Multinucleon short-range correlation model for nuclear spectral functions: Theoretical framework
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Artiles, Oswaldo↗
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SU-E-T-43: Analytical Model for Photon Peripheral Dose in Radiotherapy Treatments
Purpose: The higher survival rate of radiotherapy patients entails a growing concern on second cancers associated to peripheral doses. Currently, dosimetry of out-of field doses is still under development. Our group has developed a methodology to estimate neutron equivalent dose in organs (1,2). We aimed to propose a model to estimate out-of-field photon doses in isocentric treatments from basic clinical data. Methods: The proposed function models the dose as the sum of leakage and scatter terms. The latter is modeled as a virtual source at the collimator, which suffers from attenuation in air and tissue, corrected by the inverse-square-law. The model was parameterized using experimental measurements with TLD700 chips placed inside an anthropomorphic phantom (6–18MV) irradiated with conformal and modulated techniques in Elekta, Siemens and Varian linacs. This model provides photon dose at a point as a function of clinical parameters as prescription dose/UM, PTV volume, distance to the field edge, height of the MLC leaves and distance from the the MLC to the isocenter. Model was tested against independent measurements (TLD100) for a VMAT treatment on a Elekta. Dose to organs is modeled from dose to points along the head-to-feet axis of the organ of a “standard man” escalated by patient height. Results: Our semi-empirical model depends on 3 given parameters (leakage parameter can be individualized). A novelty of our model, over other models (e.g., PERIDOSE), arises from its applicability to any technique (independently of the number of MU needed to deliver a dose). Differences between predictions and measurements were < 0.005mSv/UM. Conclusion: We have proposed a unique model which successfully account for photon peripheral organ dose. This model can be applied in the day-to-day clinic as it only needs a few basic parameters which are readily accessible.1. Radiother. Oncol. 107:234–243, 2013. 2. Phys. Med. Biol. 57:6167–6191, 2012.
60 APPLIED LIFE SCIENCES↗
ASTEROID LIGHT CURVES FROM THE PALOMAR TRANSIENT FACTORY SURVEY: ROTATION PERIODS AND PHASE FUNCTIONS FROM SPARSE PHOTOMETRY
We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ∼53,000 fitted periods. By this method we find that 9033 of our light curves (of ∼8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ∼2 g cm{sup −3}, while C types have a lower limit of between 1 and 2 g cm{sup −3}. These results are in agreement with previous density estimates. For 5–20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms scatter by a factor of ∼3.
79 ASTRONOMY AND ASTROPHYSICS↗
Optimization and supervised machine learning methods for fitting numerical physics models without derivatives
Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.
97 MATHEMATICS AND COMPUTING↗
Heavy-impurity resonance, hybridization, and phonon spectral functions in Fe 1-x M x Si, M=Ir,Os
The vibrational behavior of heavy substitutional impurities (M=Ir,Os) in Fe 1-x M x Si (x = 0, 0.02, 0.04, 0.1) was investigated with a combination of inelastic neutron scattering (INS), transport measurements, and first-principles simulations. In this paper, our INS measurements on single-crystals mapped the four-dimensional dynamical structure factor, S(Q;E), for several compositions and temperatures. Our results show that both Ir and Os impurities lead to the formation of a weakly dispersive resonance vibrational mode, in the energy range of the acoustic phonon dispersions of the FeSi host. We also show that Ir doping, which introduces free carriers and increases electron-phonon coupling, leads to softened interatomic force-constants compared to doping with Os, which is isoelectronic to Fe. We analyze the phonon S(Q,E) from INS through a Green's function model incorporating the phonon self-energy based on first-principles density functional theory (DFT) simulations. Calculations of the quasiparticle spectral functions in the doped system reveal the hybridization between the resonance and the acoustic phonon modes. Finally, our results demonstrate a strong interaction of the host acoustic dispersions with the resonance mode, likely leading to the large observed suppression in lattice thermal conductivity.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon
Forest disturbance and regrowth are key processes in forest dynamics, but detailed information on these processes is difficult to obtain in remote forests such as the Amazon. We used chronosequences of Landsat satellite imagery (Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus) to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clear-cut, and clear-cut and burned (cut + burn) and their successional pathways of forest regrowth in the Central Amazon. We also assessed whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clear-cut. The results show that all spectral bands from the Landsat satellites were sensitive to the disturbances but after 3 to 6 years only the near-infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR values decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR values will return to pre-disturbance values in about 39, 36, and 56 years for windthrow, clear-cut, and cut + burn disturbances, respectively. The NIR band captured the observed, and different, successional pathways of forest regrowth after windthrow, clear-cut, and cut + burn. Consistent with inferences from the NIR observations, ELM-FATES predicted higher peaks of biomass and stem density after clear-cuts than after windthrows. ELM-FATES also predicted recovery of forest structure and canopy coverage back to pre-disturbance conditions in 38 years after windthrows and 41 years after clear-cut. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clear-cut to those of the NIR results suggests the NIR band can be used to benchmark forest regrowth in ecosystem models. Our results show the potential of Landsat imagery data for mapping forest regrowth from different types of disturbances, benchmarking, and the improvement of forest regrowth models.
