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A demonstration of a whole core neutron transport method in a gas cooled reactor

This paper illustrates a capability of the whole core transport method COMET. Building on previous works which demonstrated the accuracy of the method, this work serves to emphasize the robust capability of the method while also accentuating its efficiency. A set of core configurations is presented based on an operating gas-cooled thermal reactor, Japan's HTTR, and COMET determines the eigenvalue and fission density profile throughout each core configuration. Results for core multiplication factors are compared to MCNP for accuracy and also to compare runtimes. In all cases, the values given by COMET differ by those given by MCNP by less than the uncertainty inherent in the stochastic solution procedure, however, COMET requires runtimes shorter on the order of a few hundred. Figures are provided illustrating the whole core fission density profile, with segments of pins explicitly modeled individually, so that pin-level neutron flux behavior can be seen without any approximation due to simplification strategies such as homogenization. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multilevel graph embedding

The goal of the present paper is the design of embeddings of a general sparse graph into a set of points in $\mathbb{R}^d$ for appropriate d ≥ 2. The embeddings that we are looking at here aim to keep vertices that are grouped in communities together and keep the rest apart. To achieve this property, we utilize coarsening that respects possible community structures of the given graph. We employ a hierarchical multilevel coarsening approach that identifies communities (strongly connected groups of vertices) at every level. The multilevel strategy allows any given (presumably expensive) graph embedding algorithm to be made into a more scalable (and faster) algorithm. We demonstrate the presented approach on a number of given embedding algorithms and large-scale graphs and achieve speed-up over the methods in a recent paper.

97 MATHEMATICS AND COMPUTING↗

Temperature induces significant changes in both glycolytic reserve and mitochondrial spare respiratory capacity in colorectal cancer cell lines

Thermotherapy, as a method of treating cancer, has recently attracted considerable attention from basic and clinical investigators. A number of studies and clinical trials have shown that thermotherapy can be successfully used as a therapeutic approach for various cancers. However, the effects of temperature on cancer bioenergetics have not been studied in detail with a real time, microplate based, label-free detection approach. This study investigates how changes in temperature affect the bioenergetics characteristics (mitochondrial function and glycolysis) of three colorectal cancer (CRC) cell lines utilizing the Seahorse XF96 technology. Experiments were performed at 32 °C, 37 °C and 42 °C using assay medium conditions and equipment settings adjusted to produce equal oxygen and pH levels ubiquitously at the beginning of all experiments. The results suggest that temperature significantly changes multiple components of glycolytic and mitochondrial function of all cell lines tested. Under hypothermia conditions (32 °C), the extracellular acidification rates (ECAR) of CRC cells were significantly lower compared to the same basal ECAR levels measured at 37 °C. Mitochondrial stress test for SW480 cells at 37 °C vs 42 °C demonstrated increased proton leak while all other OCR components remained unchanged (similar results were detected also for the patient-derived xenograft cells Pt.93). Interestingly, the FCCP dose response at 37 °C vs 42 °C show significant shifts in profiles, suggesting that single dose FCCP experiments might not be sufficient to characterize the mitochondrial metabolic potential when comparing groups, conditions or treatments. These findings provide valuable insights for the metabolic and bioenergetic changes of CRC cells under hypo- and hyperthermia conditions that could potentially lead to development of better targeted and personalized strategies for patients undergoing combined thermotherapy with chemotherapy.

