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At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Comparison of GEMS in interplanetary dust particles and GEMS ‐like objects in a Stardust impact track in aerogel

Abstract Comet 81P/Wild 2 dust, the first comet sample of known provenance, was widely expected to resemble anhydrous chondritic porous ( CP ) interplanetary dust particles ( IDP s). GEMS , distinctly characteristic of CP IDP s, have yet to be unambiguously identified in the Stardust mission samples despite claims of likely candidates. One such candidate is Stardust impact track 57 “Febo” in aerogel, which contains fine‐grained objects texturally and compositionally similar to GEMS . Their position adjacent the terminal particle suggests that they may be indigenous, fine‐grained, cometary material, like that in CP IDP s, shielded by the terminal particle from damage during deceleration from hypervelocity. Dark‐field imaging and multidetector energy‐dispersive X‐ray mapping were used to compare GEMS ‐like‐objects in the Febo terminal particle with GEMS in an anhydrous, chondritic IDP . GEMS in the IDP are within 3× CI (solar) abundances for major and minor elements. In the Febo GEMS ‐like objects, Mg and Ca are systematically and strongly depleted relative to CI ; S and Fe are somewhat enriched; and Au, a known aerogel contaminant, is present, consistent with ablation, melting, abrasion, and mixing of the SiO x aerogel with crystalline Fe‐sulfide and minor enstatite, high‐Ni sulfide, and augite identified by elemental mapping in the terminal particle. Thus, GEMS ‐like objects in “caches” of fine‐grained debris abutting terminal particles are most likely deceleration debris packed in place during particle transit through the aerogel.

Ishii, Hope A.↗

DOE OSTI2021

A Multi-Objective Bayesian Optimization Approach Using the Weighted Tchebycheff Method

Abstract Bayesian optimization (BO) is a low-cost global optimization tool for expensive black-box objective functions, where we learn from prior evaluated designs, update a posterior surrogate Gaussian process model, and select new designs for future evaluation using an acquisition function. This research focuses upon developing a BO model with multiple black-box objective functions. In the standard multi-objective (MO) optimization problem, the weighted Tchebycheff method is efficiently used to find both convex and non-convex Pareto frontiers. This approach requires knowledge of utopia values before we start optimization. However, in the BO framework, since the functions are expensive to evaluate, it is very expensive to obtain the utopia values as a prior knowledge. Therefore, in this paper, we develop a MO-BO framework where we calibrate with multiple linear regression (MLR) models to estimate the utopia value for each objective as a function of design input variables; the models are updated iteratively with sampled training data from the proposed MO-BO. These iteratively estimated mean utopia values are used to formulate the weighted Tchebycheff MO acquisition function. The proposed approach is implemented in two numerical test examples and one engineering design problem of optimizing thin tube geometries under constant loading of temperature and pressure, with minimizing the risk of creep-fatigue failure and design cost, along with risk-based and manufacturing constraints. Finally, the model accuracy with frequentist, Bayesian and without MLR-based calibration are compared to true Pareto solutions.

Engineering↗

DOE OSTI2015

WE-G-204-05: Relative Object Detectability Evaluation of a New High Resolution A-Se Direct Detection System Compared to Indirect Micro-Angiographic Fluoroscopic (MAF) Detectors

Purpose: To evaluate the task specific imaging performance of a new 25µm pixel pitch, 1000µm thick amorphous selenium direct detection system with CMOS readout for typical angiographic exposure parameters using the relative object detectability (ROD) metric. Methods: The ROD metric uses a simulated object function weighted at each spatial frequency by the detectors’ detective quantum efficiency (DQE), which is an intrinsic performance metric. For this study, the simulated objects were aluminum spheres of varying diameter (0.05–0.6mm). The weighted object function is then integrated over the full range of detectable frequencies inherent to each detector, and a ratio is taken of the resulting value for two detectors. The DQE for the 25µm detector was obtained from a simulation of a proposed a-Se detector using an exposure of 200µR for a 50keV x-ray beam. This a-Se detector was compared to two microangiographic fluoroscope (MAF) detectors [the MAF-CCD with pixel size of 35µm and Nyquist frequency of 14.2 cycles/mm and the MAF-CMOS with pixel size of 75µm and Nyquist frequency of 6.6 cycles/mm] and a standard flat-panel detector (FPD with pixel size of 194µm and Nyquist frequency of 2.5cycles/mm). Results: ROD calculations indicated vastly superior performance by the a-Se detector in imaging small aluminum spheres. For the 50µm diameter sphere, the ROD values for the a-Se detector compared to the MAF-CCD, the MAF-CMOS, and the FPD were 7.3, 9.3 and 58, respectively. Detector performance in the low frequency regime was dictated by each detector’s DQE(0) value. Conclusion: The a-Se with CMOS readout is unique and appears to have distinctive advantages of incomparable high resolution, low noise, no readout lag, and expandable design. The a-Se direct detection system will be a powerful imaging tool in angiography, with potential break-through applications in diagnosis and treatment of neuro-vascular disease. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

