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DOE OSTI2013

Clustering procedures for the optimal selection of data sets from multiple crystals in macromolecular crystallography

A systematic approach to the scaling and merging of data from multiple crystals in macromolecular crystallography is introduced and explained. The availability of intense microbeam macromolecular crystallography beamlines at third-generation synchrotron sources has enabled data collection and structure solution from microcrystals of <10 µm in size. The increased likelihood of severe radiation damage where microcrystals or particularly sensitive crystals are used forces crystallographers to acquire large numbers of data sets from many crystals of the same protein structure. The associated analysis and merging of multi-crystal data is currently a manual and time-consuming step. Here, a computer program, BLEND, that has been written to assist with and automate many of the steps in this process is described. It is demonstrated how BLEND has successfully been used in the solution of a novel membrane protein.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Provenance–aware workflow for data quality management and improvement for large continuous scientific data streams

Data quality assessment, management and improvement is integral part of any big data intensive scientific research to ensure accurate, reliable and reproducible science discoveries. The task of maintaining the quality of data, however, is non-trivial and pose a challenge for a program like Department of Energy’s Atmospheric Radiation Measurement (ARM) that collects data from hundreds of instruments across the world,and distributes thousands of streaming data products that are continuously growing in near-real-time in an archive 1.7 Petabyte in size and growing. We present a computational data processing workflow to collect the data quality issue via an easy and intuitive web-based portal that allows reporting of any quality issues for any site, facility or instruments at a granularity down to individual variable in the data files. Portal allows instrument specialists and scientists to provide corrective actions in form of symbolic equation. A parallel processing framework applies the data improvement to large volume of data in efficient parallel environment, while optimizing data transfer and file I/O operations. Corrected files are systematically versioned and archived. A provenance tracking module tracks and records any change made to the data during its entire life cycle which are communicated transparently to the scientific users. Developed in Python using open source technologies, software architecture enables efficient and fast management and improvement of data in an operational data center environment.

Kumar, Jitendra↗

DOE OSTI2015

A Hard X-ray Study of a Manganese-Terpyridine Dimer Catalyst in a Chromium-Based Metal Organic Framework

Much of today’s scientific research is geared toward discovering clean energy from renewable sources. A promising approach is to split water into its fundamental elements – hydrogen and oxygen. The hydrogen produced from this process is a source of clean energy. Plants carry out this water splitting routinely as a part of photosynthesis, but we cannot do this readily as the reaction requires a lot of energy, negating the value of cleaner and plentiful energy from hydrogen. Adding a catalyst provides an alternative pathway for the reaction so that it can proceed with lower energy input. Many such catalysts have been developed; the one used in this study is manganese based and is called manganese-terpyridine dimer (MnTD). The problem is that when individual molecules of MnTD interact they destroy each other, which limits practical use of the catalyst. However, by placing the catalyst in a Metal Organic Framework (MOF), the molecules of MnTD can be separated so that, in principle, they do not interact with each other and only interact with water. The MOF is essentially a repetition of boxes, and each box should contain one MnTD molecule. However, preliminary studies showed that a different molecule, not MnTD, may be inside the boxes. My research focused on identifying which molecules are present in the MOF. The primary method of analysis used was x-ray powder diffraction, a technique in which x-rays are scattered by a sample, and the intensity of the scattered radiation is measured as a function of scattering angle. Three samples were analyzed; one contained only the MOF, one contained the MOF and catalyst before catalysis, and one contained the MOF and catalyst during catalysis. The diffraction experiments were carried out at the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory. Initial results revealed that the MOF structure falls apart during catalysis. To further analyze the data, I used several computer programs, including GSAS II, FOX, and VESTA. These programs allowed me to create maps that showed regions of electron density within the MOF and gave me clues as to which molecules were present. I found that MnTD was not the catalytic molecule in the MOF. The preliminary studies showed that manganese oxide is likely present, which is consistent with by data. However, the catalytic rate for this system is much higher than that reported for manganese oxide, and thus future studies are needed to verify the identity of the catalytic molecule and determine the reasons for its unusually high rate of catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗

DOE OSTI2013

Simulating Collisions for Hydrokinetic Turbines

Evaluations of blade-strike on an axial-flow Marine Hydrokinetic turbine were conducted using a conventional methodology as well as an alternative modeling approach proposed in the present document. The proposed methodology integrates the following components into a Computational Fluid Dynamics (CFD) model: (i) advanced eddy-resolving flow simulations, (ii) ambient turbulence based on field data, (iii) moving turbine blades in highly transient flows, and (iv) Lagrangian particles to mimic the potential fish pathways. The sensitivity of blade-strike prob- ability to the following conditions was also evaluated: (i) to the turbulent environment, (ii) to fish size and (iii) to mean stream flow velocity. The proposed methodology provided fraction of collisions and offered the capability of analyzing the causal relationships between the flow environment and resulting strikes on rotating blades. Overall, the conventional methodology largely overestimates the probability of strike, and lacks the ability to produce potential fish and aquatic biota trajectories as they interact with the rotating turbine. By using a set of experimental correlations of exposure-response of living fish colliding on moving blades, the occurrence, frequency and intensity of the particle collisions was next used to calculate the survival rate of fish crossing the MHK turbine. This step indicated survival rates always greater than 98%. Although the proposed CFD framework is computationally more expensive, it provides the advantage of evaluating multiple mechanisms of stress and injury of hydrokinetic turbine devices on fish.

CFD↗

DOE OSTI2017

A computationally efficient P 1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods

The iterative convergence of the P 1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P 1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P 1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P 1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Additionally, PC provided 50% computational savings compared to employing CG in a standalone mode. The P 1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P 1 model provided good agreement against benchmark data with L 2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Toward Magnetic Resonance–Only Simulation: Segmentation of Bone in MR for Radiation Therapy Verification of the Head

Purpose: To develop a practical method to localize bones in magnetic resonance (MR) images, to create “computed tomography–like” MR images (ctMRI) that could be used for radiation therapy verification, and to generate MR-based digitally reconstructed radiographs (DRR). Methods and Materials: Using T1-weighted MR images, an air mask was derived from the manual contouring of all airways within the head and neck region using axial images at 6 anatomic levels. Compact bone, spongy bone, and soft tissue masks were then automatically generated using the statistical data derived from MR intensities and the air mask. ctMRI were then generated by mapping the MR intensities of the voxels within these masks into the CT number ranges of corresponding tissues. MR-based DRRs created from ctMRI were quantitatively evaluated using the co-registered MR and CT head images of 20 stereotactic radiosurgery patients. Ten anatomical points, positioned on the skull segmented using a threshold of 300 HU, in CT and ctMRI, were used to determine the differences in distance between MR-based DRRs and CT-based DRRs, and to evaluate the geometric accuracy of ctMRI and MR-based DRRs. Results: The bony structures were identified on ctMRI and were visible in the MR-based DRRs. From the 20 patient cases, the mean geometric difference and standard deviation between the 10 anatomical points on MR-based and CT-based DRRs was −0.05 ± 0.85 mm, respectively. This included uncertainty in image fusion. The maximum distance difference was 1.88 mm. Conclusions: A practical method was developed to segment bone from MR images. The ctMRI created can be used for radiation treatment verification when MR-only simulation is performed. MR-based DRRs can be used in place of CT-based DRRs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Implementing intensity modulated radiotherapy to the prostate bed: Dosimetric study and early clinical results

Salvage intensity modulated radiotherapy (IMRT) to the prostate bed has hardly been studied so far. We present here a feasibility study and early clinical results for 10 patients. These patients were selected on the basis of having either a biochemical relapse or high risk histology after prostatectomy. They were treated using “sliding-window” IMRT to 68 Gy in 34 fractions. Three-dimensional conformal radiotherapy (3D-CRT) plans were generated using the same planning computed tomography data set. Dose coverage of planning target volumes (PTVs) and of organs-at-risk (OAR, namely: rectum, bladder, and femoral heads) were compared. Acute toxicity and chronic toxicity were measured using the Common Toxicity Criteria for Adverse Events version 3.0 scale. IMRT significantly reduces the dose above the prescription dose given to the PTV1 (mean dose: IMRT 67.2 Gy vs 3D-CRT 67.7 Gy (p = 0.0137)), without altering dose coverage for PTV2 (mean dose: IMRT 68.1 Gy vs 3D-CRT 68.0 Gy (p = 0.3750)). Doses to OAR were lower with IMRT and differences were statistically significant (mean dose: IMRT 51.4 Gy vs 3D-CRT 56.6 Gy for rectum (p = 0.002), IMRT 45.1 Gy vs 3D-CRT 53.1 Gy for bladder (p = 0.002), and IMRT 26.1 Gy vs 3D-CRT 28.4 Gy for femoral heads (p = 0.0059)). There was no acute or chronic genitourinary or gastrointestinal toxicity >1 with a median follow-up of 38 months. IMRT to the prostatic fossa is feasible and reduces dose to OAR, with consequential limited toxicity.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2013

Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models

In the dynamic hospital setting, decision support can be a valuable tool for improving patient outcomes. Data-driven inference of future outcomes is challenging in this dynamic setting, where long sequences such as laboratory tests and medications are updated frequently. This is due in part to heterogeneity of data types and mixed-sequence types contained in variable length sequences. In this work we design a probabilistic unsupervised model for multiple arbitrary-length sequences contained in hospitalization Electronic Health Record (EHR) data. The model uses a latent variable structure and captures complex relationships between medications, diagnoses, laboratory tests, neurological assessments, and medications. It can be trained on original data, without requiring any lossy transformations or time binning. Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values. We train this model on data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The results are evaluated against held-out data for predicting the length of sequences and presence of Intensive Care Unit (ICU) in hospitalization bed sequences. Our method outperforms a baseline approach, showing that in these experiments the trained model captures information in the sequences that is informative of their future values.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for the purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and accounted for. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked. Infrared, laser or stereoscopic vision sensors are all options for computer-vision implementation depending on interior vs exterior deployment, resolution desired and other factors. Similarly the radiation sensors will be focused on gamma-ray or neutron detection due to the long travel length and ability to penetrate even moderate shielding. There is a significant difference between the vision sensors and radiation sensors in the way the 'source' or signals are generated. A vision sensor needs an external light-source to illuminate the object and then detects the re-emitted illumination (or lack thereof). However, for a radiation detector, the radioactive material is the source itself. The only exception to this is the field of active interrogations where radiation is beamed into a material to entice new/additional radiation emission beyond what the material would emit spontaneously. The aspect of the nuclear material being the source itself means that all other objects in the environment are 'illuminated' or irradiated by the source. Most radiation will readily penetrate regular material, scatter in new directions or be absorbed. Thus if a radiation source is located near a larger object that object will in turn scatter some radiation that was initially emitted in a direction other than the direction of the radiation detector, this can add to the count rate that is observed. The effect of these scatter is a deviation from the traditional distance dependence of the radiation signal and is a key challenge that needs a combined system calibration solution and algorithms. Thus both an algebraic approach as well as a statistical approach have been developed and independently evaluated to investigate the sensitivity to this deviation from the simplified radiation fall-off as a function of distance. The resulting calibrated system algorithms are used and demonstrated in various laboratory scenarios, and later in realistic tracking scenarios. The selection and testing of radiological and computer-vision sensors for the additional specific scenarios will be the subject of ongoing and future work. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

SU-E-QI-14: Quantitative Variogram Detection of Mild, Unilateral Disease in Elastase-Treated Rats

Purpose: Determining the presence of mild or early disease in the lungs can be challenging and subjective. We present a rapid and objective method for evaluating lung damage in a rat model of unilateral mild emphysema based on a new approach to heterogeneity assessment. We combined octree decomposition (used in three-dimensional (3D) computer graphics) with variograms (used in geostatistics to assess spatial relationships) to evaluate 3D computed tomography (CT) lung images for disease. Methods: Male, Sprague-Dawley rats (232 ± 7 g) were intratracheally dosed with 50 U/kg of elastase dissolved in 200 μL of saline to a single lobe (n=6) or with saline only (n=5). After four weeks, 3D micro-CT images were acquired at end expiration on mechanically ventilated rats using prospective gating. Images were masked, and lungs were decomposed to homogeneous blocks of 2×2×2, 4×4×4, and 8×8×8 voxels using octree decomposition. The spatial variance – the square of the difference of signal intensity – between all pairs of the 8×8×8 blocks was calculated. Variograms – graphs of distance vs. variance - were made, and data were fit to a power law and the exponent determined. The mean HU values, coefficient of variation (CoV), and the emphysema index (EI) were calculated and compared to the variograms. Results: The variogram analysis showed that significant differences between groups existed (p<0.01), whereas the mean HU (p=0.07), CoV (p=0.24), and EI (p=0.08) did not. Calculation time for the variogram for a typical 1000 block decomposition was ∼6 seconds, and octree decomposition took ∼2 minutes. Decomposing the images prior to variogram calculation resulted in a ∼700x decrease in time as compared to other published approaches. Conclusions: Our results suggest that the approach combining octree decomposition and variogram analysis may be a rapid, non-subjective, and sensitive imaging-based biomarker for quantitative characterization of lung disease.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Advanced Manufacturing for Thermal and Environmental Control Systems: Achieving National Energy Goals