60 APPLIED LIFE SCIENCES↗

Confocal Raman Microscopy for the Determination of Protein and Quaternary Ammonium Ion Loadings in Biocatalytic Membranes for Electrochemical Energy Conversion and Storage

Here, the need to immobilize active enzyme, while ensuring high rates of substrate turnover and electronic charge transfer with an electrode, is a centrally important challenge in the field of bioelectrocatalysis. In this work, we demonstrate the use of confocal Raman microscopy as a tool for quantitation and molecular-scale structural characterization of ionomers and proteins within biocatalytic membranes to aid in the development of energy efficient biofuel cells. A set of recently available short side chain Aquivion ionomers spanning a range of equivalent weight (EW) suitable for enzyme immobilization was investigated. Aquivion ionomers (790 EW, 830 EW and 980 EW) received in the proton-exchanged (SO 3 H) form were treated with tetra-n-butylammonium bromide (TBAB) to neutralize the ionomer and expand the size of ionic domains for enzyme incorporation. Through the use of confocal Raman microscopy, membrane TBA+ ion content was predicted in calibration studies to within a few percent of the conventional titrimetric method across the full range of TBA + : SO 3 - ratios of practical interest (0.1 to 1.7). Protein incorporation into membranes was quantified at the levels expected in biofuel cell electrodes. Furthermore, features associated with the catalytically active, enzyme-coordinated copper center were evident between 400 cm -1 - 500 cm -1 in spectra of laccase catalytic membranes, demonstrating the potential to interrogate mechanistic chemistry at the enzyme active site of biocathodes under fuel cell reaction conditions. When benchmarked against the 1100 EW Nafion ionomer in glucose/air enzymatic fuel cells (EFCs), EFCs with laccase air-breathing cathodes prepared from TBA + modified Aquivion ionomers were able to reach maximum power densities (P max ) up to 1.5 times higher than EFCs constructed with cathodes prepared from TBA + modified Nafion. The improved performance of EFCs containing the short side chain Aquivion ionomers relative to Nafion is traced to effects of ionomer ion-exchange capacity (IEC, where IEC = EW -1 ), where the greater density of SO 3 - moieties in the Aquivion materials produces an environment more favourable to mass transport and higher TBA + concentrations.

36 MATERIALS SCIENCE↗

Hydrogen Activation by Silica Supported Metal Ion Catalysts: Catalytic Properties of Metals and Performance of DFT Functionals

Single-site heterogeneous catalysts (SSHC) have received increasing attention due to their well-defined active sites and potentially high specific activity. Detailed computational studies were carried out on a set of potential SSHC’s, i.e., silica-supported metal ions, to investigate the reactivity of these catalysts with H2 as well as to evaluate the performance of density functional theory (DFT) methods in conjunction with triple-ζ quality basis sets (i.e., cc-pVTZ) on reaction energetics. The ions considered include 4d and 5d metals as well as several post-transition metal ions. A representative cluster model of silica is used to calculate reaction free energies of the metal hydride formation that results from the heterolytic cleavage of H2 on the M–O bond. The hydride formation free energy is previously shown to be strongly correlated with the catalytic activity of such catalysts for alkene hydrogenation. ONIOM calculations (CCSD(T)//MP2) are used to assess the accuracy and reliability of the MP2 results and it is found that MP2 is a suitable level of theory for gauging the performance of DFT functionals. The performance of various DFT functionals is assessed relative to MP2 results and it is found that the wB97xd and PBE0 functionals have the lowest standard deviation (STD) value while the MN12SX and PBE functionals have the lowest mean absolute deviation (MAD) values. The B3LYP functional is shown to have similar MAD and STD values as the top performing functionals. Potential active SSHC’s for exergonic hydrogen activation predicted in this study include mostly late and post transition metal ions, i.e., Au3+, Pd2+, Pt4+, Pd4+, Ir4+, Hg2+, Rh3+, Pb4+, Tl3+, In3+, Ir3+, Os4+, Cd2+, Ru2+, and Ga3+. This study provides important guidance to future computational studies of such catalyst systems.

