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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A simplified regression building thermal modelling method for detached two-floor house in U.S.

The residential building sector accounts for approximately 37% of total U.S. electricity consumption. Within the residential building sector, heating and cooling is the main target for peak load shifting/reduction since it is the largest contributor to peak demand. In fact, the flexibility of residential HVAC loads can provide continuous variation of demand to provide grid services by varying their demand over a baseline. The performance of HVAC load control to provide grid services relies heavily on the accuracy of indoor air temperature or cooling/heating demand predictions and therefore the quality of building model. Besides forward models, popular building models are data-driven models which can be broken down into two categories: gray-box model, e.g. Resistance-Capacitance (RC) model and black-box model. RC model, also called lumped capacitance or network model, which is constituted with electrical analogue pattern with resistance (R) and capacitance (C). In general, RC models require considerable computation burden and long periods of data to train limited number of model coefficients. Black-box models have gained increasing interest due to their capability in analyzing large-scale data and flexibility in practical applications. But, the data-mining based (machine learning algorithms/techniques based) models tend to have invisible model structures which poses a problem when trying to use the model for optimal control or model predictive control of the HVAC system. Hence, there is a continuing need for efficient online system identification techniques, which can provide explicit parameters for the model. Traditional regression models fit well for this specific purpose. This paper presents an innovative way to predict average indoor temperature in separate floors of typical detached residential house. A rolling horizon linear regression model, which includes online adaptive correction component, is proposed to predict the temperature difference between downstairs and upstairs. A RC model is used to predict the overall mean indoor air temperature. Since the adaptive algorithm needs to be implemented online, a less computation-demanding polynomial fitting algorithm is adopted. This kind of fitting problem can be cast as linear regression problem with multiple variables, parameters of which can be efficiently obtained by well-known gradient descent method.The validation is conducted by comparing the predicted results with the results from data-mining based models as well as measured data from a real typical detached two-floor house. The results show that the developed method has satisfactory performance in predicting the building indoor temperature in 1st and 2nd floors.

Cui, Borui↗
DOE OSTI2012

Modeling and Characterization of Dynamic Failure of Soda-lime Glass Under High Speed Impact

In this paper, the impact-induced dynamic failure of a soda-lime glass block is studied using an integrated experimental/analytical approach. The Split Hopkinson Pressure Bar (SHPB) technique is used to conduct dynamic failure test of soda-lime glass first. The damage growth patterns and stress histories are reported for various glass specimen designs. Making use of a continuum damage mechanics (CDM)-based constitutive model, the initial failure and subsequent stiffness reduction of glass are simulated and investigated. Explicit finite element analyses are used to simulate the glass specimen impact event. A maximum shear stress-based damage evolution law is used in describing the glass damage process under combined compression/shear loading. The impact test results are used to quantify the critical shear stress for the soda-lime glass under examination.