This project was part of a regional initiative in the five counties of Central New York (CNY) that received funding from the U.S. Department of Energy (DOE) and four other federal agencies through the 2012 Advanced Manufacturing Jobs and Innovation Accelerator Challenge (AMJIAC). The CNY initiative was focused on cultivating the emergent regional cluster in “Advanced Manufacturing for Thermal and Environmental Control (AM-TEC).” As one component of the CNY AM-TEC initiative, the DOE-funded project supported five research & development seed projects that strategically targeted: 1) needs and opportunities of CNY AM-TEC companies, and 2) the goal of DOE’s Advanced Manufacturing Office (AMO) to reduce energy consumption by 50% across product life-cycles over 10 years. The project also sought to fulfill the AMO mission of developing and demonstrating new, energy-efficient processing and materials technologies at a scale adequate to prove their value to manufacturers and spur investment. The five seed projects demonstrated technologies and processes that can reduce energy intensity and improve production as well as use less energy throughout their lifecycles. The project was conducted over three years in two 18-month budget periods. During the first budget period, two projects proposed in the original AMJAIC application were successfully completed: Seed Project 1 focused on saving energy in heat transfer processes via development of nano structured surfaces to significantly increase heat flux; Seed Project 2 addressed saving energy in data centers via subzero cooling of the computing processors. Also during the first budget period, a process was developed and executed to select a second round of seed projects via a competitive request for proposals from regional companies and university collaborators. Applicants were encouraged to form industry-academic partnerships to leverage experience and resources of public and private sectors in the CNY region. Proposals were evaluated by a national panel of experts. Three projects were selected for awards and were completed successfully during the second budget period: Seed Project 3 focused on enabling self-powered furnaces to permit residents to shelter in place during power outages; Seed Project 4 addressed development of a novel method of controlling air conditioning systems that could enable flexible load matching in market segments not possible with existing technologies; and Seed Project 5 focused on the creation of smarter occupancy sensors to enable effective highly localized demand based ventilation.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

Effectively Using Remote I/O For Work Composition in Distributed Workflows

Distributed scientific workflows are becoming more important with the interest in incorporating AI into their loops. A critical programming and performance question is how to compose workflow tasks when data is produced on one system but must be consumed on another. Since the dominant technique is composition with remote I/O, this paper explores its performance expectations. We describe BigFlowSim, a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement.With BigFlowSim, we generate a synthetic benchmark. We quantify the effects of each parameter with a performance sensitivity study. We explain trends in terms of data movement reduction and show that, under certain conditions, it is possible to establish a total order among most parameters. We apply these insights to a high energy physics workflow, Belle II Monte Carlo and simulate several I/O optimizations. Speedups range from 5% to 2×, without changing compute time.

Friese, Ryan D.↗

DOE OSTI2014

An Advanced Network and distributed Storage Laboratory (ANDSL) for Data Intensive Science (Final Report)

The original intent of this project was to build and operate an Advanced Network and Distributed Storage Laboratory (ANDSL) for Data Intensive Science that will prepare the Open Science Grid (OSG) community for a new generation of wide area communication capabilities operating at a 100Gb rate. The plan was to engage a team of four dedicated scientists that will design, develop and operate a state of the art laboratory that will be fully integrated into the organizational and operational infrastructure of the OSG. The ANDSL was planned to include host-based hardware and software required to profile, emulate and study real-life distributed storage workloads at rates of 100 Gbps. The laboratory was designed to utilize the Department Of Energy’s Advanced Network Initiative (ANI) 100GbTestbed as connections to the fabric become available so that OSG stakeholders can use it to profile real-life data intensive science applications as well as experiment with advanced storage and data management technologies. The goal of the original program of work was to close the adoption gap, decreasing the time between availability of production 100Gbps links and the end-to-end use of such a network to enable scientific discovery.

