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Study of boron detection limit using the in-air PIGE set-up at LAMFI-USP

The quantification of small amounts of boron in materials is of extreme importance in different areas of materials science. Boron is an important contaminant and also a silicon dopant in the semiconductor industry. Boron is also extensively used in nuclear power plants, either for neutron shielding or for safety control and boron is an essential nutrient for life, either vegetable or animal. The production of silicon solar cells, by refining metallurgical-grade silicon (MG-Si) requires the control and reduction of several silicon contaminants to very low concentration levels. Boron is one of the contaminants of solar-grade silicon (SG-Si) that must be controlled and quantified at sub-ppm levels. In the metallurgical purification, boron quantification is usually made by Inductive Coupled Plasma Mass Spectrometry, (ICP-MS) but the results need to be verified by an independent analytical method. In this work we present the results of the analysis of silicon samples by Particle Induced Gamma-Ray Emission (PIGE) aiming the quantification of low concentrations of boron. PIGE analysis was carried out using the in-air external beam line of the Laboratory for Materials Analysis with Ion Beams (LAMFI-USP) by the {sup 10}B(p,αγ({sup 7}Be nuclear reaction, and measuring the 429 keV γ-ray. The in-air PIGE measurements at LAMFI have a quantification limit of the order of 10{sup 16} at/cm{sup 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Roadmap for the Application of Ion Beam Technologies to Challenges for the Advancement and Implementation of Nuclear Energy Technologies

The use of ion beams in interrogating materials performance for nuclear energy applications is advancing at a rapid rate. Ion irradiations have been proven to produce radiation effects data that are of direct relevance for understanding neutron-induced displacement damage. This development reflects significant and continued investment in infrastructure by the U.S. Department of Energy (DOE) as well as support of science and engineering research at universities and national laboratories. Application of ion beam irradiation methods to enhance the deployment of materials in reactors is in the spirit of the Gateway for Accelerated Innovation in Nuclear (GAIN) initiative sponsored by DOE to accelerate the deployment of innovation in the U.S. nuclear industry. Ion beam irradiation shows considerable promise for assisting in down selecting candidate materials for use in both current and advanced nuclear energy systems. Ion beams allow rapid achievement of materials damage levels not accessible by neutron irradiation in test reactors due to cost and time constraints. Ion beam studies provide data on the effects of irradiation under very specific conditions of temperature, radiation dose, and radiation dose rate that are difficult or impossible to achieve via reactor irradiation experiments. This data can be used to develop and validate detailed predictive radiation effects models for use in reactor materials research and development. Despite the current high state of the art and the maturity of quality assurance, there are still challenges to the deployment of ion beam data in support of reactor materials qualification. For the most part, these challenges arise from the lack of a detailed mechanistic understanding of potential difference between ion induced and neutron induced materials damage, which is exacerbated by difficulties in obtaining bulk physical and mechanical properties data from the micron-scale heavy ion irradiation depths. In particular, improved understanding of dose rate effects, as a function of temperature, are needed. This document offers a roadmap for the development and enhancement of current U.S. ion beam irradiation technologies within university and national laboratory settings, and especially for the deployment of new highly controlled in situ interrogation of materials during irradiation to provide dynamic and mechanistic data for model development. The status and capabilities of relevant U.S. ion beam facilities are summarized and recommended “best practices” for performing ion irradiations are described. The potential role of ion beam irradiations to assist the development and deployment of reactor materials is outlined. Key principles include developing methods for rapid and cost-effective materials selection and development, characterizing fundamental material response under irradiation, and developing a robust mechanistic understanding of microstructure evolution under irradiation (including development and validation of reliable predictive models for microstructure evolution).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulation of circularly polarized luminescence spectra using coupled cluster theory