SU-C-209-05: Monte Carlo Model of a Prototype Backscatter X-Ray (BSX) Imager for Projective and Selective Object-Plane Imaging

Purpose: To develop a Monte Carlo N-Particle (MCNP) model for the validation of a prototype backscatter x-ray (BSX) imager, and optimization of BSX technology for medical applications, including selective object-plane imaging. Methods: BSX is an emerging technology that represents an alternative to conventional computed tomography (CT) and projective digital radiography (DR). It employs detectors located on the same side as the incident x-ray source, making use of backscatter and avoiding ring geometry to enclose the imaging object. Current BSX imagers suffer from low spatial resolution. A MCNP model was designed to replicate a BSX prototype used for flaw detection in industrial materials. This prototype consisted of a 1.5mm diameter 60kVp pencil beam surrounded by a ring of four 5.0cm diameter NaI scintillation detectors. The imaging phantom consisted of a 2.9cm thick aluminum plate with five 0.6cm diameter holes drilled halfway. The experimental image was created using a raster scanning motion (in 1.5mm increments). Results: A qualitative comparison between the physical and simulated images showed very good agreement with 1.5mm spatial resolution in plane perpendicular to incident x-ray beam. The MCNP model developed the concept of radiography by selective plane detection (RSPD) for BSX, whereby specific object planes can be imaged by varying kVp. 10keV increments in mean x-ray energy yielded 4mm thick slice resolution in the phantom. Image resolution in the MCNP model can be further increased by increasing the number of detectors, and decreasing raster step size. Conclusion: MCNP modelling was used to validate a prototype BSX imager and introduce the RSPD concept, allowing for selective object-plane imaging. There was very good visual agreement between the experimental and MCNP imaging. Beyond optimizing system parameters for the existing prototype, new geometries can be investigated for volumetric image acquisition in medical applications. This material is based upon work supported under an Integrated University Program Graduate Fellowship sponsored by the Department of Energy Office of Nuclear Energy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

On the determination of the electromagnetic field upon scattering by a small inhomogeneous spherical object

An efficient and fairly simple method of solving the problem of the incidence of a plane electromagnetic wave on an inhomogeneous object with specified spherically symmetric distributions of its electric permittivity and magnetic permeability is presented. The fields inside the object and the integrated scattering and absorption cross sections are found by assuming the object to be small compared to the vacuum wavelength. Since no constraints are imposed on the scales of the fields inside the object, the method is suitable for investigating complex cases, including those associated with the local amplification and absorption of the electromagnetic field in inhomogeneous resonant media.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Flexible and Effective Object Tiering for Heterogeneous Memory Systems

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory management, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide memory tiering. The framework includes tools to monitor the capacity and usage of individual data objects, routines that aggregate and convert this information into tier recommendations for the host platform, and mechanisms to enforce these recommendations according to user-selected policies. Moreover, the developed tools and techniques are fully automatic, work on standard Linux systems, and do not require modification or recompilation of existing software. Using this framework, this study evaluates and compares the impact of a variety of design choices for memory tiering, including different policies for prioritizing objects for the fast memory tier as well as the frequency and timing of migration events. In conclusion, the results, collected on a modern Intel platform with conventional DDR4 SDRAM as well as Intel Optane NVRAM, show that guiding data tiering with object-level information can enable significant performance and efficiency benefits compared with standard hardware- and software-directed data-tiering strategies for a diverse set of memory-intensive workloads.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Downscaling↗

DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

Environmental sciences↗

DOE OSTI2016

Investigation of the Residual in Column-Integrated Atmospheric Energy Balance Using Cloud Objects