glass, brittle failure, failure strength, damage m↗
DOE OSTI2017

Partnership for Edge Physics Simulation

A major goal of our participation in the Edge Physics Simulation project has been to contribute to the understanding of the self-organization of tokamak turbulence fluctuations resulting in the formation of a staircase structure in the ion temperature. A second important goal is to demonstrate how small scale turbulence in plasmas self-organizes with dynamically driven quasi-stationary flow shear. These goals have been accomplished through the analyses of the statistical properties of XGC1 flux driven Gyrokinetic electrostatic ion temperature gradient (ITG) turbulence simulation data in which neutrals are included. The ITG turbulence data, and in particular fluctuation data, were obtained from a massively parallel flux-driven gyrokinetic full-f particle-in-cell simulation of a DIII-D like equilibrium. Below some the findings are summarized. It was observed that the emergence of staircase structure is related to the variations in the normalized temperature gradient length (R/LT) and the poloidal flow shear. Average turbulence intensity is found to be large in the vicinity of minima in R/LTi, where ITG growth is expected to be lower. The distributions of the occurrences of potential fluctuation are found to be Gaussian away from the staircase-step locations, but they are found to be non-Gaussian in the vicinity of staircase-step locations. The results of analytically derived expressions for the distribution of the occurrences of turbulence intensity and intensity flux were compared with the corresponding quantities computed using XGC1 simulation data and good agreement is found. The derived expressions predicts inward and outward propagation of turbulence intensity flux in an intermittent fashion. The outward propagation of turbulence intensity flux occurs at staircase-step locations and is related to the change in poloidal flow velocity shear and to the change in the ion temperature gradient. The standard deviation, skewness and kurtosis for turbulence quantities were computed and found to be large in the vicinity of the staircase-step structures. Large values of skewness and kurtosis can be explained by a temporary opening and closing of the structure which allows turbulence intensity events to propagate. The staircase patterns may reduce the ion heat transport and a manipulation of these patterns may be used to optimize heat transport in tokamaks. An additional objective of the research in support of the Edge Physics Simulation initiative has been to improve the understanding of scrape-off layer thermal transport. In planning experiments and designing future tokamaks, it is important to understand the physical effects that contribute to divertor heat-load fluxes. The research accomplished will contribute to developing new models for the scrape-off layer region. The XGC0 code was used to compute the heat fluxes and the heat-load width in the outer divertor plates of C-Mod and DIII-D tokamaks. It was observed that the width of the XGC0 neoclassical heat-load was approximately inversely proportional to the total plasma current. Anomalous transport in the H-mode pedestal region of five Alcator C-Mod discharges, representing a collisionality scan, was analyzed. The understanding of anomalous transport in the pedestal region is important for the development of a comprehensive model for the H-mode pedestal slope. It was found that the electron thermal anomalous diffusivities at the pedestal top increase with the electron collisionality. This dependence can point to the DRIBM as the modes that drive the anomalous transport in the plasma edge of highly collisional discharges. The effects of plasma shaping on the H-mode pedestal structure was also investigated. The differences in the predicted H-mode pedestal width and height for the DIII-D discharges with different elongation and triangularities were discussed. For the discharges with higher elongation, it was found that the gradients of the plasma profiles in the H-mode pedestal reach semi-steady states. In these simulations, the pedestal slowly continued to evolve to higher pedestal pressures and bootstrap currents until the peeling ballooning stability conditions were satisfied. The discharges with lower elongation do not reach the semi-steady state, and ELM crashes were triggered at earlier times. The plasma elongation was found to have a stronger stabilizing effect than the plasma triangularity. For the discharges with lower elongation and lower triangularity, the ELM frequency was large, and the H-mode pedestal evolves rapidly. It was found that the temperature of neutrals in the scrape-off-layer region can affect the dynamics of the H-mode pedestal buildup. However, the final pedestal profiles were nearly independent of the neutral temperature. The elongation and triangularity affected the pedestal widths of plasma density and electron temperature profiles differently. This study illustrated a new mechanism for controlling the pedestal bootstrap current and the pedestal stability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Modeling and Characterization of Dynamic Failure of Glasses Under High Speed Impact

: In this chapter, the impact-induced dynamic failure of a glass block is studied using an integrated experimental/analytical approach. Both soda-lime and borosilicate glass materials are investigated. The Split Hopkinson Pressure Bar (SHPB) technique is used to conduct dynamic failure test of soda-lime glass first. The damage growth patterns and stress histories are reported for various glass specimen designs. Making use of a continuum damage mechanics (CDM)-based constitutive model, the initial failure and subsequent stiffness reduction of glass are simulated and investigated. Explicit finite element analyses are used to simulate the glass specimen impact event. A maximum shear stress-based damage evolution law is used in describing the glass damage process under combined compression/shear loading. The impact test results are used to quantify the critical shear stress for the soda-lime glass under examination.

continuum damage mechanics model↗
DOE OSTI2015

Lattice Rotation Patterns and Strain Gradient Effects in Face-Centered-Cubic Single Crystals Under Spherical Indentation

Strain gradient effects are commonly modeled as the origin of the size dependence of material strength, such as the dependence of indentation hardness on contact depth and spherical indenter radius. However, studies on the microstructural comparisons of experiments and theories are limited. First, we have extended a strain gradient Mises-plasticity model to its crystal plasticity version and implemented a finite element method to simulate the load-displacement response and the lattice rotation field of Cu single crystals under spherical indentation. The strain gradient simulations demonstrate that the forming of distinct sectors of positive and negative angles in the lattice rotation field is governed primarily by the slip geometry and crystallographic orientations, depending only weakly on strain gradient effects, although hardness depends strongly on strain gradients. Second, the lattice rotation simulations are compared quantitatively with micron resolution, three-dimensional X-ray microscopy (3DXM) measurements of the lattice rotation fields under 100mN force, 100 mu m radius spherical indentations in < 111 >, < 110 >, and < 001 > oriented Cu single crystals. Third, noting the limitation of continuum strain gradient crystal plasticity models, two-dimensional discrete dislocation simulation results suggest that the hardness in the nanocontact regime is governed synergistically by a combination of strain gradients and source-limited plasticity. However, the lattice rotation field in the discrete dislocation simulations is found to be insensitive to these two factors but to depend critically on dislocation obstacle densities and strengths.