We report the first computations of circularly polarized luminescence (CPL) rotatory strengths at the equation-of-motion coupled cluster singles and doubles (EOM-CCSD) level of theory. Using a test set of eight chiral ketones, we compare both dipole and rotatory strengths for absorption (electronic circular dichroism) and emission to the results from time-dependent density-functional theory (TD-DFT) and available experimental data for both valence and Rydberg transitions. For two of the compounds, we obtained optimized geometries of the lowest several excited states using both EOM-CCSD and TD-DFT and determined that structures and EOM-CCSD transition properties obtained with each structure were sufficiently similar that TD-DFT optimizations were acceptable for the remaining test cases. Agreement between EOM-CCSD and the Becke three-parameter exchange function and Lee-Yang-Parr correlation functional (B3LYP) corrected using the Coulomb attenuating method (CAM-B3LYP) is typically good for most of the transitions, though agreement with the uncorrected B3LYP functional is significantly worse for all reported properties. The choice of length vs. velocity representation of the electric dipole operator has little impact on the EOM-CCSD transition strengths for nearly all of the states we examined. For a pair of closely related β, γ-enones, (1R)-7-methylenebicyclo[2.2.1]heptan-2-one and (1S)-2-methylenebicyclo[2.2.1]heptan-7-one, we find that EOM-CCSD and CAM-B3LYP agree with the energetic ordering of the two possible excited-state conformations, resulting in good agreement with experimental rotatory strengths in both absorption and emission, whereas B3LYP yields a qualitatively incorrect result for the CPL signal of (1S)-2-methylenebicyclo[2.2.1]heptan-7-one. Finally, we predict that one of the compounds considered here, trans-bicyclo[3.3.0]octane-3,7-dione, is unique in that it exhibits an achiral ground state and a chiral first excited state, leading to a strong CPL signal but a weak circular dichroism signal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

WE-E-18A-10: Comparison of Patient Dose and Vessel Visibility Between Antiscatter Grid Removal and Lower Angiographic Radiation Dose Settings for Pediatric Imaging: A Preclinical Investigation

Purpose: To define an alternative to antiscatter grid (ASG) removal in angiographic systems which achieves similar patient dose reduction as ASG removal without degrading image quality during pediatric imaging. Methods: This study was approved by the local institution animal care and use committee (IACUC). Six different digital subtraction angiography settings were evaluated that altered the mAs, (100, 70, 50, 35, 25, 17.5% of reference mAs) with and without ASG. Three pigs of 5, 15, and 20 kg (9, 15, and 17 cm abdominal thickness; smaller than a newborn, average 3 yr old, and average 10 year old human abdomen respectively) were imaged using the six dose settings with and without ASG. Image quality was defined as the order of vessel branch that is visible relative to the injected vessel. Five interventional radiologists evaluated all images. Image quality and patient dose were statistically compared using analysis of variance and receiver operating curve (ROC) analysis to define the preferred dose level and use of ASG for a minimum visibility of 2nd or 3rd order branches of vessel visibility. Results: ASG grid removal reduces dose by 26% with reduced image quality. Only with the ASG present can 3rd order branches be visualized; 100% mAs is required for 9 cm pig while 70% mAs is adequate for the larger pigs. 2nd order branches can be visualized with ASG at 17.5% mAs for all three pig sizes. Without the ASG, 50%, 35% and 35% mAs is required for smallest to largest pig. Conclusion: Removing ASG reduces patient dose and image quality. Image quality can be improved with the ASG present while further reducing patient dose if an optimized radiographic technique is used. Rami Nachabe is an employee of Philips Health Care; Keith Strauss is a paid consultant of Philips Health Care.

60 APPLIED LIFE SCIENCES↗

Developing evidence-based prescriptive ventilation rate standards for commercial buildings in California: a proposed framework

