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At least 1,783 records · Page 99

DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT

We present dynamical models of four interacting systems: NGC 5257/8, The Mice, the Antennae, and NGC 2623. The parameter space of the encounters are constrained using the Identikit model-matching and visualization tool. Identikit utilizes hybrid N-body and test particle simulations to enable rapid exploration of the parameter space of galaxy mergers. The Identikit-derived matches of these systems are reproduced with self-consistent collisionless simulations which show very similar results. The models generally reproduce the observed morphology and H I kinematics of the tidal tails in these systems with reasonable properties inferred for the progenitor galaxies. The models presented here are the first to appear in the literature for NGC 5257/8 and NGC 2623, and The Mice and the Antennae are compared with previously published models. Based on the assumed mass model and our derived initial conditions, the models indicate that the four systems are currently being viewed 175-260 Myr after first passage and cover a wide range of merger stages. In some instances there are mismatches between the models and the data (e.g., in the length of a tail); these are likely due to our adoption of a single mass model for all galaxies. Despite the use of a single mass model, these results demonstrate the utility of Identikit in constraining the parameter space for galaxy mergers when applied to real data.

79 ASTRONOMY AND ASTROPHYSICS↗

THE SPITZER INTERACTING GALAXIES SURVEY: A MID-INFRARED ATLAS OF STAR FORMATION

The Spitzer Interacting Galaxies Survey is a sample of 103 nearby galaxies in 48 systems, selected using association likelihoods and therefore free from disturbed morphology biases. All galaxies have been observed with Infrared Array Camera and MIPS 24 μm bands from the Spitzer Space Telescope. This catalog presents the global flux densities and colors of all systems and correlations between the interacting systems and their specific star formation rate (sSFR). This sample contains a wide variety of galaxy interactions with systems ranging in mass, mass ratios, and gas-content as well as interaction strength. This study seeks to identify the process of triggering star formation in galaxy interactions, therefore, we focus on the non-active galactic nucleus spiral galaxies only. From this subset of 70 spiral galaxies we have determined that this sample has enhanced sSFR compared to a sample of non-interacting field galaxies. Through optical data we have classified each system by “interaction strength”; the strongly interacting (Stage 4) galaxies have higher sSFR values than the weakly (Stage 2) and moderately (Stage 3) interacting systems. However, the Stage 2 and 3 systems have statistically identical sSFR properties, despite the lack of optical interaction signatures exhibited by the Stage 2 galaxies. We suggest that the similarity of sSFR in these stages could be a consequence of some of these Stage 2 systems actually being post-perigalactic and having had sufficient time for their tidal features to fade to undetectable levels. This interpretation is consistent with the correlation of sSFR with separation, which we have determined to have little variation up to 100 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗

Transverse momentum fluctuations and their correlation with elliptic flow in nuclear collision

In this article, we propose observables v 0 and v 0 (p T ) which quantify the relative fluctuations in the total transverse momentum at fixed multiplicity. We first study the factorization of the fixed multiplicity momentum dependent two particle correlation function into a product of v 0 ($p^{a}_{T}$) and v 0 ($p^{b}_{T}$) within realistic hydrodynamic simulations. Then we present computations of v 0 (p T ) for different particle types. We determine the relation between the integrated v 0 and previously measured observables, and compare results from a hybrid hydrodynamics based model to experimental data. The effects of bulk viscosity and an initial pre-equilibrium stage on the results are quantified. We find that v 0 is strongly correlated with the initial state entropy per elliptic area, S/A. Using this result, we explain how the observed correlations between the elliptic flow and the transverse momentum (both in simulations and experiment) reflect the initial state correlations between 1/A and ellipticity ε 2 at fixed multiplicity. Furthermore, we argue that the systematic experimental study of v 0 , with the same sophistication as used for the other v n , can contribute significantly to our understanding of quark gluon plasma properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Genetic Identification of Lamprey Genera and Anadromous Ecotypes in Watersheds of the Northeastern Pacific Ocean