Gao, Y. F.↗
DOE OSTI2016

Analysis of Electric Vehicle Charging Impact on the Electric Power Grid

In order to evaluate the impact of electric vehicles (EVs) on the distribution grid and assess their potential benefits to the future smart grid, it is crucial to study the EV charging patterns and the usage charging station. Though EVs are not yet widely adopted nationwide, a valuable methodology to conduct such studies is the statistical analysis of real-world charging data. This paper presents actual EV charging behavior of 64 EVs (5 brands, 8 models) from EV users and charging stations at Los Angeles Department of Water and Power for more than one year. Twenty-four-hour EV charging load curves have been generated and studied for various load periods: daily, monthly, seasonally and yearly. Finally, the effect and impact of EV load on the California distribution network are evaluated at different EV penetration rates.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

3D Printed, Low Tortuosity Garnet Framework For Beyond 500 Wh/kg Batteries

In this project, we developed LLZO garnet ink recipes and processes for 3D-printing highly ordered ionically conductive garnet porous structures on dense garnet separators. Using this technique, we are able to fabricate controlled architecture LLZO garnet solid-state electrolyte (SSE) trilayers for application in solid-state lithium batteries. The trilayer comprises a thin dense center layer sandwiched between a 3D-printed patterned porous layer and a random porous layer. The dense layer functions as the ionic separator between the anode and cathode. The random porous layer hosts the lithium-metal anode and provides the structural support. The 3D-printed SSE patterned porous layer hosts the cathode, providing continuous, low tortuosity pathways for fast 3D Li+ transport through the cell while increasing the electrode/electrolyte interface area to decrease the interfacial resistance. Compared to the random porous structure, this ordered patterned structure possesses more vacant space for higher cathode loading without sacrificing ionically conducting capability, thus potentially greatly increasing the cell energy density. For demonstration purposes, we developed two patterns for the 3D-printed porous layer: grids and columns, for hosting sulfur and NMC cathode, respectively. The corresponding two types of cells were fabricated and tested, and have demonstrated achievement of theoretical discharge capacity without cathode calendaring. In addition, we developed a fundamental solid-state ionic and electronic transport model to optimize the 3D-printed structures for maximum energy and power density. The model was validated by experiment and provides the critical design criteria for achieving the >500 Wh/kg energy goal as function of C-rate.

25 ENERGY STORAGE↗
DOE OSTI2022

Modelling and Experimental Validation of Improved Performance of Lithium-Ion Batteries Having Thick Electrodes with Laser-Ablated Micro-Structures

For widespread adoption of electric vehicles, lithium-ion batteries (LiBs) need to achieve energy densities of >275 Wh/kg, cost less than $100/Wh, and charge to more than 80% capacity within 15 minutes. Increasing the battery electrode thicknesses is one way to increase cell energy densities while also saving on cell manufacturing cost by increasing the ratio of electrode active material to inactive material within each cell. However, increased electrode loading is often accompanied by decreased Li+-ion diffusion across the full thick electrodes. This leads to significant cell polarization that prevents full capacity utilization and accelerates cell degradation, especially at fast charging/discharging rates. The introduction of secondary pore networks in thick battery electrodes alleviates some of the trade-offs between energy and power performance. These microstructures provide low tortuosity pathways for facile Li+-ion diffusion deep into the thick electrodes, diminishing detrimental concentration gradients within the cell. Ultrafast-pulsed laser ablation is a promising method to introduce micro pores or channels in thick battery electrodes as it allows for precise control of pattern geometries, results in minimal damage to the electrode and can be introduced into existing roll-to-roll electrode manufacturing lines. Herein, the limitations of thick planer electrodes and the advanced predictive models to identify optimal electrode patterns for improved cycling performance will be presented. The impact of electrode laser patterning to create secondary pore networks also will be discussed. Materials characterization techniques (SEM-EDS, XRD) were used to explore the affect ultrafast laser ablation had on the electrode materials’ morphology and structure. The improvements in the patterned electrodes’ electrochemical cycling performances and degrees of wetting will be compared to a pristine baseline case. Finally, the discrepancies between experimentally obtained data and model predictions will be explained.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rendezvous algorithms for large-scale modeling and simulation

