutectoid temperatures, but owing to the refined grain size, the precipitation of the lamellar phase was far more rapid in these samples and the hardness increased more rapidly than in the cold rolled sample when heated below the eutectoid temperature. The data generated from these rolling efforts has been used to make the process modeling efforts more robust and applicable to all USHPRR partner rolling mills. The flow stress for cold rolling the samples was determined to be between 170-190 ksi, with frictional forces between 0.2 and 0.4 for the PNNL mill. The measured roll separation forces and those simulated using finite element methods for hot and cold rolling for the PNNL rolling mill were in good agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The Effect of Rolling As-Cast and Homogenized U-10Mo Samples on the Microstructure Development and Recovery Curves

Over the past several years Pacific Northwest National Laboratory (PNNL) has been actively involved in supporting the U.S. Department of Energy National Nuclear Security Administration Office of Material Management and Minimization (formerly Global Threat Reduction Initiative). The U.S. High-Power Research Reactor (USHPRR) project is developing alternatives to existing highly enriched uranium alloy fuel to reduce the proliferation threat. One option for a high-density metal fuel is uranium alloyed with 10 wt% molybdenum (U-10Mo). Forming the U-10Mo fuel plates/foils via rolling is an effective technique and is actively being pursued as part of the baseline manufacturing process. The processing of these fuel plates requires systematic investigation/understanding of the pre- and post-rolling microstructure, end-state mechanical properties, residual stresses, and defects, their effect on the mill during processing, and eventually, their in-reactor performance. In the work documented herein, studies were conducted to determine the effect of cold and hot rolling the as-cast and homogenized U-10Mo on its microstructure and hardness. The samples were homogenized at 900°C for 48 h, then later annealed for several durations and temperatures to investigate the effect on the material’s microstructure and hardness. The rolling of the as-cast plate, both hot and cold, was observed to form a molybdenum-rich and -lean banded structure. The cold rolling was ineffective, and in some cases exacerbated the as-cast defects. The grains elongated along the rolling direction and formed a pancake shape, while the carbides fractured perpendicularly to the rolling direction and left porosity between fractured particles of UC. The subsequent annealing of these samples at sub-eutectoid temperatures led to rapid precipitation of the α + γ ' lamellar phase, mainly in the molybdenum-lean regions. Annealing the samples above the eutectoid temperature did not refine the grain size or the banded microstructure. However, annealing the samples led to quick recovery in hardness as evidenced by a drop in Vickers hardness of 20%. Hot rolling was performed at 650 and 800°C. The hot-rolling mill loads (load separation force) were approximately 40 to 50% less than the cold-rolling for the same reduction and thickness. It was observed that hot rolling the samples with 50% or more reduction in thickness were responsible for dynamic recrystallization in the hot-rolled samples and led to grain refinement. Unlike the cold-rolled samples, the hot-rolled samples did not fracture the carbides and appeared to heal the casting defects. The recovery phenomenon was similar to the cold-rolled samples above the eutectoid temperatures, but owing to the refined grain size, the precipitation of the lamellar phase was far more rapid in these samples and the hardness increased more rapidly than in the cold rolled sample when heated below the eutectoid temperature. The data generated from these rolling efforts has been used to make the process modeling efforts more robust and applicable to all USHPRR partner rolling mills. The flow stress for cold rolling the samples was determined to be between 170-190 ksi, with frictional forces between 0.2 and 0.4 for the PNNL mill. The measured roll separation forces and those simulated using finite element methods for hot and cold rolling for the PNNL rolling mill were in good agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Characterization of atomic-level structure in Fe-based amorphous and nanocrystalline alloy by experimental and modeling methods

The atomic structure of Fe{sub 70}Nb{sub 10}B{sub 20} alloy in “as-cast” state and after annealing was investigated using high-energy X-ray diffraction (XRD), Mössbauer spectroscopy (MS) and high resolution transmission electron microscopy (HRTEM). The HRTEM observations allowed to indicate some medium-range order (MRO) regions about 2 nm in size and formation of some kinds of short-range order (SRO) structures represented by atomic clusters with diameter ca. 0.5 nm. The Reverse Monte Carlo (RMC) method basing on the results of XRD measurements was used in modeling the atomic structure of Fe-based alloy. The structural model was described by peak values of partial pair correlation functions and coordination numbers determined by Mössbauer spectroscopy investigations. The three-dimensional configuration box of atoms was obtained from the RMC simulation and the representative Fe-centered clusters were taken from the calculated structure. According to the Gonser et al. approach, the measured spectra of alloy studied were decomposed into 5 subspectra representing average Fe–Fe coordination numbers. Basing on the results of disaccommodation of magnetic permeability, which is sensitive to the short order of the random packing of atoms, it was stated that an occurrence of free volume is not detected after nanocrystallization process. - Highlights: • Atomic cluster model of amorphous structure was proposed for studied glassy alloy. • Short range order (ca. 0.5 nm) regions interpreted as clusters were identified by HREM. • Clusters correspond to coordination numbers (N = 4,6,8,9) calculated by using Gonser approach. • Medium-range order (ca. 2 nm) could be referred to few atomic clusters. • SRO regions are able to grow up as nuclei of crystalline bcc Fe and iron borides. • Crystalline particles have spherical morphology with an average diameter of 20 nm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

New superconducting toroidal magnet system for IAXO, the international AXion observatory

Axions are hypothetical particles that were postulated to solve one of the puzzles arising in the standard model of particle physics, namely the strong CP (Charge conjugation and Parity) problem. The new International AXion Observatory (IAXO) will incorporate the most promising solar axions detector to date, which is designed to enhance the sensitivity to the axion-photon coupling by one order of magnitude beyond the limits of the current state-of-the-art detector, the CERN Axion Solar Telescope (CAST). The IAXO detector relies on a high-magnetic field distributed over a very large volume to convert solar axions into X-ray photons. Inspired by the successful realization of the ATLAS barrel and end-cap toroids, a very large superconducting toroid is currently designed at CERN to provide the required magnetic field. This toroid will comprise eight, one meter wide and twenty one meter long, racetrack coils. The system is sized 5.2 m in diameter and 25 m in length. Its peak magnetic field is 5.4 T with a stored energy of 500 MJ. The magnetic field optimization process to arrive at maximum detector yield is described. In addition, materials selection and their structure and sizing has been determined by force and stress calculations. Thermal loads are estimated to size the necessary cryogenic power and the concept of a forced flow supercritical helium based cryogenic system is given. A quench simulation confirmed the quench protection scheme.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