ABSTRACT Nonparasitic, nonmigratory Western Brook Lamprey (WBL; Lampetra ayresii ), and parasitic, anadromous Western River Lamprey (WRL; L. ayresii ) are sympatric lampreys that likely represent different life history variations of a single species. Novel genetic tools are critical for differentiating WBL and WRL, whose larvae preclude morphological identification (ID) and will enable comprehensive assessment of imperiled native lampreys of the Northeastern Pacific (including WBL, WRL, and Pacific Lamprey, Entosphenus tridentatus ). We developed 47 candidate single nucleotide polymorphism (SNP) markers using whole genome resequencing of WBL ( N = 24) and WRL ( N = 15) from Ksi Ts'oohl Ts'ap Creek (Nass River, British Columbia, Canada) which are likely ecotypes distinguished by few divergent SNPs across multiple chromosomes. We used five novel candidate SNPs to perform genetic ID of WBL and WRL ecotypes in collections of mixed native lampreys from lower Columbia River tributaries ( N = 1474), Ksi Ts'oohl Ts'ap Creek ( N = 352), and ocean phase WRL from the Georgia Basin (Salish Sea, British Columbia, Canada; N = 91). Two previously published SNPs were used to ID genera, Entosphenus versus Lampetra . Morphological ID utilized photographs collected from a subset of genotyped lampreys, and high concordance was demonstrated between ID methods for genera (99%) and Lampetra ecotypes (> 98%). We characterized spatial and temporal composition of lamprey genera and ecotypes surveyed across NE Pacific tributaries under the expectation these compositions would be similar across nearby sites and across years at the same site. Proportions of lamprey genera were highly variable within regions and across years; however, Lampetra ecotypic proportions were spatially and temporally stable. WRL were rare in lower Columbia tributaries (~1% average rate among Lampetra ) and common further north (> 40% of Lampetra ). Genetic ID methods are powerful monitoring tools that create the novel ability to ascertain genera and ecotypes regardless of life stage, while increasing the efficiency of surveys by eliminating time‐intensive morphological data collection.

Silver, G. S. [Columbia River Inter‐Tribal Fish Co↗

Dosimetric and deformation effects of image-guided interventions during stereotactic body radiation therapy of the prostate using an endorectal balloon

Purpose: During stereotactic body radiation therapy (SBRT) for the treatment of prostate cancer, an inflatable endorectal balloon (ERB) may be used to reduce motion of the target and reduce the dose to the posterior rectal wall. This work assessed the dosimetric impact of manual interventions on ERB position in patients receiving prostate SBRT and investigated the impact of ERB interventions on prostate shape. Methods: The data of seven consecutive patients receiving SBRT for the treatment of clinical stage T1cN0M0 prostate cancer enrolled in a multi-institutional, IRB-approved trial were analyzed. The SBRT dose was 50 Gy in five fractions to a planning target volume (PTV) that included the prostate (implanted with three fiducial markers) with a 3-5 mm margin. All plans were based on simulation images that included an ERB inflated with 60 cm{sup 3} of air. Daily kilovoltage cone-beam computed tomography (CBCT) imaging was performed to localize the PTV, and an automated fusion with the planning images yielded displacements required for PTV relocalization. When the ERB volume and/or position were judged to yield inaccurate repositioning, manual adjustment (ERB reinflation and/or repositioning) was performed. Based on all 59 CBCT image sets acquired, a deformable registration algorithm was used to determine the dose received by, displacement of, and deformation of the prostate, bladder (BLA), and anterior rectal wall (ARW). This dose tracking methodology was applied to images taken before and after manual adjustment of the ERB (intervention), and the delivered dose was compared to that which would have been delivered in the absence of intervention. Results: Interventions occurred in 24 out of 35 (69%) of the treated fractions. The direct effect of these interventions was an increase in the prostate radiation dose that included 95% of the PTV (D95) from 9.6 {+-} 1.0 to 10.0 {+-} 0.2 Gy (p = 0.06) and an increase in prostate coverage from 94.0% {+-} 8.5% to 97.8% {+-} 1.9% (p = 0.03). Additionally, ERB interventions reduced prostate deformation in the anterior-posterior (AP) direction, reduced errors in the sagittal rotation of the prostate, and increased the similarity in shape of the prostate to the radiotherapy plan (increased Dice coefficient from 0.76 {+-} 0.06 to 0.80 {+-} 0.04, p = 0.01). Postintervention decreases in prostate volume receiving less than the prescribed dose and decreases in the voxel-wise displacement of the prostate, bladder, and anterior rectal wall were observed, which resulted in improved dose-volume histogram (DVH) characteristics. Conclusions: Image-guided interventions in ERB volume and/or position during prostate SBRT were necessary to ensure the delivery of the dose distribution as planned. ERB interventions resulted in reductions in prostate deformations that would have prevented accurate localization of patient anatomy.

