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At least 649 records · Page 36

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a significant hurdle for achieving optimal performance and reliability in super-conducting radiofrequency (SRF) cavities used in accelerator cryomodules. A thorough understanding of the generation and propagation of FE-induced radiation is therefore essential to mitigate this problem. The absence of standardized measurement protocols further complicates the comparison of radiation data across different testing phases and facilities. This highlights the need for a precise quantitative method to diagnose and analyze FE-induced radiation. Such efforts could prove beneficial for improving cavity preparation and cleanroom assembly techniques during the prototype and production stages of Fermilab's Proton Improvement Plan-II (PIP-II) project. This study presents the initial steps of detailed Geant4 simulations aimed at analyzing FE-induced radiation in the low-beta 650 MHz 5-cell elliptical (LB650) cavity. Our goal is to combine these results with radiation diagnostics to enhance diagnostic accuracy and optimize detector positioning. This integrated approach ultimately aims to improve the preparation, assembly, and testing procedures for PIP-II SRF cavities, ensuring the delivery of FE-free cryomodules.

Wijethunga, S. A.K. [Fermilab] (ORCID:000000028765↗

Experimental validation of the TOPAS Monte Carlo system for passive scattering proton therapy

Purpose: TOPAS (TOol for PArticle Simulation) is a particle simulation code recently developed with the specific aim of making Monte Carlo simulations user-friendly for research and clinical physicists in the particle therapy community. The authors present a thorough and extensive experimental validation of Monte Carlo simulations performed with TOPAS in a variety of setups relevant for proton therapy applications. The set of validation measurements performed in this work represents an overall end-to-end testing strategy recommended for all clinical centers planning to rely on TOPAS for quality assurance or patient dose calculation and, more generally, for all the institutions using passive-scattering proton therapy systems. Methods: The authors systematically compared TOPAS simulations with measurements that are performed routinely within the quality assurance (QA) program in our institution as well as experiments specifically designed for this validation study. First, the authors compared TOPAS simulations with measurements of depth-dose curves for spread-out Bragg peak (SOBP) fields. Second, absolute dosimetry simulations were benchmarked against measured machine output factors (OFs). Third, the authors simulated and measured 2D dose profiles and analyzed the differences in terms of field flatness and symmetry and usable field size. Fourth, the authors designed a simple experiment using a half-beam shifter to assess the effects of multiple Coulomb scattering, beam divergence, and inverse square attenuation on lateral and longitudinal dose profiles measured and simulated in a water phantom. Fifth, TOPAS’ capabilities to simulate time dependent beam delivery was benchmarked against dose rate functions (i.e., dose per unit time vs time) measured at different depths inside an SOBP field. Sixth, simulations of the charge deposited by protons fully stopping in two different types of multilayer Faraday cups (MLFCs) were compared with measurements to benchmark the nuclear interaction models used in the simulations. Results: SOBPs’ range and modulation width were reproduced, on average, with an accuracy of +1, −2 and ±3 mm, respectively. OF simulations reproduced measured data within ±3%. Simulated 2D dose-profiles show field flatness and average field radius within ±3% of measured profiles. The field symmetry resulted, on average in ±3% agreement with commissioned profiles. TOPAS accuracy in reproducing measured dose profiles downstream the half beam shifter is better than 2%. Dose rate function simulation reproduced the measurements within ∼2% showing that the four-dimensional modeling of the passively modulation system was implement correctly and millimeter accuracy can be achieved in reproducing measured data. For MLFCs simulations, 2% agreement was found between TOPAS and both sets of experimental measurements. The overall results show that TOPAS simulations are within the clinical accepted tolerances for all QA measurements performed at our institution. Conclusions: Our Monte Carlo simulations reproduced accurately the experimental data acquired through all the measurements performed in this study. Thus, TOPAS can reliably be applied to quality assurance for proton therapy and also as an input for commissioning of commercial treatment planning systems. This work also provides the basis for routine clinical dose calculations in patients for all passive scattering proton therapy centers using TOPAS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