Observationally based atmospheric energy balance is analyzed using Clouds and the Earth’s Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over the tropics and positive over midlatitudes. A negative residual implies that the precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud-object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over the western Pacific are 0.84, 0.95, and 0.93, respectively. However, when all energy components are added, the atmospheric energy residual over the tropical Pacific is temporally correlated well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus alters not enough atmospheric energy compared to the residual, this suggests the following: 1) if retrieval errors associated with deep convective clouds are causing the column-integrated atmospheric energy residual, the errors vary among individual deep convective clouds, and 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over the tropical western Pacific.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

A Python Object Oriented & Data Driven Testing Infrastructure for an Environmental Information Management System

Software systems such as TEIMS, the Taurus Environmental Information Management System evolve in size and complexity making manual testing no longer sufficient or feasible, becoming a performance and quality risk. TEIMS is a system of systems comprised of dynamic, data-driven web-based applications that support planning, operational monitoring, data collection, sample management, reporting and, scientific findings for LLNL’s Environmental Restoration Department (ERD). Selenium’s Integrated Development Environment (IDE) was previously used to support TEIMS testing. An approach with limited flexibility for future software development. As a student intern I was assigned the task to develop an object oriented testing infrastructure for TEIMS. A critical resource in this approach is the development of a catalogue of page elements. To accomplish this I created a comma separated value file, which is comprised of key identifiers based on page elements. Using the Python language and the Selenium Web driver I then developed the object mapping structure, which serves as a wrapper for exposure of each element allowing interaction with the tests and test suites. A master driver “Module” allowed the web driver to be shared among the objects and tests. I then developed a web-based graphical user interface (GUI) for test history, metrics and searching. This data driven approach provides flexibility and extensibility, allowing changes to the structure to be performed in a single place. The result is an object oriented/data driven infrastructure that allows tests to be simpler, flexible, and maintainable, with searchable results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Measurements Conducted on an Unknown Object Labeled Pu-239

Measurements were carried out on 12 November 2013 to determine whether Pu-239 was present on an object discovered in a plastic bag with label “Pu-239 6 uCi.” Following initial survey measurements to verify that the object was not leaking or contaminated, spectra were collected with a High Purity Germanium (HPGe) detector with object positioned in two different configurations. Analysis of the spectra did not yield any direct evidence of Pu-239. From the measured spectra, minimum detectable activity (MDA) was determined to be approximately 2 uCi for the gamma-ray measurements. Although there was no direct evidence of Pu-239, a peak at 60 keV characteristic of Am-241 decay was observed. Since it is very likely that Am-241 would be present in aged plutonium samples, this was interpreted as indirect evidence for the presence of plutonium on the object. Analysis of this peak led to an estimated Pu-239 activity of 0.02–0.04 uCi, or <1x10 -6 grams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Additive Manufacturing of Dense Hexagonal Boron Nitride Objects

The feasibility of manufacturing hexagonal boron nitride objects via additive manufacturing techniques was investigated. It was demonstrated that it is possible to hot-extrude thermoplastic filaments containing uniformly distributed boron nitride particles with a volume concentration as high as 60% and that these thermoplastic filaments can be used as feedstock for 3D-printing objects using a fused deposition system. Objects 3D-printed by fused deposition were subsequently sintered at high temperature to obtain dense ceramic products. In a parallel study the behavior of hexagonal boron nitride in aqueous solutions was investigated. It was shown that the addition of a cationic dispersant to an azeotrope enabled the formulation of slurries with a volume concentration of boron nitride as high as 33%. Although these slurries exhibited complex rheological behavior, the results from this study are encouraging and provide a pathway for manufacturing hexagonal boron nitride objects via robocasting.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Grid-scale Energy Storage Hazard Analysis & Design Objectives for System Safety

Battery based energy storage systems are becoming a critical part of a modernized, resilient power system. However, batteries have a unique combination of hazards that can make design and engineering of battery systems difficult. This report presents a systematic hazard analysis of a hypothetical, grid scale lithium-ion battery powerplant to produce sociotechnical "design objectives" for system safety. We applied system's theoretic process analysis (STPA) for the hazard analysis which is broken into four steps: purpose definition, modeling the safety control structure, identifying unsafe control actions, and identifying loss scenarios. The purpose of the analysis was defined as to prevent event outcomes that can result in loss of battery assets due to fires and explosions, loss of health or life due to battery fires and explosions, and loss of energy storage services due to non- operational battery assets. The STPA analysis resulted in identification of six loss scenarios, and their constituent unsafe control actions, which were used to define a series of design objectives that can be applied to reduce the likelihood and severity of thermal events in battery systems. These design objectives, in all or any subset, can be utilized by utilities and other industry stakeholders as "design requirements" in their storage request for proposals (RFPs) and for evaluation of proposals. Further, these design objectives can help to protect firefighters and bring a system back to full functionality after a thermal event. We also comment on the hazards of flow battery technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