54 ENVIRONMENTAL SCIENCES↗
Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium
Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify coding regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.
59 BASIC BIOLOGICAL SCIENCES↗
A THREE-DIMENSIONAL BABCOCK-LEIGHTON SOLAR DYNAMO MODEL
We present a three-dimensional (3D) kinematic solar dynamo model in which poloidal field is generated by the emergence and dispersal of tilted sunspot pairs (more generally bipolar magnetic regions, or BMRs). The axisymmetric component of this model functions similarly to previous 2.5 dimensional (2.5D, axisymmetric) Babcock-Leighton (BL) dynamo models that employ a double-ring prescription for poloidal field generation but we generalize this prescription into a 3D flux emergence algorithm that places BMRs on the surface in response to the dynamo-generated toroidal field. In this way, the model can be regarded as a unification of BL dynamo models (2.5D in radius/latitude) and surface flux transport models (2.5D in latitude/longitude) into a more self-consistent framework that builds on the successes of each while capturing the full 3D structure of the evolving magnetic field. The model reproduces some basic features of the solar cycle including an 11 yr periodicity, equatorward migration of toroidal flux in the deep convection zone, and poleward propagation of poloidal flux at the surface. The poleward-propagating surface flux originates as trailing flux in BMRs, migrates poleward in multiple non-axisymmetric streams (made axisymmetric by differential rotation and turbulent diffusion), and eventually reverses the polar field, thus sustaining the dynamo. In this Letter we briefly describe the model, initial results, and future plans.
79 ASTRONOMY AND ASTROPHYSICS↗
Passive Gamma Analysis of the Boiling-Water-Reactor Assemblies
Passive gamma analysis can be used to determine BU and CT of BWR assembly. The analysis is somewhat more complicated and less effective than similar method for PWR assemblies. From the measurements along the lengths of the BWR1 and BWR9 assemblies, there are hints that we may be able to use their information to help improve the model functions for better results.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Stand-Alone and Hybrid Electric Thermal Energy Storage in the System Advisor Model
This project developed stand-alone electric-thermal energy storage (ETES), stand-alone pumped thermal energy storage (PTES), and hybrid molten-salt power tower (MSPT)-ETES performance and dispatch optimization techno-economic models. The models are available to the public through the System Advisor Model (SAM) software, scripting, and as open-source code. We compared results of the dispatch model to PLEXOS dispatch of a similar generator using the same initial grid pricing signal and found our dispatch model performed well, but closer agreement between the models was limited by the inherent differences between price-taker and unit commitment models. Nevertheless, the price-taker models developed in this project are useful to analyze proposed ETES and PTES technologies because they provide more detailed system and component models, solve several orders of magnitude faster, and are available as free open-source software. The model results represent the most optimistic returns considering grid arbitrage from the input electricity pricing, so the financial results can be applied as a feasibility stage-gate. We also submitted a journal draft paper that describes the ETES dispatch model methodology and demonstrates model functionality. An accepted journal article will serve as peer-reviewed documentation for the models, along with the open-source code, SAM help-menu content, and eventually this final project report.
14 SOLAR ENERGY↗
Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways
Solid-liquid interfaces are at the heart of many modern-day technologies and provide a challenge to many materials simulation methods. A realistic first-principles computational study of such systems entails the inclusion of solvent effects. In this work, we implement an implicit solvation model that has a firm theoretical foundation into the widely used density-functional code Vienna ab initio Software Package. The implicit solvation model follows the framework of joint density functional theory. We describe the framework, our algorithm and implementation, and benchmarks for small molecular systems. We apply the solvation model to study the surface energies of different facets of semiconducting and metallic nanocrystals and the S N 2 reaction pathway. We find that solvation reduces the surface energies of the nanocrystals, especially for the semiconducting ones and increases the energy barrier of the S N 2 reaction.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Electrochemical Reduction Selectivity of Crotonaldehyde on Copper
Lignocellulosic waste is a potential feedstock for the generation of fuels and commodity chemicals, but existing conversion methods are too cost-intensive to be viable long-term solutions. Electrochemical reductions are promising for decentralized biomass valorization due to their modular scaling and capacity to run intermittently and without high temperatures or pressures. Using crotonaldehyde as a multi-functional model compound for the many partially unsaturated oxygenates found in processed biomass, we here demonstrate the production of butanal, butanol, butene, and butane (variously useful as commodity chemicals and major components of liquified petroleum gas) under ambient conditions by reductive bulk electrolysis with a copper mesh working electrode. We identify an optimum potential for reduced organic production under the reaction conditions and compare product distributions from reductions of intermediate species to further propose branching reaction pathways. Though butanal is typically the most abundant product from crotonaldehyde reduction, most of the butene and butane appear to result from a pathway involving initial reduction of the aldehyde group. We discuss evidence that selectivity is driven by interplay between crotonaldehyde reduction, local pH shifts due to the hydrogen evolution reaction, and changes in site reactivity and availability due to electrode fouling. This demonstration of model electrochemical biomass valorization also serves to inform further exploration into reduction of multi-functional molecules and electrochemical biomass processing in general.