ULTRADEEP IRAC IMAGING OVER THE HUDF AND GOODS-SOUTH: SURVEY DESIGN AND IMAGING DATA RELEASE

The IRAC ultradeep field and IRAC Legacy over GOODS programs are two ultradeep imaging surveys at 3.6 and 4.5 μm with the Spitzer Infrared Array Camera (IRAC). The primary aim is to directly detect the infrared light of reionization epoch galaxies at z > 7 and to constrain their stellar populations. The observations cover the Hubble Ultra Deep Field (HUDF), including the two HUDF parallel fields, and the CANDELS/GOODS-South, and are combined with archival data from all previous deep programs into one ultradeep data set. The resulting imaging reaches unprecedented coverage in IRAC 3.6 and 4.5 μm ranging from >50 hr over 150 arcmin{sup 2}, >100 hr over 60 sq arcmin{sup 2}, to ∼200 hr over 5–10 arcmin{sup 2}. This paper presents the survey description, data reduction, and public release of reduced mosaics on the same astrometric system as the CANDELS/GOODS-South Wide Field Camera 3 (WFC3) data. To facilitate prior-based WFC3+IRAC photometry, we introduce a new method to create high signal-to-noise PSFs from the IRAC data and reconstruct the complex spatial variation due to survey geometry. The PSF maps are included in the release, as are registered maps of subsets of the data to enable reliability and variability studies. Simulations show that the noise in the ultradeep IRAC images decreases approximately as the square root of integration time over the range 20–200 hr, well below the classical confusion limit, reaching 1σ point-source sensitivities as faint as 15 nJy (28.5 AB) at 3.6 μm and 18 nJy (28.3 AB) at 4.5 μm. The value of such ultradeep IRAC data is illustrated by direct detections of z = 7–8 galaxies as faint as H{sub AB} = 28.

79 ASTRONOMY AND ASTROPHYSICS↗

Final report : testing and evaluation for solar hot water reliability.

Solar hot water (SHW) systems are being installed by the thousands. Tax credits and utility rebate programs are spurring this burgeoning market. However, the reliability of these systems is virtually unknown. Recent work by Sandia National Laboratories (SNL) has shown that few data exist to quantify the mean time to failure of these systems. However, there is keen interest in developing new techniques to measure SHW reliability, particularly among utilities that use ratepayer money to pay the rebates. This document reports on an effort to develop and test new, simplified techniques to directly measure the state of health of fielded SHW systems. One approach was developed by the National Renewable Energy Laboratory (NREL) and is based on the idea that the performance of the solar storage tank can reliably indicate the operational status of the SHW systems. Another approach, developed by the University of New Mexico (UNM), uses adaptive resonance theory, a type of neural network, to detect and predict failures. This method uses the same sensors that are normally used to control the SHW system. The NREL method uses two additional temperature sensors on the solar tank. The theories, development, application, and testing of both methods are described in the report. Testing was performed on the SHW Reliability Testbed at UNM, a highly instrumented SHW system developed jointly by SNL and UNM. The two methods were tested against a number of simulated failures. The results show that both methods show promise for inclusion in conventional SHW controllers, giving them advanced capability in detecting and predicting component failures.

14 SOLAR ENERGY↗

Common practices for quantifying methane emissions from plumes detected by remote sensing

This document provides a set of community-accepted practices for quantifying methane emissions based on plumes detected via spectroscopic remote sensing. Its primary goal is to promote consistency in the generation, validation, reporting, and quality assessment of methane emission estimates derived from remote sensing radiances. Developed by subject matter experts with deep experience across all stages of the measurement process, this guidance reflects a critical evaluation of current methodologies and highlights key practices needed to produce reliable, interoperable, and traceable products. The focus is specifically on methane emissions quantified from distinct plumes originating from localized sources, rather than diffuse emissions spread over large regions, which are beyond the scope of this work. This document is intended to serve both data producers and users. For producers, it offers a framework for aligning with field-recognized standards to ensure their outputs meet rigorous quality and transparency criteria. For users, it provides a reference to assess dataset fitness-for-purpose by highlighting essential metadata, assumptions, and methodological choices that underpin emission estimates. By fostering a shared understanding of best practices, this work aims to enhance comparability, confidence, and utility of remotely sensed methane emission products.