Plascencia, Cesar↗

Automated Detection and Characterization of Surface Restructuring Events in Bimetallic Catalysts

Surface restructuring in bimetallic systems has recently been shown to play a crucial role in heterogeneous catalysis. In particular, the segregation in binary alloys can be reversed in the presence of strongly bound adsorbates. Mechanistic characterization of such restructuring phenomena at the atomic level remains scarce and challenging because of the large configurational space that must be explored. To this end, we propose an automated method to discover elementary surface restructuring processes in an unbiased fashion using Pd/Ag as an example. Here, we employ high-temperature classical molecular dynamics to rapidly detect restructuring events, isolate them, and optimize using density functional theory. In addition to confirming the known exchange descent mechanism, our systematic approach has revealed three new predominant classes of events at step edges of close-packed surfaces that have not been considered before: (1) vacancy insertion; (2) direct exchange; and (3) interlayer exchange. The discovered events enable us to construct the complete set of mechanistic pathways by which Pd is incorporated into the Ag host in vacuum at the single-atom limit. Finally, these atomistic insights provide a step toward systematic understanding and engineering of surface segregation dynamics in bimetallic catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mass generation in an Abelian gauge theory with multiple scalar fields and no tree-level dimensionful couplings

We study the Abelian Higgs model with multiple scalar fields, but without mass terms. Solving the model nonperturbatively order-by-order in the number of scalar fields, we find that radiative corrections generate masses for the scalar and gauge boson, without spontaneous symmetry breaking. The mass scales are set by the Λ -parameter of the electroweak running coupling, thereby naturally avoiding the hierarchy problem. No part of our calculation employs a weak-coupling expansion, and we find that the perturbative vacuum is metastable, and hence must decay to the stable nonperturbative vacuum of the theory, which we identify. Although the field content of our Lagrangian is standard, our results predict the existence of two heavy scalar resonances in addition to the Higgs. We believe that these predicted resonances will ultimately allow experimentalists to discriminate between our method and standard solutions of the Higgs model. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Coherency-Constrained Spectral Clustering for Power Network Reduction

This paper presents a methodology for reducing the complexity of large-scale power network models using spectral clustering, aggregation of electrical components, and cost function approximation. Two approaches are explored using unconstrained and constrained spectral clustering to determine areas for effective system reduction. Once the system areas are determined, both loads and generators by type are aggregated, and their new cost function is approximated through polynomial curve-fitting or statistical methods. The performance of reduced networks is evaluated in terms of their ability to follow the true daily cost of the original system over a 24-hour period considering a set of several days. Two test systems are taken as test beds. Application of the methodology to a modified version of the IEEE 39-bus system reduces it from 17 generators to a 4-bus system and 9 generators with about 93% of accuracy. Similarly, the IEEE 118-bus system is reduced from 19 generators to a 3-bus system with three aggregated units achieving over 99% of accuracy. These findings address scalability challenges and enhance accuracy for high and mid-loading level conditions, and by aggregating thermal units with similar cost functions.

42 ENGINEERING↗

Simulink/PARS Integration Support

The state of the art for signal processor hardware has far out-paced the development tools for placing applications on that hardware. In addition, signal processors are available in a variety of architectures, each uniquely capable of handling specific types of signal processing efficiently. With these processors becoming smaller and demanding less power, it has become possible to group multiple processors, a heterogeneous set of processors, into single systems. Different portions of the desired problem set can be assigned to different processor types as appropriate. As software development tools do not keep pace with these processors, especially when multiple processors of different types are used, a method is needed to enable software code portability among multiple processors and multiple types of processors along with their respective software environments. Sundance DSP, Inc. has developed a software toolkit called “PARS”, whose objective is to provide a framework that uses suites of tools provided by different vendors, along with modeling tools and a real time operating system, to build an application that spans different processor types. The software language used to express the behavior of the system is a very high level modeling language, “Simulink”, a MathWorks product. ORNL has used this toolkit to effectively implement several deliverables. This CRADA describes this collaboration between ORNL and Sundance DSP, Inc.