Rendezvous algorithms encode a communication pattern that is useful when processors sending data do not know who the receiving processors should be, or vice versa. The idea is to define an intermediate decomposition where datums from different sending processors can ”rendezvous” to perform a computation, in a manner that both the senders and eventual receivers of the results can identify the appropriate rendezvous processor. Though they were originally designed for interpolating between overlaid grids with independent parallel decompositions (Plimpton et al., 2004), we have recently found rendezvous algorithms useful for a variety of operations in particle- or grid-based simulation codes when running large problems on large numbers of processors. In particular, we show they can perform well when a load-balanced intermediate decomposition is randomized and not spatial, requiring all-to-all communication to move data between processors. In this case rendezvous algorithms leverage the large bisection communication bandwidths which parallel machines provide. We describe how rendezvous algorithms work in a scientific computing context and give specific examples for molecular dynamics and Direct Simulation Monte Carlo codes which result in dramatic performance improvements versus simpler algorithms which do not scale as well. We explain how a generic rendezvous algorithm can be implemented, and also point out similarities with the MapReduce paradigm popularized by Google and Hadoop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The Shifting Role of mRUE for Regulating Ecosystem Production

To design a comprehensive view of ecosystem resource use, in this work we integrated parallel resource use efficiency observations into a multiple-resource use efficiency (mRUE) framework using a dynamic factor analysis model. Results from 56 site-years of eddy covariance data and mRUE factors for a site in the US Midwest show temporal dynamics and coherence (using Pearson’s R) among resources are associated with interannual variation in precipitation. Loading factors are derived from mRUE observations and quantify how strongly data are connected to the underlying ecosystem state. Water and light resource use loading factors are coherent at annual timescales (Pearson’s R of 0.86), whereas declining patterns of carbon use efficiency loading factors highlight the ecosystem’s trade-off between carbon uptake and respiration during the growing season. At annual and monthly timescales, influence decreases from ~85 to ~65% for loading factors for carbon use, while influence of light use loading factors peaks to ~60% at growing season timescales. Quantifying variation in ecosystem function provides novel insights into the temporal dynamics of changing significance of multiple resources to ecosystem function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Using System Dynamics to Define, Study, and Implement Smart Control Strategies on the Electric Power Grid

The United States electric power grid is the most complex and expansive control system in the world. Local generation control occurs at individual units based on response time and unit economics, larger regional control coordinates unit response to error conditions, and high level large-area regional control is ultimately administered by a network of humans guided by economic and resiliency related factors. Under normal operating conditions, the grid is a relatively slow moving entity that exhibits high inertia to outside stimuli, and behaves along repeatable diurnal and seasonal patterns. However, that paradigm is quickly changing because of the increasing implementation of renewable generation sources. Renewable generators by nature cannot be tightly controlled or scheduled. They appear like a negative load to the system with all of the variability associated with load on a larger scale. Also, grid-reactive loads (i.e. smart devices) can alter their consumption based on price or demand rules adding more variability to system behavior. This paper demonstrates how a systems dynamic modeling approach capable of operating over multiple time scales, can provide valuable insight into developing new “smart-grid” control strategies and devices needed to accommodate renewable generation and regulate the frequency of the grid.

