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At least 307 records · Page 17

Requirements and Recommendations for a Physical Attack Characterization Framework

This study seeks to identify existing frameworks or develop requirements and recommendations for a new framework that can consistently characterize physical attacks, analogous to MITRE ATT&CK®. MITRE ATT&CK is widely used across government, research organizations, and the cyber security community to characterize cyber attack tactics, techniques, and procedures (TTPs) in a consistent and commonly understood manner. While physical attack taxonomies, methodologies, and other tools for evaluating physical security do exist, many are sector and/or facility-type specific—and therefore not able to provide comparable scenarios across sectors—or are more focused on security assessment instead of the characterization of attacks themselves. A MITRE ATT&CK analog for physical attacks on critical infrastructure would provide a common language and structure for analysis of physical attacks. Existing attack characterization methodologies do not robustly address cyber-physical security risks. To fully understand a facility’s security needs, it is important to understand the entire vulnerability landscape from both a physical and a cyber perspective. To underscore this need, organizations such as the Cybersecurity and Infrastructure Security Agency (CISA) are calling for a coordinated approach to cyber and physical security, which they refer to as cyber and physical security convergence. A physical attack characterization framework that could be used jointly with MITRE ATT&CK would help support a more robust analysis in support of convergence, enabling the consistent characterization of attacks that utilize both cyber and physical tactics and techniques. This could provide analysts and stakeholders with a clearer understanding of how security mitigations deployed in the physical realm impact security risks in the cyber realm, and vice versa. In this study, the project team evaluates existing physical security taxonomies and methodologies to assess whether an existing method can be used to create a “physical half” of MITRE ATT&CK. This study then provides requirements and recommendations for a framework that can leverage aspects of existing methodologies. The goal of the final framework is for it to be widely adopted and referenced, regardless of critical infrastructure sector, facility type, or facility components. This study also identifies applicable use cases for when and how a framework could be applied across the various critical infrastructure sectors for a variety of attack types or motivations. Through a literature review of existing security-focused methodologies and taxonomies, engagement with relative stakeholders, evaluation of potential physical attack framework use cases, and subsequent identification of requirements, this study identified the following key findings and recommendations: There is a need for a new physical attack characterization framework; A physical attack framework should be interoperable with the MITRE ATT&CK framework; A physical attack framework should be broadly applicable, but with detailed tactics, techniques, and procedures that encompass the entire attack path; A physical attack framework should be based on observed or feasible events; A physical attack framework should adapt features from existing methodologies, frameworks, and taxonomies; A physical attack framework should be owned, overseen, and maintained by one organization.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