Background - The goal of this project, with a focus on commercial buildings in California, was to develop a new framework for evidence-based minimum ventilation rate (MVR) standards that protect occupants in buildings while also considering energy use and cost. This was motivated by research findings suggesting that current prescriptive MVRs in commercial buildings do not provide occupants with fully safe and satisfactory indoor environments. Methods - The project began with a broad review in several areas ? the diverse strategies now used for standards or guidelines for MVRs or for environmental contaminant exposures, current knowledge about adverse human effects associated with VRs, and current knowledge about contaminants in commercial buildings, including their their presence, their adverse human effects, and their relationships with VRs. Based on a synthesis of the reviewed information, new principles and approaches are proposed for setting evidence-based VRs standards for commercial buildings, considering a range of human effects including health, performance, and acceptability of air. Results ? A review and evaluation is first presented of current approaches to setting prescriptive building ventilation standards and setting acceptable limits for human contaminant exposures in outdoor air and occupational settings. Recent research on approaches to setting acceptable levels of environmental exposures in evidence-based MVR standards is also described. From a synthesis and critique of these materials, a set of principles for setting MVRs is presented, along with an example approach based on these principles. The approach combines two sequential strategies. In a first step, an acceptable threshold is set for each adverse outcome that has a demonstrated relationship to VRs, as an increase from a (low) outcome level at a high reference ventilation rate (RVR, the VR needed to attain the best achievable levels of the adverse outcome); MVRs required to meet each specific outcome threshold are estimated; and the highest of these MVRs, which would then meet all outcome thresholds, is selected as the target MVR. In a second step, implemented only if the target MVR from step 1 is judged impractically high, costs and benefits are estimated and this information is used in a risk management process. Four human outcomes with substantial quantitative evidence of relationships to VRs are identified for initial consideration in setting MVR standards. These are: building-related symptoms (sometimes called sick building syndrome symptoms), poor perceived indoor air quality, and diminished work performance, all with data relating them directly to VRs; and cancer and non-cancer chronic outcomes, related indirectly to VRs through specific VR-influenced indoor contaminants. In an application of step 1 for offices using a set of example outcome thresholds, a target MVR of 9 L/s (19 cfm) per person was needed. Because this target MVR was close to MVRs in current standards, use of a cost/benefit process seemed unnecessary. Selection of more stringent thresholds for one or more human outcomes, however, could raise the target MVR to 14 L/s (30 cfm) per person or higher, triggering the step 2 risk management process. Consideration of outdoor air pollutant effects would add further complexity to the framework. For balancing the objective and subjective factors involved in setting MVRs in a cost-benefit process, it is suggested that a diverse group of stakeholders make the determination after assembling as much quantitative data as possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Decarbonization in Climate Resilience Planning

Recent executive orders such as E.O. 14008 require federal agencies to address climate change by enhancing resilience and reducing emissions through decarbonization. Traditionally, federal agencies require their sites to develop preparedness plans, such as continuity of operations plans and/or more comprehensive resilience plans. When climate change is included in these plans, the focus tends to be on climate adaptation solutions such as hardening infrastructure and not on climate mitigation through decarbonization. However, with the ambitious emission reductions targets set out by the federal government, it is essential to provide resources and tools to support energy and water managers in achieving decarbonization goals. To achieve this, there is a need for decarbonization to be incorporated into existing resilience planning processes. We discuss a method of incorporating a decarbonization analysis into an existing resilience planning process to create a holistic framework that considers climate adaptation, climate mitigation, and risk reduction priorities when developing and prioritizing solutions for federal sites. Site managers and decision makers must be aware of potential opportunities and trade-offs in meeting energy and water performance goals, emission reductions goals, and climate adaptation goals when developing technological, operational, or institutional resilience solutions. By combining these processes, energy and water managers can minimize the additional level of effort to ensure that their sites are not only able to withstand climate-related energy and water disruptions, but also contribute to climate mitigation. A holistic approach can help federal agencies serve as a model for incorporating decarbonization strategies into site-level resilience planning for the rest of the nation.

Elliott, Douglas B.↗

A Study of Physics-Informed Deep Learning for System Fluid Dynamics Closures

The sub-grid-scale (SGS) physics models, or so-called closure relations (CR), are essential in thermal-fluid modeling and simulation codes, ranging from large-eddy simulation to system-level thermo-fluid dynamic problems. While details vary, all thermo-fluid codes solve coupled mass-momentum-energy conservation partial differential equations (PDE). Traditionally, the analytical form of closure models has to be known, and then we calibrate the model using data from a set of applicable experiments. Characteristically, it takes long effort to gain insights and mechanistic understanding needed for developing closure models. Such a model is a compact form of data. The long time required for new model development limits the pace of model application while dealing with new geometries, new coolants or system conditions, particularly in newly designed systems. Alternative to mechanistic and semi-analytical models, it is possible to discover the pattern of closure relations by applying the modern machine learning methods to the body of relevant experimental data. Deep learning (DL) is a relatively new branch in the machine learning family, and a major breakthrough has been achieved since Hinton introduces a fast algorithm to efficiently train a feed-forward neural network (NN) with multilayer perceptrons. Generally, any NN with more than two layers is considered as deep learning, and it contains a large number of hyper-parameters to achieve pattern recognition or regression for complex datasets. Hornik shows that multilayer NN is compatible with universal approximation theorem. There is no constraint for a multilayer NN to capture the properties of any measurable information. This capability makes DL attractive for closure models in a system thermal-hydraulic code. As system geometry and/or operating conditions change, new physical experiments (increasingly sophisticated) are conducted to support evaluation and revision of closure models. Such a so-called data-driven modeling relaxes the structural form of system codes to directly assimilate data instead of hard-wiring the model to pre-calibrated correlations. The objective of this research is to enable cost-effective development of a DL-based closure that reflects the data. The previous work on applying machine learning techniques to fluid dynamics focused on statistical learning with basic NN from direct numerical simulations (DNS) dataset. In the present work, we show that DL-based closure models can cause the fluid calculation to diverge if multilayer NN is used. To address the issue, we investigate conditions by which the DL-based closure models work compatibly, stably, and effectively with PDE-constrained forward prediction problems. Optimally meeting the compatibility conditions constitutes a physics-informed deep learning (PIDL) strategy. We refer to this process as PDE-constrained machine learning or PDE-ML. To develop the technical basis for PDE-ML using DL-based fluid dynamics closure, numerical experiments are performed for manufactured problems of increasing complexity. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An air quality index-based multistage type-2-fuzzy interval-stochastic programming model for energy and environmental systems management under multiple uncertainties