biomass↗
The SACADA database for human reliability and human performance
Lack of appropriate and sufficient human performance data has been identified as a key factor affecting human reliability analysis (HRA) quality especially in the estimation of human error probability (HEP). The Scenario Authoring, Characterization, and Debriefing Application (SACADA) database was developed by the U.S. Nuclear Regulatory Commission (NRC) to address this data need. An agreement between NRC and the South Texas Project Nuclear Operating Company (STPNOC) was established to support the SACADA development with aims to make the SACADA tool suitable for implementation in the nuclear power plants' operator training program to collect operator performance information. The collected data would support the STPNOC's operator training program and be shared with the NRC for improving HRA quality. This paper discusses the SACADA data taxonomy, the theoretical foundation, the prospective data to be generated from the SACADA raw data to inform human reliability and human performance, and the considerations on the use of simulator data for HRA. Each SACADA data point consists of two information segments: context and performance results. Context is a characterization of the performance challenges to task success. The performance results are the results of performing the task. The data taxonomy uses a macrocognitive functions model for the framework. At a high level, information is classified according to the macrocognitive functions of detecting the plant abnormality, understanding the abnormality, deciding the response plan, executing the response plan, and team related aspects (i.e., communication, teamwork, and supervision). The data are expected to be useful for analyzing the relations between context, error modes and error causes in human performance.
99 GENERAL AND MISCELLANEOUS↗
Initial Demonstration of Peregrine in VERA-CS
This milestone demonstrates integration of the MOOSE-based Peregrine fuel performance code into the CASL Virtual Environment for Reactor Analysis (VERA). Specifically targeted at VERA’s core simulator functionality (VERA-CS), the existing VERA subchannel-neutronics capability based on COBRA-TF (CTF) and Insilico was extended to use the axisymmetric 2D R-Z fuel rod modeling functionality of PEREGINE to replace the simple fuel rod model in CTF. This three-way coupling involved defining and implementing data interfaces, software infrastructure development to support the requirements of each code, and numerical methods to implement the coupled physics. The result is a new VERA capability known as Tiamat. Development of Tiamat required extensions to the VERA build system to support a “meta build” that uses the MOOSE/libMesh/Peregrine native build system, development of a new driver layer designed to support long-term CASL code integration requirements, and implementation of data transfers for the coupled applications using the DataTransferKit (DTK). Peregrine is now compiled and tested under the VERA continuous integration server. Tiamat, a new advanced simulation tool consisting of three coupled codes - CTF for multiphase subchannel flow, Insilico for neutronics and Peregrine for fuels performance - has been developed. Tiamat was used to simulate a 17x17 assembly model for Watts Bar Unit 1 Cycle 1, which exceeds the goals of this milestone.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Quantum mechanical study of solvent effects in a prototype S{sub N}2 reaction in solution: Cl{sup −} attack on CH{sub 3}Cl
The nucleophilic attack of a chloride ion on methyl chloride is an important prototype S{sub N}2 reaction in organic chemistry that is known to be sensitive to the effects of the surrounding solvent. Herein, we develop a highly accurate Specific Reaction Parameter (SRP) model based on the Austin Model 1 Hamiltonian for chlorine to study the effects of solvation into an aqueous environment on the reaction mechanism. To accomplish this task, we apply high-level quantum mechanical calculations to study the reaction in the gas phase and combined quantum mechanical/molecular mechanical simulations with TIP3P and TIP4P-ew water models and the resulting free energy profiles are compared with those determined from simulations using other fast semi-empirical quantum models. Both gas phase and solution results with the SRP model agree very well with experiment and provide insight into the specific role of solvent on the reaction coordinate. Overall, the newly parameterized SRP Hamiltonian is able to reproduce both the gas phase and solution phase barriers, suggesting it is an accurate and robust model for simulations in the aqueous phase at greatly reduced computational cost relative to comparably accurate ab initio and density functional models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
ARE ALL SHORT-HARD GAMMA-RAY BURSTS PRODUCED FROM MERGERS OF COMPACT STELLAR OBJECTS?