100Gb networks↗

DOE OSTI2022

Development, verification, and validation of comprehensive acoustic fluid-structure interaction capabilities in an open-source computational platform

The acoustic fluid-structure interaction (FSI) formulation is a practical numerical approach for the seismic analysis of fluid-filled tanks. However, there are no verification and validation studies reported in the literature that demonstrate the ability of an acoustic FSI numerical model to predict responses important to structural and mechanical design for intense translational and rotational earthquake inputs. Herein, an acoustic FSI formulation is implemented in the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE), and is formally verified and validated using analytical solutions and code-to-code verification, and experimental data, respectively. The analytical solutions are for small amplitude, unidirectional seismic inputs. The code-to-code verification utilizes a previously verified and validated Arbitrary Lagrangian-Eulerian (ALE) numerical model in the commercial finite element code LS-DYNA. The validation studies utilize a comprehensive data set assembled from results of 3D earthquake-simulator tests of a fluid-filled vessel. The acoustic numerical model in MOOSE is verified and validated for hydrodynamic pressures and support reactions except for cases that involve significant convective response. For small amplitude inputs, numerically predicted wave heights match those of the analytical solutions. The numerical model is not verified and validated for wave height calculations under intense 3D seismic inputs. The run times for the acoustic FSI simulations in MOOSE are an order of magnitude, or more, shorter than for the corresponding ALE simulations in LS-DYNA. The utility of the MOOSE acoustic FSI implementation is demonstrated by seismic analysis of a building equipped with a fluid-filled, advanced nuclear reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

ON A NEW THEORETICAL FRAMEWORK FOR RR LYRAE STARS. I. THE METALLICITY DEPENDENCE

We present new nonlinear, time-dependent convective hydrodynamical models of RR Lyrae stars computed assuming a constant helium-to-metal enrichment ratio and a broad range in metal abundances (Z = 0.0001–0.02). The stellar masses and luminosities adopted to construct the pulsation models were fixed according to detailed central He-burning horizontal-branch evolutionary models. The pulsation models cover a broad range in stellar luminosity and effective temperatures and the modal stability is investigated for both fundamental (FU) and first overtone polsators (FOs). We predict the topology of the instability strip (IS) as a function of the metal content and new analytical relations for the edges of the IS in the observational plane. Moreover, a new analytical relation to constrain the pulsation mass of double pulsators as a function of the period ratio and the metal content is provided. We derive new Period–Radius–Metallicity relations for FU and FO pulsators. They agree quite well with similar empirical and theoretical relations in the literature. From the predicted bolometric light curves, transformed into optical (UBVRI) and near-infrared (NIR; JHK) bands, we compute the intensity-averaged mean magnitudes along the entire pulsation cycle and in turn new and homogenous metal-dependent (RIJHK) Period–Luminosity relations. Moreover, we compute new dual and triple-band optical, optical–NIR, and NIR Period–Wesenheit–Metallicity relations. Interestingly, we find that the optical Period-W(V, B–V) is independent of the metal content and that the accuracy of individual distances is a balance between the adopted diagnostics and the precision of photometric and spectroscopic data sets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Simulating Blade-Strike on Fish passing through Marine Hydrokinetic Turbines

The study reported here evaluated the occurrence, frequency, and intensity of blade strike of fish on an axial-flow marine hydrokinetic turbine by using two modeling approaches: a conventional kinematic formulation and a proposed Lagrangian particle- based scheme. The kinematic model included simplifying assumptions of fish trajectories such as distribution and velocity. The proposed method overcame the need for such simplifications by integrating the following components into a computational fluid dynamics (CFD) model: (i) advanced eddy-resolving flow simulation, (ii) generation of ambient turbulence based on field data, (iii) moving turbine blades in highly transient flows, and (iv) Lagrangian particles to mimic the potential fish pathways. The test conditions to evaluate the blade-strike probability and fish survival rate were: (i) the turbulent environment, (ii) the fish size, and (iii) the approaching flow velocity. The proposed method offered the ability to produce potential fish trajectories and their interaction with the rotating turbine. Depending upon the scenario, the percentile of particles that registered a collision event ranged from 6% to 19% of the released sample size. Next, by using a set of experimental correlations of the exposure-response of living fish colliding with moving blades, the simulated collision data were used as input variables to estimate the survival rate of fish passing through the operating turbine. The resulting survival rates were greater than 96% in all scenarios, which is comparable to or better than known survival rates for conventional hydropower turbines. The figures of strike probability and mortality rate were amplified by the kinematic model. The proposed method offered the advantage of expanding the evaluation of other mechanisms of stress and injury on fish derived from hydrokinetic turbines and related devices.

CFD↗