Highlights: • A multistage type-2-fuzzy interval-stochastic programming (MTIP) method is developed. • Air quality index (AQI) is introduced to manage energy and environmental systems. • AQI-MTIP model is formulated and results for Tianjin's EES are generated. • Impacts of environmental requirements on energy systems is analyzed. • Results can provide support for making effective pollutant mitigation policy. In this study, a multistage type-2-fuzzy interval-stochastic programming (MTIP) method is developed, which extends upon the existing multistage stochastic programming (MSP) by allowing uncertainties expressed as probabilistic distributions, interval values and type-2 fuzzy sets to be effectively incorporated within the optimization framework. Through coupling air quality index (AQI) with MTIP, an AQI-MTIP model is formulated for energy and environmental systems (EES) management of Tianjin. A number of scenarios based on changed AQIs are examined to analyze the impacts of environmental requirements on the city's energy system. Results indicate that (i) with the improvement of environmental requirement, utilization of clean energies (especially natural gas) is provoked markedly; (ii) PM{sub 2.5} is the primary pollutant, 64.50% of which should be reduced each period to maintain the city's air quality at a health-safe level. These findings can help decision makers adjust energy structure, make effective mitigation strategy, and gain deep insight into the relationship between energy consumption and environmental requirement.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Pulmonary nodule detection in CT images based on shape constraint CV model

Purpose: Accurate detection of pulmonary nodules remains a technical challenge in computer-aided diagnosis systems because some nodules may adhere to the blood vessels or the lung wall, which have low contrast compared to the surrounding tissues. In this paper, the analysis of typical shape features of candidate nodules based on a shape constraint Chan–Vese (CV) model combined with calculation of the number of blood branches adhered to nodule candidates is proposed to reduce false positive (FP) nodules from candidate nodules. Methods: The proposed scheme consists of three major stages: (1) Segmentation of lung parenchyma from computed tomography images. (2) Extraction of candidate nodules. (3) Reduction of FP nodules. A gray level enhancement combined with a spherical shape enhancement filter is introduced to extract the candidate nodules and their sphere-like contour regions. FPs are removed by analysis of the typical shape features of nodule candidates based on the CV model using spherical constraint and by investigating the number of blood branches adhered to the candidate nodules. The constrained shapes of CV model are automatically achieved from the extracted candidate nodules. Results: The detection performance was evaluated on 127 nodules of 103 cases including three types of challenging nodules, which are juxta-pleural nodules, juxta-vascular nodules, and ground glass opacity nodules. The free-receiver operating characteristic (FROC) curve shows that the proposed method is able to detect 88% of all the nodules in the data set with 4 FPs per case. Conclusions: Evaluation shows that the authors’ method is feasible and effective for detection of three types of nodules in this study.

60 APPLIED LIFE SCIENCES↗

Realistic respiratory motion margins for external beam partial breast irradiation