97 MATHEMATICS AND COMPUTING↗

Single-Site Metal Organic Complexes on Oxide Supports for Selective Alkane Functionalization

High levels of reaction selectivity for heterogeneous catalysis are generally difficult to achieve with traditional metal nanoparticle catalysts, due to the variety of metal binding sites available. In this project, we have developed a metal-ligand coordination strategy to form transition metal single-sites on high surface area supports as heterogeneous single-site catalysts. Metal centers can be atomically dispersed in the binding pockets of organic ligands on oxide supports. The systems have to be carefully designed so that tendencies for metal cluster formation or binding to surface defect sites are overcome by the attractive coordination environment provided by the organic ligand. This was confirmed by a comprehensive set of characterization methods, including XAS, XPS, XRD, TEM, and CO adsorption. Design and tuning of metal-support and support-ligand interactions were crucial for high structural uniformity. We demonstrate that supported metal-ligand SSCs are effective, recyclable catalysts for alkene hydrosilylation reactions. Compared with commercial homogeneous catalysts, they exhibit improved yield and selectivity, less metal aggregation and side reactions, and stronger tolerance with functionalized substrates. These results give some preliminary indication that coordination with organic ligands can improve activity and selectivity in metal/oxide heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Underwater Noise Measurements around a Tidal Turbine in a Busy Port Setting

Acoustic emissions from current energy converters remain an environmental concern for regulators because of their potential effects on marine life and uncertainties about their effects stemming from a lack of sufficient observational data. Several recent opportunities to characterize tidal turbine sound emissions have begun to fill knowledge gaps and provide a context for future device deployments. In July 2021, a commercial-off-the-shelf hydrophone was deployed in a free-drifting configuration to measure underwater acoustic emissions and characterize a 25 kW-rated tidal turbine at the University of New Hampshire’s Living Bridge Project in Portsmouth, New Hampshire. Sampling methods and analysis were performed in alignment with the recently published IEC 62600-40 Technical Specification for acoustic characterization of marine energy converters. Results from this study indicate acoustic emissions from the turbine were below ambient sound levels and therefore did not have a significant impact on the underwater noise levels of the project site. As a component of Pacific Northwest National Laboratory’s Triton Field Trials (TFiT) described in this Special Issue, this effort provides a valuable use case for the IEC 62600-40 Technical Specification framework and further recommendations for cost-effective technologies and methods for measuring underwater noise at future current energy converter project sites.

tidal turbine↗

Development of a Trip Energy Estimation Model Using Real-World Global Positioning System Driving Data: Preprint

A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Future Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.

33 ADVANCED PROPULSION SYSTEMS↗

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methods and Results for Standard Model Event Generation at $\sqrt{s}$ = 14 TeV, 33 TeV and 100 TeV Proton Colliders (A Snowmass Whitepaper)

This document describes the novel techniques used to simulate the common Snowmass 2013 En- ergy Frontier Standard Model backgrounds for future hadron colliders. The purpose of many Energy Frontier studies is to explore the reach of high luminosity data sets at a variety of high energy collid- ers. The generation of high statistics samples which accurately model large integrated luminosities for multiple center-of-mass energies and pile-up environments is not possible using an unweighted event generation strategy | an approach which relies on event weighting was necessary. Even with these improvements in e ciency, extensive computing resources were required. This document de- scribes the speci c approach to event generation using Madgraph5 to produce parton-level processes, followed by parton showering and hadronization with Pythia6, and pile-up and detector simulation with Delphes3. The majority of Standard Model processes for pp interactions at √s = 14, 33, and 100 TeV with 0, 50, and 140 additional pile-up interactions are publicly available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High Energy Yield Distributed Architecture for Large Commercial and Utility-Scale PV Systems