The origin and progenitors of short-hard gamma-ray bursts (GRBs) remain a puzzle and a highly debated topic. Recent Swift observations suggest that these GRBs may be related to catastrophic explosions in degenerate compact stars, denoted as 'Type I' GRBs. The most popular models include the merger of two compact stellar objects (NS-NS or NS-BH). We utilize a Monte Carlo approach to determine whether a merger progenitor model can self-consistently account for all the observations of short-hard GRBs, including a sample with redshift measurements in the Swift era (z-known sample) and the CGRO/BATSE sample. We apply various merger time delay distributions invoked in compact star merger models to derive the redshift distributions of these Type I GRBs, and then constrain the unknown luminosity function of Type I GRBs using the observed luminosity-redshift (L-z) distributions of the z-known sample. The best luminosity function model, together with the adopted merger delay model, is then applied to confront the peak flux distribution (log N-log P distribution) of the BATSE and Swift samples. We find that for all the merger models invoking a range of merger delay timescales (including those invoking a large fraction of 'prompt mergers'), it is difficult to reconcile the models with all the data. The data are instead statistically consistent with the following two possible scenarios. First, that short/hard GRBs are a superposition of compact-star-merger-origin (Type I) GRBs and a population of GRBs that track the star formation history, which are probably related to the deaths of massive stars (Type II GRBs). Second, the entire short/hard GRB population is consistent with a typical delay of 2 Gyr with respect to the star formation history with modest scatter. This may point toward a different Type I progenitor than the traditional compact star merger models.
79 ASTRONOMY AND ASTROPHYSICS↗
The dual role of cGMP in oocyte maturation of zebrafish
Highlights: • Activation of the NO/sGC/cGMP pathway could lead to oocyte maturation (OM). • Inhibition of the NO/sGC/cGMP pathway could lead to OM. • NO level increased in follicular cells but remained constant in oocytes during OM. • cGMP level increased in the follicular cells but decreased in oocytes during OM. The roles of cyclic guanosine monophosphate (cGMP) signaling in oocyte maturation attracts much attention in mammals, but its roles in fish are still largely unknown. Using zebrafish as a model, we demonstrated for the first time in fish that cGMP is involved in oocyte maturation, and its functional model in oocyte maturation is different from that of mammals. The intracellular cGMP could be regulated by nitric oxide (NO), we found that all three NO synthase enzymes and four soluble guanylyl cyclases (sGC) are expressed in the zebrafish ovary. Intriguingly, either the activation or inhibition of the NO/sGC/cGMP pathway in fully grown follicles could lead to oocyte maturation. During oocyte maturation, cGMP levels increased in the follicular cell layer but decreased in oocytes, while NO levels increased in follicular cells but remained constant in oocytes. Based on these findings in zebrafish, we propose a hypothetical model on the dual role of cGMP in oocyte maturation: in follicular cells the LH signal could increase the level of NO and cGMP which induces oocyte maturation, while in the oocyte the decreased cGMP level can also induce oocyte maturation. These findings help us to understand the molecular mechanism of fish oocyte maturation.
60 APPLIED LIFE SCIENCES↗
Constructing Hubbard models for the hydrogen chain using sliced-basis density matrix renormalization group
Sliced-basis DMRG(sb-DMRG) is used to simulate a chain of hydrogen atoms and to construct low-energy effective Hubbard-like models. The downfolding procedure first involves a change of basis to a set of atom-centered Wannier functions constructed from the natural orbitals of the exact DMRG one-particle density matrix. The Wannier function model is then reduced to a fewer-parameter Hubbard-like model, whose parameters are determined by minimizing the expectation value of the Wannier Hamiltonian in the ground state of the Hubbard Hamiltonian. This indirect variational procedure not only yields compact and simple models for the hydrogen chain, but also allows us to explore the importance of constraints in the effective Hamiltonian, such as the restricting the range of the single-particle hopping and two-particle interactions, and to assess the reliability of more conventional downfolding. The entanglement entropy for a model's ground state, cut in the middle, is an important property determining the ability of DMRG and tensor networks to simulate the model, and here we study its variation with the range of the interactions. Counterintuitively, we find that shorter ranged interactions often have larger entanglement.
36 MATERIALS SCIENCE↗