60 APPLIED LIFE SCIENCES↗

3D delivered dose assessment using a 4DCT-based motion model

Purpose: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). Methods: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying “fluoroscopic” 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using “ground truth” XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. Results: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images reconstructed from kV and MV projections compared to the ground truth, which is clinically comparable to 4DCT (0.093%). For the second XCAT phantom that has an irregular breathing pattern, the errors are 0.81% and 1.75% for kV and MV reconstructions, both of which are better than that of 4DCT (4.01%). In the case of real patient, although it is impossible to obtain the actual delivered dose, the dose estimation is clinically reasonable and demonstrates differences between 4DCT and MV reconstruction-based dose estimates. Conclusions: With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed 3D fluoroscopic images was as good as 4DCT for regular respiratory pattern and was a better dose estimation for the irregular respiratory pattern.

60 APPLIED LIFE SCIENCES↗

EGS Collab Experiment 1: In-situ observation of pre-, co- and post-seismic shear slip preceding hydraulic fracturing

Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the acceleration of sliding, followed by fast co-seismic slip and a transient afterslip phase. Total displacements were about 7, 5.5 and 9.5 micrometers, respectively for the observed pre-slip, co-seismic slip and afterslip. The observed pre-slip lasted about 0.4 seconds. Co-seismic slip was recorded by the 1 kHz displacement recording and a 12-component array of 3-C accelerometers sampled at 100 kHz. The observed afterslip is consistent with analytical models of arrest in a velocity-strengthening region and subsequent stress relaxation. The observed slip vector agrees with the activation of a bedding plane within the phyllite, which is corroborated by relocated seismic events that were observed during the later stages of the injection experiment. This submission includes the pressure and deformation data recorded by the SIMFIP probe during the first injection at the 164 ft (50 m) notch of borehole E1-I. The injection was performed on on 05/22/2018 as part of Experiment 1 of the EGS Collab project. This data accompanies a manuscript submitted to GRL, linked in this submission.

15 GEOTHERMAL ENERGY↗

Precompound Emission of Energetic Light Fragments in Spallation Reactions [Dissertation]

Emission of light fragments (LF) from nuclear reactions is an open question. Different reaction mechanisms contribute to their production; the relative roles of each, and how they change with incident energy, mass number of the target, and the type and emission energy of the fragments is not completely understood. None of the available models are able to accurately predict emission of LF from arbitrary reactions. However, the ability to describe production of LF (especially at energies ≳ 30 MeV) from many reactions is important for different applications, such as cosmic-ray-induced Single Event Upsets (SEUs), radiation protection, and cancer therapy with proton and heavy-ion beams, to name just a few. The Cascade-Exciton Model (CEM) version 03.03 and the Los Alamos version of the Quark-Gluon String Model (LAQGSM) version 03.03 event generators in Monte Carlo N-Particle Transport Code version 6 (MCNP6) describe quite well the spectra of fragments with sizes up to 4 He across a broad range of target masses and incident energies (up to ~ 5 GeV for CEM and up to ~ 1 TeV/A for LAQGSM). However, they do not predict the high energy tails of LF spectra heavier than 4 He well. Most LF with energies above several tens of MeV are emitted during the precompound stage of a reaction. The current versions of the CEM and LAQGSM event generators do not account for precompound emission of LF larger than 4 He. The aim of our work is to extend the precompound model in them to include such processes, leading to an increase of predictive power of LF-production in MCNP6. This entails upgrading the Modified Exciton Model currently used at the preequilibrium stage in CEM and LAQGSM. It also includes expansion and examination of the coalescence and Fermi break-up models used in the precompound stages of spallation reactions within CEM and LAQGSM. Extending our models to include emission of fragments heavier than 4 He at the precompound stage has indeed provided results that have much better agreement with experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A hard X-ray study of a manganese-terpyridine catalyst in a chromium-based Metal Organic Framework

Hydrogen produced from water splitting is a promising source of clean energy. However, a robust catalyst is necessary to carry out the water oxidation step of water splitting. In this study, the catalyst studied was [(terpy)Mn(μ-O)2Mn(terpy)] 3+ (MnTD) synthesized in the Metal Organic Framework (MOF) MIL-101(Cr), and the method used for analysis was hard X-ray powder diffraction. The diffraction data was used to detect the presence of MOF in different catalytic stages, and lattice parameters were assigned to the samples containing MOF. Fourier maps were constructed with GSAS II to determine the contents of the MOF as preliminary studies suggested that MnTD may not be present. Results showed that MOF is present before catalysis occurs but disappears by the time 45 minutes of catalysis has ensued. Changes in the MOF’s lattice parameters and location of electron density in the Fourier maps suggest attractions between the MOF and catalyst that may lead to MOF degradation. Fourier maps also revealed limited, if any, amounts of MnTD, even before catalysis occurred. Molecular manganese oxide may be the source of the high rate of water oxidation catalysis in the studied system.

