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At least 1,801 records · Page 100

Incorporating uncertainty for enhanced leaderboard scoring and ranking in data competitions

Data competitions have become a popular and cost-effective approach for crowdsourcing versatile solutions from diverse expertise. Current practice relies on the simple leaderboard scoring based on a given set of competition data for ranking competitors and distributing the prize. However, a disadvantage of this practice in many competitions is that a slight difference in the scores due to the natural variability of the observed data could result in a much larger difference in the prize amounts. In this article, we propose a new strategy to quantify the uncertainty in the rankings and scores from using different data sets that share common characteristics with the provided competition data. By using a bootstrap approach to generate many comparable data sets, the new method has four advantages over current practice. Furthermore, during the competition, it provides a mechanism for competitors to get feedback about the uncertainty in their relative ranking. After the competition, it allows the host to gain a deeper understanding of the algorithm performance and their robustness across representative data sets. It also offers a transparent mechanism for prize distribution to reward the competitors more fairly with superior and robust performance. Finally, it has the additional advantage of being able to explore what results might have looked like if competition goals evolved from their original choices. The implementation of the strategy is illustrated with a real data competition hosted by Topcoder on urban radiation search.

42 ENGINEERING↗

Microstructure and strength of a thick-section gas-tungsten arc weld in cast Haynes® 282® alloy

A 50-mm deep gas tungsten arc weld was made with matching filler metal in cast Haynes 282 alloy. The narrow gap joint was filled with 104 weld beads. The weld deposit was of high quality with no visible indications of physical defects. The weld heat-affected zone was characterized by microcracking and localized recrystallization. Hardness testing showed that a softened region in the as-welded heat-affected zone was nearly eliminated by post-weld heat treatment. Tensile testing up to 816°C showed that cross-weld specimen strengths were about 80% of the yield strength of the original cast base metal. The rupture strengths of cross-weld specimens are within 20% of wrought base metal reference data.

36 MATERIALS SCIENCE↗

Time-of-Flight Estimation for Nondestructive Evaluation

Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the classical approaches to the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof apart under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high-qualitymeasurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current capabilities that must be achieved in order to satisfy the criticaldemands of the various LLNL programs.In itsbasic foundations, signal processing is essentially the “extraction of critical information (signals) from noisy, uncertain data.” Clearly, in a perfect world the best signal processing is none---just make a reliable, noise-free, uncertainty-free, measurement. Unfortunately, even the best of systems is still straddled within the confines and limitations of physical instrumentation. With this in mind, we discuss the development of signal processing techniques toextract the desired UT information from noisy measurement data. We start with a discussion of a simple homogeneous representation of a “part” under investigation and its insonification by an ultrasonicexcitation from a physics-based perspective. Once developed, we briefly discussthe various choices of excitation signals and their tradeoffs.Next,we discuss a simulation approach employing simple models from the signal processing perspective and then move on to the development of the basic signal processing approach to ultrasonic signal processing all based on estimating the pulse arrival estimation. Starting with simple peak detection techniques, progressing to the processing workhorse so-called “matched-filter” and finally to the more sophisticated “model-based matched filter.”The underlying pre-and post-processing of noisy measurement data along with the application of these techniques are subsequently demonstrated on experimental ultrasonic data.Finally, we present some results for processing “weld” data when the ultrasonic excitation signal is not directly available.

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A Comparative Study of Joint Modeling Methods and Analysis of Fasteners [Slides]

Motivation: Crucial aspect of mechanical design is joining methodology of parts. Ability to analyze joint and fasteners in system for structural integrity is fundamental. Different modeling representations of fasteners include spring, beam, and solid elements. Various methods compared for linear system to decide method appropriate for design study. New method for modeling fastener joint is explored from full system perspective. Analysis results match well with published experimental data for new method.