EVSE Characterization: V2G EVSE Comparison

As part of the U.S. Department of Energy EVs@Scale consortium Next-Generation Profiles project, results and analysis from the characterization of high-power conductive and wireless charging infrastructure are presented. This characterization is conducted over a wide range of direct current (DC) current and DC voltage operation for nominal test conditions and off-nominal test conditions. Test plans and procedures were developed to define the test configurations and requirements, measurement parameters, and test procedures used throughout testing. Results from a 2024 study conducted on electric vehicle supply equipment (EVSE) characterization by the Idaho National Laboratory (INL) include two bi-directional vehicle-to-grid (V2G) capable EVSEs. These EVSE are referred to as V2G-EVSE9 and V2G-EVSE10. Laboratory testing is conducted at nominal test conditions to characterize the power transfer capabilities, efficiency, power factor, and other power quality metrics of the two DC EVSEs capable of V2G bi-directional power transfer. Results from testing show the performance is consistent for V2G-EVSE9 and V2G-EVSE10 when comparing charging to discharging performance, except for V2G-EVSE10 for power transfer when operating above 70% of the rated DC current. V2G-EVSE10 efficiency is >98% while charging and <91% while discharging at the same operating conditions, near maximum-rated current, at 300VDC. In contrast, V2G-EVSE9 results are consistent for charging and discharging. This EVSE is nearly 96% efficient while charging or discharging when operating over 50% of rated AC power. V2G EVSE performance is also characterized during off-nominal AC grid conditions involving AC voltage deviation (426 VAC to 518 VAC), AC frequency deviation of +2% (58.8 Hz to 61.2 Hz), and AC voltage harmonics injection. Many test conditions have little-to-no impact on performance characteristics of the two EVSEs; however, there are a few notable findings with significant power transfer capability impacts. AC voltage harmonics injection resulted in negative impacts on power quality attributes for both EVSEs, but with no impact on power transfer capability. Off-nominal AC voltage and frequency conditions resulted in unstable or lack of power transfer capability for both EVSEs. V2G-EVSE9 is unable to transfer power when AC voltage is >300V L-N. V2G-EVSE10 is unable to transfer power when AC frequency deviation exceeds +0.8%. V2G energy management system transient response and latency are quantified during laboratory testing. V2G-EVSE9 and V2G-EVSE10 utilize cloud-based V2G energy management systems that command the power transfer level between the EVSE and EV. The latency and response characteristics of the entire systems (web-based user interface, V2G energy management system, cellular communications, and EVSE response) are quantified through laboratory testing for V2G-EVSE9 and V2G-EVSE10. V2G-EVSE9 latency ranges from 0.8 to 1.8 seconds, whereas V2G-EVSE10 latency ranges from 3.4 to 8.8 seconds. The ramp rate to a change in power transfer request also differs between the two EVSEs. V2G-EVSE10 ramp rate ranges from 50% to -250% of rated AC power per second, whereas V2G-EVSE9 rate ranges from 95% to -95% of rated AC power per second. At the highest rate of change in power transfer, V2G-EVSE10 can change from full charge power to full discharge power in less than one second. The V2G EVSE characterization presented in this report provides valuable insights and results for use by numerous entities. This includes modeling and simulation organizations, decision makers, fleet planning, industry stakeholders, and many others involved with the development and deployment of electrified transportation technologies. Additional high-power DC chargers, bidirectional chargers, and inductive power transfer EVSE characterization results are anticipated from additional EVSE brands and models, which will be detailed in future publications in support of the U.S. Department of Energy EVs@Scale consortium Next-Gen Profiles project.

25 ENERGY STORAGE↗

Summary of Terra and Aqua MODIS On-orbit Calibration and Characterization Results

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's EOS Terra spacecraft has been in operation for more than seven years since its launch in December 1999 and the MODIS onboard Aqua spacecraft has been in operation for more than 4.5 years since its launch in May 2002. Compared to its heritage sensors, such as AVHRR, CZCS, SeaWiFS, HIRS, and Landsat TM, the MODIS instrument was developed with improved spectral and spatial resolutions, and temporal scale or global coverage frequency. The two MODIS instruments are nearly identical with each collecting data in 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2jm and 16 thermal emissive bands (TEB) from 3.7 to 4.4 microns. MODIS makes the Earth view observations with a scan angle range of +/-55 degree relative to instrument nadir and at three nadir spatial resolutions: 0.25km for bands 1-2.05km for bands 3-7, and 1km for bands 8-36, thus enabling complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS observations have been routinely used to generate a broad range of science data products that are widely distributed and extensively applied for the studies of the Earth's land, oceans, and atmosphere and for the monitoring of climate and environmental changes. It is obvious that the MODIS science data product quality strongly relies on sensor on-orbit performance and its capability of continuously tracking sensor response changes over time. Because of this, each MODIS was built with a comprehensive set of on-board calibrators (OBC) that include a solar diffuser (SD) for the RSB calibration, a blackbody (BB) for the TEB calibration, and a spectro-radiometric calibration assembly (SRCA) for the spatial (RSB and TEB) and spectral (RSB only) characterization. Most importantly, extensive and dedicated sensor calibration and characterization efforts have been constantly made by the MODIS Characterization Support Team (MCST) at NASA/GSFC. In this presentation, we will provide an overview of MODIS sensor operations since 1aunh and the onorbit calibration and characterization methodologies with emphasis on the differences between Terra and Aqua MODIS characteristics. We will summarize both Terra and Aqua MODIS onorbit calibration and characterization results, including their RSB and TEB detector noise characterization, the sensor response changes, and the corrections to the optics degradation. In addition to radiometric calibration performance, we will illustrate both sensors' spectral and spatial characterization results in terms of their band-to-band registrations and spectral band center wavelength shifts.