54 ENVIRONMENTAL SCIENCES↗

Steady and unsteady transonic small disturbance analysis of realistic aircraft configurations

A transonic unsteady aerodynamic and aeroelasticity code CAP-TSD (Computational Aeroelasticity Program-Transonic Small Disturbance) has been developed for application to realistic aircraft configurations. The code uses a time-accurate approximate factorization (AF) algorithm for solution of the unsteady transonic small-disturbance potential equation. The paper gives an overview of the CAP-TSD code development effort and reports on recent algorithm modifications. The algorithm modifications include: an Engquist-Osher (E-O) type-dependent switch to treat regions of supersonic flow, extension of the E-O switch for second-order spatial accuracy, nonisentropic effects to treat strong-shock cases, nonreflecting far field boundary conditions for unsteady applications, and several modifications to accelerate convergence to steady state. The modifications have significantly improved the stability of the AF algorithm and hence the reliability of the CAP-TSD code in general. Calculations are also presented from a flutter analysis of a 45-deg sweptback wing which agree well with experimental data. The paper present descriptions of the CAP-TSD code and algorithm details along with results.

Batina, John T.↗

Quantification of Numerical Uncertainty via Nonlinear Dynamical Approach

Motivations (Ensure a Higher Level of Confidence in the Predictability & Reliability of Numerical Simulation for Multiscale Complex Nonlinear Fluid Problems) - The last two decades have been an era when computation is ahead of analysis & when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems & non-traditional fields (Especially when computations offer the ONLY way of generating this type of data limited simulations). - At present some of the numerical uncertainties can be explained and minimized by traditional numerical analysis and standard CFD practices. However, such practices, usually based on linearized analysis, MIGHT NOT be sufficient for strongly nonlinear and/or stiff problems. - We need a good understanding of the nonlinear behavior of numerical schemes being used as an integral part of code verification, validation and certification.

HEC↗

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗

A Convolution Neural Network for Voltage Event Classification at a Photovoltaic Inverter

This paper presents a convolutional neural network (CNN) developed to identify voltage events in photovoltaic (PV) inverters. The CNN is trained on synthetic data generated using the IEEE 13-bus distribution feeder model and evaluated on field measured data collected from Energy Northwest’s Horn Rapids Solar, Storage, and Training (HRSST) facility. The study focuses on two common voltage events: faults and voltage sags. The CNN is configured to analyze voltage and current waveforms from three-phase PV systems, demonstrating excellent accuracy during training. Field data from the HRSST facility is employed to assess its real-world performance, where the CNN achieves perfect identification of faults and voltage sags in a sample of nine events. This work highlights the potential of the proposed method to enhance PV protection schemes, providing a robust foundation for improved voltage event detection and grid reliability.

Cornachione, Matthew A.↗

Identification of Performance Shaping Factor Lag and Linger Effects for Dynamic Human Reliability Analysis: Application of Experimental Data

Many researchers have emphasized the importance of dynamic probabilistic safety assessment (PSA), which highlights the necessity of studies for dynamic human reliability analysis (HRA). Dynamic HRA concentrates on a dynamic account of human actions or how performance shaping factors (PSFs) can dynamically modify the human error probability (HEP) over time. In contrast, existing static HRA does not consider human actions as changes over time or event progressions. Accordingly, previous research on dynamic HRA conceptually suggested PSF lag and linger effects to treat dependence between operator actions in dynamic HRA versus existing approaches. As follow-up research, this study attempted to identify PSF lag and linger effects for dynamic HRA on the basis of experimental data. Firstly, mathematical models for PSF lag and linger effects were developed based on a literature survey in the field of biology. Secondly, we analyzed experimental scenarios from a control room study to identify operator actions considered in PSA. Lastly, based on the experimental data, the effect of the stress PSF with lag and linger effects was compared to that without PSF lag and linger effects. This paper concludes with an overall discussion of PSF lag and linger effects based on the relation between the stress PSF and error occurrence.