Photovoltaic energy has come a long way from its early days when small cells were fabricated in the labs in the early 50s. While it took a long time for PV modules to mature into what we now see in the market and in rooftops across the world, the power electronics has been lagging behind & was always the weakest point in the PV plant, being responsible for the majority of failures & robbing the PV plants of their full potential by losing precious Watts in the process of converting power from DC to AC. Since the early days of PV power, it has been recognized that the modules need to operate at their maximum power point in order to extract as much power as is available from the PV modules at a given time of day and year. Numerous maximum power point devices were developed to do just this. While effective at extracting as much power as they can, soon after there was a realization that in a PV installation where a central inverter is used, many losses occur, hence energy yield losses. This has led to thinking about alternative architectures where the maximum power point tracking (MPPT) is performed much closer to the modules rather than at a central inverter. Several architectures were proposed ranging from a microinverter, microconverter, string inverter, string optimizer, and to a multi-string inverter or optimizer. While these architectures promise to increase the energy yield by 5% to 25% (depending where MPPT is located), & recovering losses due to shading, soiling, mismatch … there were no real studies and implementations in the field to corroborate these numbers. The program that GE Global Research proposed & received funding for is aimed at a type of distributed architectures, namely the dc architectures where only the MPPT function is distributed across the PV plant. Further, the project is concerned with choosing the right architecture for large scale commercial & utility scale plants but not residential installations. Findings from Task 1- Define Requirements & Develop Architecture- showed that for large scale commercial & utility PV plants, locating the MPPT at the string level with a string size of >3kW is the most cost effective solution & that the increase in energy yield of 6% to 8% is more than enough to make up for the increased cost due to additional power electronics. Our study also shows that in addition to an increase in energy yield, having a dc/dc converter at the string level brings additional benefits such as increased array visibility, allowing for increased monitoring and diagnostics; high and constant dc bus voltage which allows for reducing losses further and optimizing the inverter; and ability to detect ground and arc faults. Task 2 focused on designing a suitable dc/dc converter that meets the requirements defined in Task 1: Efficiency, Cost, & Reliability. For this task, we surveyed and simulated all candidate topologies known by the practitioners in the field. We also generated a novel topology, simulated it, & compared it to existing topologies. Our novel topology being a partial power processing converter came out on top due to its simplicity (fewer parts), it high efficiency, its reliability, and its lower cost. In the remaining tasks of the project, we built the hardware, tested it first in the lab, then in the field and once we worked out all the bugs and issues and were confident our system was robust, we installed it on the rooftop and started collecting the data by mid-Q3 2012. We shared our work with the scientific community in the form of conference & Journal papers, hence contributing to the general understanding of this technology area. The methods, techniques, and hardware developed under this project have all been tested in the field over long periods of time, and under many conditions and have been shown to be robust and reliable. The converters built and developed under this program have been in operation in the field since mid-June 2012, and no hardware failures have been recorded. While some software issues have been seen, none have been showstoppers. The cost analysis of the hardware showed that it meets the cost target set in the requirement document developed in the trade-off study. Improving the performance of solar installations for commercial and utility scale plants contributes to reducing their cost of ownership, hence spreading them to a larger section of the society and making them affordable. Our project contributed to the understanding of the distributed architectures, showed that PV plants’ cost of electricity can be reduced through additional power electronics which allows for harvesting more energy from the plant. When the project started in 2009, the cost of PV energy was still high, hence there was a real need to increase the energy yield, hence reduce the levelized cost of electricity (LCOE). While costs have come down significantly, the need for increasing the energy yield is still relevant, hence the project results, hardware, and techniques developed are still pertinent today. By taking this project from concept to rooftop demonstration, we showed that the technology is mature enough, robust enough, and has the potential to be used by many more customers, hence benefiting the public in general through the spread of PV energy, which ultimately contributes to reducing our dependency on fossil fuel, improving the environment, and creating more jobs.