Xiong, X.↗

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗

Advanced Characterization of Irradiated Fuels and Materials at INL

Advanced characterization of the irradiated fuels and materials is crucial to help understanding the material and fuel property changes under irradiation. Microstructural defect evolution down to nanometer scale could strongly affect the material and fuel performance on macroscale. Radiation-induced material degradation include dimensional instability, hardening and embrittlement, intergranular cracking, radiation-enhanced chemical interaction at the interfaces and breakaway swelling. To mitigate the radiation damage, advanced characterization on irradiated microstructure, microchemistry, micromechanical property and local thermal property is necessary to identify the controlling mechanisms that are responsible to the degradations. This presentation provides a summary of the advanced characterization capabilities at the Irradiation Materials Characterization Laboratory (IMCL), Materials and Fuels Complex (MFC), Idaho National Laboratory (INL). It highlights the recently established capabilities including shield sample preparation area (SSPA), shield confinement cells for two focused ion beam (FIB) systems, a shielded electron probe microanalysis (EPMA), the thermal property microscopy (TPM) along with non-shielded instruments like scanning electron microscopy (SEM), X-ray diffractometer, and transmission electron microscopy (TEM). Some examples on advanced characterizations on irradiated structural materials and fuels will be presented. It demonstrates the power of combining sample preparation of highly radioactive materials with the advanced characterization down to atomic resolutions within one facility.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

EPRI Demonstration of an Autonomous Site Characterization Vehicle - 20523

A substantial effort is applied in performing radiological characterization of structures and land areas during decommissioning of a nuclear facility. This includes multiple surveys of land areas and large structures to support eventual site release under the Multi Agency Survey and Site Investigation Manual (MARSSIM, Reference 1). These surveys are typically performed using manually delivered systems, which is time consuming and labor intensive. Radiological surveys intentionally follow a prescribed protocol with respect to areas covered, scan speeds, responses to elevated readings, required detector offsets, the need for repeat measurements, etc. Based on these attributes, combined with the repetitive effort of performing surveys over large areas, automation of radiological characterization techniques has a high potential to be successful and promises substantial benefit. EPRI has performed a project that resulted in the development and demonstration of an autonomous site characterization system. This EPRI project focused on building surfaces and the surfaces of large land areas as these configurations lend themselves more readily to automated survey. The project included: - Identification of the requirements for an autonomous site characterization system; - A survey of existing control systems that use automation to conduct characterization of structures and land areas. - As no fully adequate systems were identified, a complete system was developed that utilized commercially available detection and analysis systems and a self driving vehicle owned by EPRI. The system was demonstrated at the Kewaunee nuclear power plant site in the fall of 2019. The demonstration included: - Autonomous surveys of floor areas inside the Auxiliary Building at Kewaunee after manually controlled mapping of the survey areas. - For land areas, the vehicle autonomously surveyed areas using travel paths had been preprogrammed onto an internet available map of area. In this case, GPS coordinates from the preprogramming were used for navigation by the vehicles guidance system. This paper summarizes the characterization system development and system demonstration which will also be published in an EPRI report in the first half of 2020. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An integrated workflow for phenazine-modifying enzyme characterization