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Specification of EBR-II Contact Profilometry Data

All contact profilometry data stored in FIPD was originally measured using the HFEF vertical contact profilometer, which was an electronic gauge to measure the diameter profile of an element or capsule continuously over the region of interest. The element could be rotated as it passed through the probes if the wire wrap was not to be removed and the element could be returned to reactor for further irradiation. If the wire wrap was removed, the element could be drawn vertically through the probes, rotated, and the process repeated. In this way any cladding ovality could be observed. Figure 1 shows the setup used to measure the fuel pin diameter profile. The ambient temperature during the measurement was ~21-23 ºC. The cladding temperature during the measurement is considered to be similar to the ambient temperature by assuming the fuel decay heat did not impact the cladding temperature. Two documents contain most of the important details about contact profilometry measurements. The first one is the operational manual of the contact profilometer (title: Element contact profilometer operation and maintenance, HFEF/N OMM 4326, DOC. NO. W0202-0007-SA-01). This manual provides: (1) description of the contact profilometer including the functions of each component (support stage, sensing head, control system, and calibration standards, etc.); (2) step-by-step guidance on calibrations, operations, and measurements; and (3) maintenance procedures and other details of the contact profilometer. The second document is a publicly accessible report entitled “A Fuel-element Profilometer for the HFEF.” This report describes the development of the contact profilometer, including the design requirements, features, and details of each component, as well as the acceptance tests for the built system. This document is important because it reports the uncertainties of the measurements with detailed deduction procedures. The reported uncertainties should apply to all hard-copy contact profilometry data in FIPD. Some key information about contact profilometry measurements was extracted from these two documents. Combining the information with other sources, a specification for interpretating the contact profilometry data in FIPD was established.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

LLNL International Working Group on Gamma Spectrometry - Preparation of IDB Dataset [Slides]

The spectral information and associated metadata, including source information, detector setup, and shielding configuration is described in human readable, comma-separated text files (csv). Six csv files are associated with each material type and include the following information (where [Isotope] is U, Pu, and MOX): [Isotope]_measurement_metadata Metadata of the measurement configuration, including material composition at time of acquisition (decay corrected from certificate date). Data that is unique to a measurement configuration e.g. detector geometry, source-detector distance, analyzer and other electronics used, attenuating materials are provided in this file. [Isotope]_spectrum_metadata The information that is unique to the spectrum. This includes detector specifications (e.g. date of acquisition, number of channels, gain (keV/channel), energy range, real and live time, full width half-maximum (FWHM) of the 186 or 208 peak for uranium or plutonium measurements, respectively. [Isotope]_source_metadata The source material used for the measurement, this includes the ratio and uncertainties of isotopes present and processing information of the material. In addition, the certificate information for the source material is listed. [Isotope]_spectrum_counts_metadata The counts per channel for each spectrum. This data is linked via the UID.spectrum index to the measurement_metadata file. [Isotope]_spectrum_checksum_metadata The MD5 checksum for the original spectrum file. This data is linked via the UID.spectrum index to the measurement_metadata file. This information is provided to prevent duplication of entries in the database. [Isotope]_provenance Details on the csv data provider, including laboratory and contract information.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Biodegradable Temperature & pH Sensors VIASTIMULI-Responsive Polymers

Soil sensors play a key role in agriculture, and for good reason; knowledge about soil conditions enables farmers to make informed decisions about resource expenditure and crop selection for areas of land. On an industrial agriculture scale, though, this is difficult; the average U.S. farm is approximately 500 acres. To put that in perspective, if you’ve driven past Concannon Winery, all that land is only about 200 acres. This is why modern state-of-the-art soil sensors need to be equipped to not only collect precise and accurate data, but also to transmit that data large distances.

36 MATERIALS SCIENCE↗

Product Defect Detection System: SYSM- 5620 Final Project

Retail sales is a growing market estimated to up to seven percent year over year. With this growing market there is also a trend in growing rate of retail returns, estimated just last year at $\$$850 billion. Retail stores must ensure that products available for purchase remain safe, undamaged, and acceptable to customers throughout their time in the store. This job exists regardless of the specific solution used because stores are always responsible for preventing damaged or defective products from reaching customers and when they fail to this is categorized under operation inefficiencies which accounts for an estimated $\$$12 billion in returns. When defective items remain on the sales floor, stores may experience increased returns, reduced customer satisfaction, loss of customer trust, and potential safety concerns depending on the product type. As a result, the core job to be done is to identify defective products quickly, remove them from the sales floor before they are purchased, and preserve useful information about the defect so that the store can improve its handling, stocking, and supplier coordination over time. The need for a more reliable process is especially important in high volume retail environments where employees manage large numbers of products across many aisles, shelves, and storage areas. In these settings, manual inspection alone can be inconsistent and difficult to sustain at the individual item level. At the same time, broader retail trends continue to emphasize operational efficiency, product visibility, and improved customer experience, creating an opportunity for more automated and data driven defect detection methods.