14 SOLAR ENERGY↗

Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system

Purpose: Undertaking observer studies to compare imaging technology using clinical radiological images is challenging due to patient variability. To achieve a significant result, a large number of patients would be required to compare cancer detection rates for different image detectors and systems. The aim of this work was to create a methodology where only one set of images is collected on one particular imaging system. These images are then converted to appear as if they had been acquired on a different detector and x-ray system. Therefore, the effect of a wide range of digital detectors on cancer detection or diagnosis can be examined without the need for multiple patient exposures. Methods: Three detectors and x-ray systems [Hologic Selenia (ASE), GE Essential (CSI), Carestream CR (CR)] were characterized in terms of signal transfer properties, noise power spectra (NPS), modulation transfer function, and grid properties. The contributions of the three noise sources (electronic, quantum, and structure noise) to the NPS were calculated by fitting a quadratic polynomial at each spatial frequency of the NPS against air kerma. A methodology was developed to degrade the images to have the characteristics of a different (target) imaging system. The simulated images were created by first linearizing the original images such that the pixel values were equivalent to the air kerma incident at the detector. The linearized image was then blurred to match the sharpness characteristics of the target detector. Noise was then added to the blurred image to correct for differences between the detectors and any required change in dose. The electronic, quantum, and structure noise were added appropriate to the air kerma selected for the simulated image and thus ensuring that the noise in the simulated image had the same magnitude and correlation as the target image. A correction was also made for differences in primary grid transmission, scatter, and veiling glare. The method was validated by acquiring images of a CDMAM contrast detail test object (Artinis, The Netherlands) at five different doses for the three systems. The ASE CDMAM images were then converted to appear with the imaging characteristics of target CR and CSI detectors. Results: The measured threshold gold thicknesses of the simulated and target CDMAM images were closely matched at normal dose level and the average differences across the range of detail diameters were -4% and 0% for the CR and CSI systems, respectively. The conversion was successful for images acquired over a wide dose range. The average difference between simulated and target images for a given dose was a maximum of 11%. Conclusions: The validation shows that the image quality of a digital mammography image obtained with a particular system can be degraded, in terms of noise magnitude and color, sharpness, and contrast to account for differences in the detector and antiscatter grid. Potentially, this is a powerful tool for observer studies, as a range of image qualities can be examined by modifying an image set obtained at a single (better) image quality thus removing the patient variability when comparing systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Scalable line and plane relaxation in a parallel structured multigrid solver

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother — producing error compatible for coarse-grid correction with structured coarsening. Here, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver’s execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers — directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

97 MATHEMATICS AND COMPUTING↗

The Multi-Isotope Process (MIP) Monitor Project: FY12 Progress and Accomplishments

The Multi-Isotope Process (MIP) Monitor, being developed at Pacific Northwest National Laboratory (PNNL), provides an efficient approach to monitoring the process conditions in reprocessing facilities in support of the goal of "...(minimization of) the risks of nuclear proliferation and terrorism." The MIP Monitor measures distributions of a suite of indicator (radioactive) isotopes present within product and waste streams of a nuclear reprocessing facility. These indicator isotopes are monitored on-line by gamma spectrometry and compared, in near-real-time, to spectral patterns representing "normal" process conditions using multivariate pattern recognition software. The monitor utilizes this multivariate analysis and gamma spectroscopy of reprocessing streams to detect small changes in the gamma spectrum, which may indicate changes in process conditions. Multivariate analysis methods common in chemometrics, such as principal component analysis (PCA) and partial least squares regression (PLS), act as pattern recognition techniques, which can detect small deviations from the expected, nominal condition. By targeting multiple gamma-emitting indicator isotopes, the MIP Monitor approach is compatible with the use of small, portable, relatively high-resolution gamma detectors that may be easily deployed throughout an existing facility. The automated multivariate analysis can provide a level of data obscurity, giving a built-in information barrier to protect sensitive or proprietary operational data. Proof-of-concept simulations and experiments have been performed in previous years to demonstrate the validity of this tool in a laboratory setting. Development of the MIP Monitor approach continues to evaluate the efficacy of the monitor for automated, real-time or near-real-time application. This report details follow-on research and development efforts sponsored by the U.S. Department of Energy Fuel Cycle Research and Development related to the MIP Monitor for fiscal year 2012 (FY12).

fuel characterization↗