Abstract Increasing availability of new genomes and putative biosynthetic gene clusters (BGCs) has extended the opportunity to access novel chemical diversity for agriculture, medicine, environmental and industrial purposes. However, functional characterization of BGCs through heterologous expression is limited because expression may require complex regulatory mechanisms, specific folding or activation. We developed an integrated workflow for BGC characterization that integrates pathway identification, modular design, DNA synthesis, assembly and characterization. This workflow was applied to characterize multiple phenazine-modifying enzymes. Phenazine pathways are useful for this workflow because all phenazines are derived from a core scaffold for modification by diverse modifying enzymes (PhzM, PhzS, PhzH, and PhzO) that produce characterized compounds. We expressed refactored synthetic modules of previously uncharacterized phenazine BGCs heterologously in Escherichia coli and were able to identify metabolic intermediates they produced, including a previously unidentified metabolite. These results demonstrate how this approach can accelerate functional characterization of BGCs.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of ultrafast-laser ablation of micro-structures in Li-ion battery anode and cathode materials: Morphology, rate, and efficiency

Characterization of the rate and quality of ultrafast-laser ablation of Li-ion battery (LIB) electrode materials is presented for a collection of common and next-generation electrodes. Laser ablated micro-structures on the surface of LIB electrodes have been shown to provide dramatic enhancement of high-rate capability and electrode wetting. However, industrial adoption is hampered by a lack of data enabling informed choice of laser parameters and predicting process throughput. Here this work bridges this gap by providing characterization of the ablation process at more laser parameters (laser fluence and number of pulses used) than are currently available in the literature. Further, we expand on previous graphite and lithium iron phosphate (LFP) ablation work by extending ablation characterization to new LIB materials, providing high data resolution and adopting new characterization metrics which are relevant for industrial application of this technology. Ablated pores are characterized by their ablated depth, volume, and how the depth and volume ablation rate changes as a function of pore depth. Finally, we provide a detailed characterization of the morphology of laser ablated micro-structures which informs how material and laser parameters affect the quality of laser-processed electrodes.

25 ENERGY STORAGE↗

Combined Spatially Resolved Characterization of Antireflection and Antisoiling Coatings for PV Module Glass

Characterization of photovoltaic (PV) module materials throughout different stages of service life is crucial to understanding and improving the durability of these materials. Currently the large-scale of PV modules (>1 m 2 ) is imbalanced with the small-scale of most materials characterization tools (= 1 cm 2 ). Furthermore, understanding degradation mechanisms often requires a combination of multiple characterization techniques. Here, we present adaptations of three standard materials characterization techniques to enable mapping characterization over moderate sample areas (=25 cm 2 ). Contact angle, ellipsometry, and UV-Vis spectroscopy are each adapted and demonstrated on two representative samples: a commercial multi-functional coating for PV glass and an oxide combinatorial sample library. Best practices are discussed for adapting characterization techniques for large area mapping and combining mapping information from multiple techniques.

14 SOLAR ENERGY↗

Tracer-Guided Characterization of Dominant Pore Networks and Implications for Permeability and Wettability in Shale