Purpose: Respiratory margins for partial breast irradiation (PBI) have been largely based on geometric observations, which may overestimate the margin required for dosimetric coverage. In this study, dosimetric population-based respiratory margins and margin formulas for external beam partial breast irradiation are determined. Methods: Volunteer respiratory data and anterior–posterior (AP) dose profiles from clinical treatment plans of 28 3D conformal radiotherapy (3DCRT) PBI patient plans were used to determine population-based respiratory margins. The peak-to-peak amplitudes (A) of realistic respiratory motion data from healthy volunteers were scaled from A = 1 to 10 mm to create respiratory motion probability density functions. Dose profiles were convolved with the respiratory probability density functions to produce blurred dose profiles accounting for respiratory motion. The required margins were found by measuring the distance between the simulated treatment and original dose profiles at the 95% isodose level. Results: The symmetric dosimetric respiratory margins to cover 90%, 95%, and 100% of the simulated treatment population were 1.5, 2, and 4 mm, respectively. With patient set up at end exhale, the required margins were larger in the anterior direction than the posterior. For respiratory amplitudes less than 5 mm, the population-based margins can be expressed as a fraction of the extent of respiratory motion. The derived formulas in the anterior/posterior directions for 90%, 95%, and 100% simulated population coverage were 0.45A/0.25A, 0.50A/0.30A, and 0.70A/0.40A. The differences in formulas for different population coverage criteria demonstrate that respiratory trace shape and baseline drift characteristics affect individual respiratory margins even for the same average peak-to-peak amplitude. Conclusions: A methodology for determining population-based respiratory margins using real respiratory motion patterns and dose profiles in the AP direction was described. It was found that the currently used respiratory margin of 5 mm in partial breast irradiation may be overly conservative for many 3DCRT PBI patients. Amplitude alone was found to be insufficient to determine patient-specific margins: individual respiratory trace shape and baseline drift both contributed to the dosimetric target coverage. With respiratory coaching, individualized respiratory margins smaller than the full extent of motion could reduce planning target volumes while ensuring adequate coverage under respiratory motion.

60 APPLIED LIFE SCIENCES↗

Contrasting Metabolism in Perenniating Structures of Upland and Lowland Switchgrass Plants Late in the Growing Season

Background: Switchgrass (Panicum virgatum L.) is being developed as a bioenergy crop for many temperate regions of the world. One way to increase biomass yields is to move southern adapted lowland cultivars to more northern latitudes. However, many southerly adapted switchgrass germplasm can suffer significant winter kill in northerly climes. Materials and Methods: Here, we have applied next-generation sequencing in combination with biochemical analyses to query the metabolism of crowns and rhizomes obtained from two contrasting switchgrass cultivars. Crowns and rhizomes from field-grown lowland (cv Kanlow) and upland (cv Summer) switchgrass cultivars were collected from three randomly selected post-flowering plants. Summer plants were senescing, whereas Kanlow plants were not at this harvest date. Results: Principal component analysis (PCA) differentiated between both the Summer and Kanlow transcriptomes and metabolomes. Significant differences in transcript abundances were detected for 8,050 genes, including transcription factors such as WRKYs and those associated with phenylpropanoid biosynthesis. Gene-set enrichment analyses showed that a number of pathways were differentially up-regulated in the two populations. For both populations, protein levels and enzyme activities agreed well with transcript abundances for genes involved in the phenylpropanoid pathway that were upregulated in Kanlow crowns and rhizomes. The combination of these datasets suggests that dormancy-related mechanisms had been triggered in the crowns and rhizomes of the Summer plants, whereas the crowns and rhizomes of Kanlow plants had yet to enter dormancy. Conclusions: Delayed establishment of dormancy at more northerly latitudes could be one factor that reduces wintersurvival in the high-yielding Kanlow plants. Understanding the cellular signatures that accompany the transition to dormancy can be used in the future to select plants with improved winter hardiness.

59 BASIC BIOLOGICAL SCIENCES↗

Particle Release Experiment (PRex) (Final Report)

An experiment to release radioactive particles representative of small-scale venting from an underground nuclear test was conducted to gather data in support of treaty verification and monitoring activities. For this experiment, a CO 2 -driven “air cannon” was used to release La-140 at ambient temperatures. Lanthanum-140 was chosen to represent the fission fragments because of its short half-life and prominent gamma-ray emissions; the choice was also influenced by the successful production and use of La-140 with low levels of radioactive contaminants in a Defence Research and Development Canada Field Trial. The source was created through activation of high-purity natural lanthanum oxide at the reactor of Washington State University, Pullman, Washington. Multiple varieties of witness plates and air samplers were laid in an irregular grid covering the area over which the plume was modeled to deposit. Aerial survey, a NaI(Tl) mobile spectrometer, and handheld and backpack instruments ranging from polyvinyl toluene to high-purity germanium were used to survey the plume. Additionally, three varieties of soil sampling were investigated. The relative sensitivity and utility of sampling and survey methods are discussed in the context of On-Site Inspection. The measurements and samples show a high degree of correlation and form a valuable set of test data.