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(U)Vendor Sanitization Requirements – SIEMENS Control

This document defines the software requirements for the sanitization of the IPC and or the controller. The system is intended to manage part programs and associated data (e.g. simulations, probing data) by capturing metadata, securely sanitizing files, logging operations, backing up data to a defined path, deploying a user defined program to a controller, and restoring part programs and associated data when required.

42 ENGINEERING↗

Overview of Light Weight Radioisotope Heating Unit (LWRHU) User’s Guide

Idaho National Laboratory (INL) has recently compiled a user’s guide for the LightWeight Radioisotope Heating Unit (LWRHU). This guide gives an overview of the LWRHU to potential users. Information and data on mass properties, dimensions, thermal loads, and interfaces are discussed.

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Development of Numerical Model of Metal Foam with PCM for the Estimation of Effective Thermal Conductivity

Global warming due to climate change is a threat to humankind. Nuclear energy is one of the promising solutions to reduce fossil fuel usage. Nuclear energy can handle the base load, compensating for the volatility of renewable energy. If nuclear energy could achieve load following capability, the combination with renewable energy would be more suitable. Thermal energy storage (TES) is one of the options for enabling load following of nuclear reactors. The TES makes it possible to store surplus nuclear thermal energy and release it later as needed. In Idaho National Laboratory (INL), a new concept of latent heat TES integrated with high-temperature heat pipe has been proposed and is under development, which is called Heat pipe-Integrated Thermal Battery (HITB). HITB exchanges thermal energy between the reactor system and TES via heat pipe. The heat transferred to TES medium, made of phase change material (PCM), stores energy as sensible heat and/or latent heat. As PCM typically has poor thermal conductivity, however, various heat transfer enhancement techniques are required to achieve a rapid charging cycle. There are many techniques to enhance the heat transfer ability of TES medium such as disk, fin, and metal foam. Among them, metal foam is an appropriate option to enhance the heat transfer because it maximizes the heat transfer area through metal wicks. Metal foam is a lightweight metal structure that has a high porosity of over 0.9. The typical materials for metal foam are Aluminum, Copper, Nickel, and Silicon Carbide (SiC). Metal foam not only enhances heat transfer via conduction but also increases contact surface area. In the HITB design , the metal foam is being considered as one of the options to enhance the heat transfer of TES medium (PCM) [1]. To predict the enhanced thermal performance of TES, one should properly estimate the effective thermal conductivity of metal foam combined with PCM material or calculate heat transfer in distributed model. There are many experimental works that provides effective thermal conductivity of metal foam with various PCM [2,3]. Also, many theoretical models were developed based on the unit cell model of metal foam [4,5]. With a distributed model, on the other hand, detail heat transfer characteristics between metal foam and PCM material can be analyzed considering the geometry or buoyancy effect. However, due to the complex geometry of metal foam pores, the computational cost for three-dimensional modeling highly increases. Therefore, if metal foam structure can be modeled in simple and repetitive design, the computational cost would decrease Among the various metal foam models [2], lattice model is one of the simple and extendable design. The porosity and pores per inch (PPI) can be characterized by the size and spatial distance of lattice structure. If the three-dimensional metal foam model consists of lattice structure could properly estimate the heat transfer, which is characterized by effective thermal conductivity, it would be a good option to assess the thermal performance of metal foam with PCM. In this study, a three-dimensional numerical model was developed to simulate conductive heat transfer between metal foam and PCM. The three-dimensional lattice structure of square pillars was selected as a basic structure of the metal foam. The calculation result was characterized by the effective thermal conductivity of the whole domain. A sensitivity study was conducted for mesh size, domain size, and PPI to check whether the calculation result gives a converged result or not. Lastly, the effective thermal conductivity from the lattice model was compared with existing experimental data to validate the model result

25 ENERGY STORAGE↗

Dose Consequence and Probabilistic Risk Assessment Integration into Digital Documented Safety Analysis

This is an intern poster presentation. The current reactor authorization process is complex and error prone. The development of a digital Documented Safety Analysis has been proposed to provide an automated and integrated solution to enhance the design and authorization process. The digital DSA will consist of interlinked models, analyses, and reports, all of which will be updated using automated workflows when design changes are made. This poster examines the integration of the probabilistic risk assessment (PRA) with the transient and dose consequence analyses. A PRA for a generic high temperature gas-cooled reactor (HTGR) has been constructed which will drive the input parameters for a transient analysis model currently being constructed. Dose consequence will be determined using the results of the transient analysis and the Radiation Safety Analysis Computer (RSAC) code. Dose consequence data will then be input back into the PRA to drive design parameters.