99 GENERAL AND MISCELLANEOUS↗

STAR COUNT DENSITY PROFILES AND STRUCTURAL PARAMETERS OF 26 GALACTIC GLOBULAR CLUSTERS

We used an appropriate combination of high-resolution Hubble Space Telescope observations and wide-field, ground-based data to derive the radial stellar density profiles of 26 Galactic globular clusters from resolved star counts (which can be all freely downloaded on-line). With respect to surface brightness (SB) profiles (which can be biased by the presence of sparse, bright stars), star counts are considered to be the most robust and reliable tool to derive cluster structural parameters. For each system, a detailed comparison with both King and Wilson models has been performed and the most relevant best-fit parameters have been obtained. This collection of data represents the largest homogeneous catalog collected so far of star count profiles and structural parameters derived therefrom. The analysis of the data of our catalog has shown that (1) the presence of the central cusps previously detected in the SB profiles of NGC 1851, M13, and M62 is not confirmed; (2) the majority of clusters in our sample are fit equally well by the King and the Wilson models; (3) we confirm the known relationship between cluster size (as measured by the effective radius) and galactocentric distance; (4) the ratio between the core and the effective radii shows a bimodal distribution, with a peak at {approx}0.3 for about 80% of the clusters and a secondary peak at {approx}0.6 for the remaining 20%. Interestingly, the main peak turns out to be in agreement with that expected from simulations of cluster dynamical evolution and the ratio between these two radii correlates well with an empirical dynamical-age indicator recently defined from the observed shape of blue straggler star radial distribution, thus suggesting that no exotic mechanisms of energy generation are needed in the cores of the analyzed clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

Model-less Source Location for Forced Oscillation based on Synchrophasor and Moving Fast Fourier Transformation

Forced oscillations in power systems occur when the grid is driven by an external and periodic force. To quickly detect and locate the source of the forced oscillation is critical in terms of ensuring the reliability of an interconnected power grid. This paper explores the electromechanical wave propagation theory and the Fast Fourier Transformation to analyze the forced oscillations. It proposes a model-less, adaptive, fast, and accurate source location algorithm. The proposed algorithm is extensively evaluated through simulation data from a 70k-bus U.S. Eastern Interconnection test system and field-collected synchrophasor data from the distribution-level wide-area monitoring system, FNET/GridEye. The evaluation results demonstrate the correctness and effectiveness of the proposed model-less forced oscillation source location algorithm.

Wang, Weikang↗

Further studies with data collected by NASA's airborne Doppler lidar in Oklahoma in 1981

Continued study of the lidar data collected in 1981 has resulted in significant new improvements in the analysis techniques reported by Bluestein et al. (1985) and McCaul (1985). Through comparison of fore- and aft-derived scalar fields of intensity and spectral width, the self-consistency of the lidar moment estimates was assessed. Reflectivity estimates were found to be quite stable and reliable, while spectral widths were prone to become noisy if signal to noise ratio (SNR) fell below 12 dB. In addition, spectral widths contained a significant component due to radial velocity gradients in areas along gust fronts, and these components were different along the fore and aft lines of sight. Significant improvement in agreement between the fore and aft fields of spectral width was obtained by estimating the radial velocity gradient component and then removing it from the raw measured widths to yield only the turbulent portion of the contribution to width. Additional analyses showed that lidar-derived vorticity estimates were consistent with several approximate models of vorticity growth along gust front zones, and with the hypothesis that Helmholtz instability could have been responsible for vortices seen along part of the gust front of 30 June 1981. Computations of divergence transverse to axes through an isolated cumulus congestus indicated that the strongest convergence tended to lie along an axis parallel to the congestus. This and the results of other additional analyses seem to suggest that the lidar winds do indeed accurately reflected the basic features of the real wind field.