14 SOLAR ENERGY↗
DOE OSTI2021

Modelica-based system modeling for studying control-related faults in chiller plants and boiler plants serving large office buildings

System modeling is critical when studying operation faults in chiller plants and boiler plants. However, current fault models have difficulties faithfully representing the operation of chiller plants and boiler plants under the effects of those faults, especially the control-related ones. In this study, we present a systematic method to develop high-fidelity models for approximating the behaviors of chiller plants and boiler plants under faulty conditions. Compared to existing ones, the resulting fault models have two advantages: first, they better characterize the dynamic patterns in the system operation. In those models, control architecture and control logic are faithfully implemented. Thus, they can be used to study control-related faults, such as incorrect staging control due to sensor bias and mistuned feedback control. Second, they are readily extensible and can support large-scale investigations to explore different faulty conditions/scenarios. Those models are established in a hierarchical structure while modules in each layer can be redeclared and parameterized at upper layers. In such a case, modifications to the models can be realized through model modifiers and the process can be easily streamlined with scripts. We applied the proposed models in a comprehensive fault impact evaluation of the 13 control-related faults of chiller and boiler plants. In this evaluation, the proposed plant model is coupled with the EnergyPlus thermal load model to study the impact of various faulty scenarios. Based on the evaluation results, we identified the faults that have the most significant impacts on the operation of the chiller and boiler plants, respectively. We also found that the relationship between the impacts of the studied faults and the severity level of the faults are highly non-linear

Huang, Sen↗
DOE OSTI2018

Inferring Strength of Tantalum from Hydrodynamic Instability Recovery Experiments

Hydrodynamic instability experiments allow access to material properties at extreme conditions, where strain rates exceed 105 s -1 and pressures reach 100 GPa. Current hydrodynamic instability experimental methods require in-flight radiography to image the instability growth at high pressure and high strain rate, limiting the facilities where these experiments can be performed. An alternate approach, recovering the sample after loading, allows measurement of the instability growth with profilometry. Tantalum samples were manufactured with different 2D and 3D initial perturbation patterns and dynamically compressed by a blast wave generated by laser ablation. The samples were recovered from peak pressures between 30 and 120 GPa and strain rates on the order of 107 s -1 , providing a record of the growth of the perturbations due to hydrodynamic instability. These records are useful validation points for hydrocode simulations using models of material strength at high strain rate. Recovered tantalum samples were analyzed, providing an estimate of the strength of the material at high pressure and strain rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Fuel assembly design for APR1400 with low CBC

APR 1400 is a PWR (Pressurized Water Reactor) with rated power of 3983 MWth and 241 assemblies. Recently, demand for extremely longer cycle up to 24 months is increasing with challenge of higher critical boron concentration (CBC). In this paper, assembly design method of selecting Gd-rods is introduced to reduce CBC. The purpose of the method is to lower the critical boron concentration of the preliminary core loading pattern (PLP), and consequently to achieve more negative or less positive moderator temperature coefficient (MTC). In this method, both the ratio of the number of low-Gd rod to the number of high-Gd rod (r) and assembly average Gd wt% (w) are the decision variables. The target function is the amount of soluble boron concentration reduction, which can be converted to Δk{sub TARGET}. A set of new designed fuel assembly satisfies an objective function, min [f=∑{sub i}(Δk{sub FA}−Δk{sub i})], and enables a final loading pattern to reach a target CBC. The constraints required to determine a set of Δk are physically realizable pair, (r,w), and the sum of Δk of new designed assemblies as close to Δk{sub TARGET} as possible. New Gd-bearing assemblies selected based on valid pairs of (r,w) are replaced with existing assemblies in a PLP. This design methodology is applied to Shin-Kori Unit 3 Cycle 1 used as a reference model. CASMO-3/MASTER code is used for depletion calculation. CASMO-3/MASTER calculations with new designed assemblies produce lower CBC than the expected CBC, proving that the proposed method works successful.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

A modified Rietveld method to model highly anisotropic ceramics

High energy X-ray diffraction was employed to probe the complex constitutive behavior of a polycrystalline ferroelectric material in various sample orientations. Pb(Zn,Nb)O3-Pb(Zr,Ti)O3 (PZN-PZT) ceramics were subjected to a cyclic bipolar electric field while diffraction patterns were taken. Using transmission geometry and a two-dimensional detector, lattice strain and texture evolution (domain switching) were measured in multiple sample directions simultaneously. In addition, texture analysis suggests that non-180{sup o} domain switching is coupled with lattice strain evolution during uniaxial electrical loading. As a result of this material's high strain anisotropy, the full-pattern Rietveld method was inadequate to analyze the diffraction data. Instead, a modified Rietveld method, which includes an elastic anisotropy term, yielded significant improvements in the data analysis results.

36 MATERIALS SCIENCE↗