42 ENGINEERING↗

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An experimental and computational analysis of combustion heat release transformation in dual fuel combustion

Dual fuel (DF) diesel-methane combustion, which employs a high-reactivity fuel (diesel) to ignite a low-reactivity fuel (methane), is a widely studied combustion strategy for internal combustion engines, with significant potential for engine-out emissions reductions without the need for major hardware modifications. A phenomenon, which has been reported in the DF literature, but not explained fully, is the transformation of the shape of the apparent heat release rate (AHRR) curve as the start of injection (SOI) of diesel is advanced beyond a certain threshold; coincidentally, this AHRR transformation is usually accompanied by a sharp decrease in engine-out emissions of oxides of nitrogen (NOx). The goal of the present work is to establish the underlying physical reason(s) that cause the AHRR transformation. The AHRR transformation was observed on a single cylinder research engine (SCRE) at an indicated mean effective pressure (IMEP) of 5 bar at a speed of 1500 rev/min. The transformation occurred over a range of SOIs from 330 to 320 crank angle degrees (CAD). While the 330 CAD SOI exhibited a typical two-stage AHRR curve, with a clearly definable first-stage peak followed by a second-stage AHRR with little-to-no low temperature heat release (LTHR) present and high engine-out NOx, the 320 CAD SOI exhibited a single-stage, Gaussian-like AHRR curve, with noticeable LTHR and at least one order-of-magnitude lower NOx emissions. Here, leveraging analysis of experimental data and three-dimensional computational fluid dynamic simulations, the authors show that the AHRR transformation is impacted mainly by differences in local equivalence ratio distributions within the cylinder at ignition onset for different diesel SOIs.

33 ADVANCED PROPULSION SYSTEMS↗

A Systems Engineering Analysis of National Ignition Facility Industrial Controls Systems and Safety Interlock Systems Remote Input/Output Networking Migration from ControlNet to EtherNet/IP

The ControlNet industrial communications protocol and modules used in the Industrial Control System (ICS) and Safety Interlock System (SIS) at the National Ignition Facility (NIF) are no longer necessary and the ICS and SIS would be better served by migrating the communications structure to use EtherNet/Industrial Protocol (IP) and EtherNet bridge modules instead. By the admission of the vendor of ControlNet hardware, Rockwell Automation, in literature by Bill Petro [1], “Moving forward, customers will be able to optimize their asset utilization better using EtherNet/IP protocol than with ControlNet.” The NIF is one of the key elements of the Inertial Confinement Fusion (ICF) program at Lawrence Livermore National Laboratory (LLNL), a federally funded research and development center (FFRDC). The NIF contains the systems and provides the operational capacity to perform ICF, high energy density (HED), and discovery science experiments utilizing 192 individual beamlines, a host of diagnostics, and all the industrial systems required to facilitate these beamlines and diagnostics. The industrial systems are governed by the ICS and SIS, with the ICS providing control and the SIS providing monitoring and permissives. Construction on the NIF began in 1997 and was certified complete in 2009 and, as a result, the ICS and SIS were developed during this time using the tools that were available then. This includes the communications structure and protocols for these systems, much of which was, and still is, ControlNet. ControlNet, particularly during the time that the ICS and SIS were being built, has several attractive features. ControlNet hardware is exclusive to Rockwell Automation, which was the automation hardware chosen for the ICS and SIS. One feature that could be considered an advantage or a disadvantage depending on the communication needs of the system is that ControlNet also utilizes no active network components, excluding repeaters which are not always necessary. According to the architect of the ICS system at the NIF, Gordon Lau, one of the most attractive features of the ControlNet protocol during development of the ICS and SIS was that it is deterministic, providing timing of data transfer that is executed exactly as it is defined by the developer.

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Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

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