How Low Can You Go? Using Synthetic 3D Imagery to Drastically Reduce Real-World Training Data for Object Detection

Deep convolutional neural networks (DCNNs) currently provide state-of-the-art performance on image classification and object detection tasks, and there are many global security mission areas where such models could be extremely useful. Crucially, the success of these models is driven in large part by the widespread availability of high-quality open source data sets such as Image Net, Common Objects in Context (COCO), and KITTI, which contain millions of images with thousands of unique labels. However, global security relevant objects-of-interest can be difficult to obtain: relevant events are low frequency and high consequence; the content of relevant images is sensitive; and adversaries and proliferators seek to obscure their activities. For these cases where exemplar data is hard to come-by, even fine-tuning an existing model with available data can be effectively impossible. Recent work demonstrated that models can be trained using a combination of real-world and synthetic images generated from 3D representations; that such models can exceed the performance of models trained using real-world data alone; and that the generated images need not be perfectly realistic (Tremblay, et al., 2018). However, this approach still required hundreds to thousands of real-world images for training and fine tuning, which for sparse, global security-relevant datasets can be an unrealistic hurdle. In this research, we validate the performance and behavior of DCNN models as we drive the number of real-world images used for training object detection tasks down to a minimal set. We perform multiple experiments to identify the best approach to train DCNNs from an extremely small set of real-world images. In doing so, we: Develop state-of-the-art, parameterized 3D models based on real-world images and sample from their parameters to increase the variance in synthetic image training data; Use machine learning explainability techniques to highlight and correct through targeted training the biases that result from training using completely synthetic images; and Validate our results by comparing the performance of the models trained on synthetic data to one another, and to a control model created by fine-tuning an existing ImageNet-trained model with a limited number (hundreds) of real-world images.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform

LWRS M3 milestone report due September 15, 2023. This report summarizes development and demonstration activities of PRLO optimization platform built in Risk Analysis and Virtual ENviroment (RAVEN), specifically: (1) Improvement of multi-objective non-dominated sorting genetic algorithm II (NSGA-II) to handle large size of objectives and constraints, (2) Demonstration of pressurized water reactor core design with NSGA-II multi-objective optimization platform, and (3) Single-objective optimized core design including system analysis and fuel performance feedback.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Progress on Long-Term Objectives for the Development of Advanced Reactor Mechanistic Source Term Modeling and Simulation Tools

To assist both the advanced reactor industry and U.S. Nuclear Regulatory Commission (NRC) in the pursuit of reactor design and licensing, the U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has established a mechanistic source term (MST) research project under the auspices of the Multiphysics Applications technical area. MST analysis is central to the reactor licensing process and a focus of the NRC regarding their mission to provide reasonable assurance of adequate protection of public health and safety and environment. The MST research project is a collaboration between Argonne National Laboratory (Argonne) and Sandia National Laboratories (SNL) with a high-level objective to coordinate the development of comprehensive advanced reactor MST mod/sim capabilities to support risk-informed design and licensing decisions. As part of this effort, an MST mod/sim development pathway was developed in FY21, which outlines the high-level objectives and near-term tasks necessary to achieve the project objectives. Since publication of the development pathway, Argonne and SNL have focused initial efforts on addressing the “near-term tasks” outlined in the report, and the current work provides a status update of the progress achieved in FY22. This report is a progress update on 6 tasks supporting molten salt reactor (MSR) and sodium fast reactor (SFR) MST analyses which were initiated in FY22 as recommended high priority near-term tasks. These tasks were continued into FY23 as they also support previously recommended long-term development objectives to advance MST analyses for these advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Object-oriented analysis as a foundation for building climate storylines of compounding short-term drought and crop heat stress

Introduction: Crops are vulnerable to precipitation and heat extremes during late spring through summer. Methods: We analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041- 2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap. Results: Identified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type. Discussion: The information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

54 ENVIRONMENTAL SCIENCES↗