54 ENVIRONMENTAL SCIENCES↗

Reference floating wind array designs for three representative regions

This work presents the systematic development of three open-source reference floating wind array designs. The designs are tailored to representative site conditions for three regions of the United States: Humboldt Bay off the coast of California, the Gulf of Maine, and the Gulf of America. We adopted existing reference designs for the individual 15 MW turbines, semisubmersible floating platforms, substations, mooring systems, and power cables – integrating and adapting them as needed for each location. We adapted existing dynamic cable designs to use larger conductor sizes to meet the arrays' power transmission requirements, and we set up redundant mooring systems for each substation. The layout of each array is a uniform-grid design optimized to approximately minimize the levelized cost of energy (LCOE) within a square lease area while satisfying spatial constraints. These constraints ensure adequate clearances between adjacent turbines and between underwater components during the layout optimization to prevent clashing and ensure that all components reside within the lease boundaries. Substations are included to allow accounting for intra-array cable costs. They are placed within the uniform grid to maintain the navigability of the arrays. For each feasible layout considered, annual energy production and cable routing costs are calculated and updated in the LCOE objective function. After the optimization, we refined the cable routing with a mix of algorithmic and manual methods to ensure that the cables avoid mooring system components and approach the substation with adequate clearances. We confirmed the suitability of each reference array's layout by comparing the wake losses at each wind heading angle to the wind rose, observing that the optimized layouts largely avoid wake losses in the predominant wind directions. These reference arrays provide open-source baseline designs to enable future research and innovation of floating wind technology at the array scale.

17 WIND ENERGY↗

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗

Holographic wavefront sensors

A brief historical review of the first designs of holographic wavefront sensors (WFS’s) and the concepts lying in their basis is presented. The main directions in the development of these sensors are highlighted and considered. One of these directions implies a two-stage transition from the use of several separate measuring channels with holograms filtering only one Zernike mode: first to the use of one channel with a multiplexed hologram filtering several first Zernike modes, and then to filtering the entire set of Zernike modes with the aid of one combined multiplexed hologram. Another line of research in this field (related to the first one) is the optimisation of the filter hologram structure in order to reduce cross-modulation interferences, increase multiplexing level, etc. One more line of research implements principles of dynamic holography by introducing spatial light modulators into the WFS composition. Hence, the advantages of time multiplexing of holograms can be used. The approach developed by G. Andersen’s team, aimed at adapting the holographic WFS design for operation as an element of adaptive optical system with a zonal corrector, as well as an approach implying development of hybrid holographic sensors, are considered separately. The results of the authors’ studies of holographic WFS’s with application of the methods of Fourier holography (i.e., holography of focused beams, in particular, using diffuse scatterers in a hologram recording channel) are also reported. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improved Decarbonization Planning through Climate Resiliency Modeling

California has set ambitious decarbonization goals concerning both emissions and the portion of energy generated by renewable resources. However, climate change poses considerable uncertainties. Variation in load is driven both by the level of electrification as well as the impact of climate change on weather. Further, climate change stands to make weather more variable, impacting not just load but generation from renewable resources. In this paper, we approach the issue of the impacts of climate change on decarbonization planning from two perspectives. First, we look at the range of decarbonization pathways through 8 pathways that account for differences in socioeconomic development, global emissions, and warming. Second, we develop a more robust way of ensuring the reliability of energy resources planning than the commonly used planning reserve margin. We show that the proposed method can save between 6 and 14 billion dollars in investment and maintenance costs and outline critical policy implications concerning the reliance of power plants for satisfying planning reliability requirements, including the potential retirement of dozens of peaker power plants.

Anderson, Osten P.↗

SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were kept as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.

60 APPLIED LIFE SCIENCES↗

SU-F-J-93: Automated Segmentation of High-Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning

Purpose: We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters. Methods: Wholebrain sMRI combining 3D echo-planar spectroscopic imaging, generalized auto-calibrating partially-parallel acquisitions, and elliptical k-space encoding were conducted on 3T MRI scanner with 32-channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N-acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the water signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level-set refinement that adapts the initial blob to the fine details specific to each metabolite. Results: Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post-treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI’s regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone. Conclusion: Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance of this new acquisition modality in clinical practice.

60 APPLIED LIFE SCIENCES↗