Bluestein, H. B.↗

Statistical analysis and use of VAS radiance data

Researchers goals are to describe the information content of Vertical Atmospheric Sounder (VAS) radiance data, especially the 6.7 micrometers water vapor channel, to better interpret the atmosphere's water vapor structure from 6.7 micrometers imagery, and to investigate new analysis and forecasting techniques utilizing retrieved VAS soundings. Researchers made major progress toward these goals during FY-85. They are investigating 6.7 micrometer imagery on 6 to 7 March 1982, a day when special mesoscale ground truth data were collected during the 1982 atmospheric variability experiment/vertical amospheric sounder (AVE/VAS) field experiment. A dark (dry) image streak having mesoscale details was located over the special data region, and it provides the major focus of the case study. Mesoscale radiosonde-derived humidity data are found to verify fine scale features of the image that are not evident from the standard National Weather Service network. Thus, VAS imagery is a reliable detector of mesoscale moisture structure during this case. To investigate causes for the image streak, researchers are calculating water vapor budgets. Subsidence is found to be a factor in the current case as well; however, patterns of descent are not related to the jet streak according to traditional conceptual models. Thus, it appears that more research into jet stream dynamics is needed in order to better interpret 6.7 micrometer imagery.

Fuelberg, H. E.↗

Energy Efficient Engine exhaust mixer model technology report addendum; phase 3 test program

The Phase 3 exhaust mixer test program was conducted to explore the trends established during previous Phases 1 and 2. Combinations of mixer design parameters were tested. Phase 3 testing showed that the best performance achievable within tailpipe length and diameter constraints is 2.55 percent better than an optimized separate flow base line. A reduced penetration design achieved about the same overall performance level at a substantially lower level of excess pressure loss but with a small reduction in mixing. To improve reliability of the data, the hot and cold flow thrust coefficient analysis used in Phases 1 and 2 was augmented by calculating percent mixing from traverse data. Relative change in percent mixing between configurations was determined from thrust and flow coefficient increments. The calculation procedure developed was found to be a useful tool in assessing mixer performance. Detailed flow field data were obtained to facilitate calibration of computer codes.

Larkin, M. J.↗

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

Extra Dimensions: 3D and Time in PDF Documentation

Experimental science is replete with multi-dimensional information which is often poorly represented by the two dimensions of presentation slides and print media. Past efforts to disseminate such information to a wider audience have failed for a number of reasons, including a lack of standards which are easy to implement and have broad support. Adobe's Portable Document Format (PDF) has in recent years become the de facto standard for secure, dependable electronic information exchange. It has done so by creating an open format, providing support for multiple platforms and being reliable and extensible. By providing support for the ECMA standard Universal 3D (U3D) file format in its free Adobe Reader software, Adobe has made it easy to distribute and interact with 3D content. By providing support for scripting and animation, temporal data can also be easily distributed to a wide, non-technical audience. We discuss how the field of radiation imaging could benefit from incorporating full 3D information about not only the detectors, but also the results of the experimental analyses, in its electronic publications. In this article, we present examples drawn from high-energy physics, mathematics and molecular biology which take advantage of this functionality. We demonstrate how 3D detector elements can be documented, using either CAD drawings or other sources such as GEANT visualizations as input.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A status review of photovoltaic power conversion equipment reliability, safety, and quality assurance protocols

Data indicate that the inverter is the element of the photovoltaic plant that has the highest number of service calls and the greatest operation and maintenance cost burden. This paper describes the projects and relevant background needed in developing design qualification standards that would serve to establish a minimum level of reliability, along with a review of photovoltaic inverter quality and safety standards, most of which are in their infancy. We compare stresses and levels for accelerated testing of inverters proposed in the standard drafts, and those proposed by manufacturers and purchasers of inverters. We also review bases for the methods, stress types, and stress levels for durability testing of key inverter components. Many of the test protocols appear to need more comprehensive inclusion of stress factors existing in the natural environment such as wind driven rain, dust, and grid disturbances. Further understanding of how temperature, humidity ingress, and voltage bias affect the inverters and their components is also required. We provide data indicating inconsistent quality of the inverters and the durability of components leading to greater cost for the photovoltaic plant operator. Accordingly, the recommendation for data collection within quality standards for obtaining cost of ownership metrics is made. Design validation testing using realistic operation, environmental, and connection conditions, including under end-use field conditions with feedback for continuous improvement is recommended for inclusion within a quality standard.

14 SOLAR ENERGY↗