08 HYDROGEN↗

eRHIC ERL modeling in Zgoubi

This Note discusses on-going work regarding the modeling of eRHIC ERL in the ray-tracing code Zgoubi. The various pieces of the recirculator puzzle, their optical properties and their assemblage into an operational input data file in are addressed. The Note reports in particular on preparatory stages toward extensive end-to-end 6D polarized electron bunch transport simulations, which yield methods, as well a series of preliminary qualitative outcomes, discussed as well.

43 PARTICLE ACCELERATORS↗

Fuel Cell Buses in U.S. Transit Fleets: Current Status 2017

This report, published annually, summarizes the progress of fuel cell electric bus (FCEB) development in the United States and discusses the achievements and challenges of introducing fuel cell propulsion in transit. The report provides a summary of results from evaluations performed by the National Renewable Energy Laboratory. This annual status report combines results from all FCEB demonstrations, tracks the progress of the FCEB industry toward meeting technical targets, documents the lessons learned, and discusses the path forward for commercial viability of fuel cell technology for transit buses. These data and analyses help provide needed information to guide future early-stage research and development. The 2017 summary results primarily focus on the most recent year for each demonstration, from August 2016 through July 2017. The primary results presented in the report are from five demonstrations of two different fuel-cell-dominant bus designs: Zero Emission Bay Area Demonstration Group led by Alameda-Contra Costa Transit District (AC Transit) in California; American Fuel Cell Bus (AFCB) Project at SunLine Transit Agency in California; AFCB Project at the University of California at Irvine; AFCB Project at Orange County Transportation Authority; and AFCB Project at Massachusetts Bay Transportation Authority.

30 DIRECT ENERGY CONVERSION↗

Corrective Action Decision Document/Corrective Action Plan for Corrective Action Unit 97: Yucca Flat/Climax Mine Nevada National Security Site, Nevada, Revision 1

This corrective action decision document (CADD)/corrective action plan (CAP) has been prepared for Corrective Action Unit (CAU) 97, Yucca Flat/Climax Mine, Nevada National Security Site (NNSS), Nevada. The Yucca Flat/Climax Mine CAU is located in the northeastern portion of the NNSS and comprises 720 corrective action sites. A total of 747 underground nuclear detonations took place within this CAU between 1957 and 1992 and resulted in the release of radionuclides (RNs) in the subsurface in the vicinity of the test cavities. The CADD portion describes the Yucca Flat/Climax Mine CAU data-collection and modeling activities completed during the corrective action investigation (CAI) stage, presents the corrective action objectives, and describes the actions recommended to meet the objectives. The CAP portion describes the corrective action implementation plan. The CAP presents CAU regulatory boundary objectives and initial use-restriction boundaries identified and negotiated by DOE and the Nevada Division of Environmental Protection (NDEP). The CAP also presents the model evaluation process designed to build confidence that the groundwater flow and contaminant transport modeling results can be used for the regulatory decisions required for CAU closure. The UGTA strategy assumes that active remediation of subsurface RN contamination is not feasible with current technology. As a result, the corrective action is based on a combination of characterization and modeling studies, monitoring, and institutional controls. The strategy is implemented through a four-stage approach that comprises the following: (1) corrective action investigation plan (CAIP), (2) CAI, (3) CADD/CAP, and (4) closure report (CR) stages.

54 ENVIRONMENTAL SCIENCES↗

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

An intelligent Data Delivery Service for and beyond the ATLAS experiment

The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. It has been designed to intelligently orchestrate workflows and data management systems, decoupling data pre-processing, delivery, and primary processing in large scale workflows. It is an experiment-agnostic service that has been deployed to serve data carousel (orchestrating efficient processing of tape-resident data), machine learning hyperparameter optimization, active learning, and other complex multi-stage workflows defined via DAG (Directed Acyclic Graph), CWL (Common Workflow Language) and other descriptions, including a growing number of analysis workflows. We will at first introduce some deployed use cases in a summary. Then we will focus on new improvements and use cases under developments in ATLAS, Rubin Observatory and sPHENIX, together with future efforts.

97 MATHEMATICS AND COMPUTING↗