Pore network characterization is an important aspect in unconventional reservoir evaluation. While application of the technique of scanning electron microscope (SEM) brings substantial advances in pore characterization in shale, understanding the connected pore network that dominates flow in shale samples is limited by using SEM alone because of small fields of view and lack of views of connectivity in 3D. In this research, a technique integrating tracer imbibition, micro-computed tomography (CT) imaging, and SEM imaging was developed to provide a solution for multiscale imaging in shale. Tracer imbibition indicates pore connectivity; micro-CT imaging after tracer imbibition thus provides an overview of the connected pore network at the millimeter scale. With guidance from micro-CT images after tracer imbibition, a more accurate and detailed characterization of pore systems and related mineralogy can be conducted using higher-resolution SEM. The method was applied to five samples from Wolfcamp and Eagle Ford Formations. Results reveal the effectiveness of the integrated method by showing different patterns of distribution of the dominant pore network and different controlling mineralogy. Dominant porosity, estimated from grayscale analyses, displays a good correlation with permeability. This result indicates that dominant porosity is more relevant to permeability than is total porosity. Results from imbibition tests are also compared with that from contact angle measurement, and important implications on wettability can be obtained. The integrated method thus has the capacity to link the dominant pore network and wettability with microscale to submicroscale mineralogy, which can help better understand the pore systems and fluid flow in shale. Plain Language Summary Pore network characterization and wettability are two important aspects in unconventional reservoir evaluation and are crucial to understanding the nature of shale oil or gas storage and production. Here, a new technique integrating tracer imbibition, micro-computed tomography imaging, and scanning electron microscope imaging was developed for a more representative and effective pore characterization in shale. This integrated technique can provide a direct visualization of the dominant pore network in a millimeter-scale sample and, at the same time, can provide a guided pore network characterization under nanoscale resolution. This method thus can generate results that are more representative and more accurate in a more efficient way compared with the traditional scanning electron microscope method. The new technique can also reveal the local wettability in microscale. High-resolution analysis on the tracer imbibition or fluid displacement and mineralogy can shed light on the local wettability and the controlling mineralogy in shale.

58 GEOSCIENCES↗

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems

Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.

36 MATERIALS SCIENCE↗

Efficient Data-Driven Geologic Feature Characterization from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm

Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency and subjective human factors. We developed a novel data-driven geological feature characterization approach based on pre-stack seismic measurements. Our characterization method employs an efficient and accurate machine learning method to extract useful subsurface geologic features automatically. Specifically, we use kernel ridge regression to account for the nonlinear relationship between seismic data and geological features. We moreover employ kernel tricks to avoid the explicit nonlinear mapping and infinite dimension of feature space. Yet, the conventional kernel ridge regression can be computationally prohibitive because of the large volume of seismic measurements. We employ a data reduction technique in combination with the conventional kernel ridge regression method to improve the computational efficiency and reduce memory usage. In particular, we utilize a randomized numerical linear algebra technique, named Nyström method, to effectively reduce the dimensionality of the feature space without compromising the information content required for accurate characterization. We provide thorough computational cost analysis to show the efficiency of our new geological feature characterization methods. We validate the performance of our method in characterizing geologic fault zones because faults play an important role in various subsurface applications. Our numerical examples demonstrate that our new characterization method significantly improves the computational efficiency while maintaining comparable accuracy. Interestingly, we demonstrate that our approach yields a speedup ratio on the order of ~102 to ~103 in a multicore computational environment.

58 GEOSCIENCES↗

Characterizing non-Markovian and coherent errors in quantum simulation

Quantum simulation of many-body systems, particularly using ultracold atoms and trapped ions, presents a unique form of quantum control—it is a direct implementation of a multi-qubit gate generated by the Hamiltonian. As a consequence, it also faces a unique challenge in terms of benchmarking, because the well-established gate benchmarking techniques are unsuitable for this form of quantum control. Here we show that the symmetries of the target many-body Hamiltonian can be used not only to benchmark but to characterize experimental errors in the quantum simulation. We use our results to develop protocols to characterize these errors, which can be implemented using state-of-the-art technology. We consider two forms of errors: (i) unitary errors arising out of systematic errors in the applied Hamiltonian and (ii) canonical non-Markovian errors arising out of random shot-to-shot fluctuations in the applied Hamiltonian. We show that the dynamics of the expectation value of the target Hamiltonian itself, which is ideally constant in time, can be used to characterize these errors. In the presence of errors, the expectation value of the target Hamiltonian shows a characteristic thermalization dynamics, when it satisfies the operator thermalization hypothesis (OTH). That is, an oscillation in the short time followed by relaxation to a steady-state value in the long time limit. We show that while the steady-state value can be used to characterize the coherent errors, the amplitude of the oscillations can be used to estimate the non-Markovian errors. We prove a sandwich theorem to establish a linear relation between the amplitude of the oscillations and the magnitude of the non-Markovian errors. Moreover, by varying the initial state, we show that the steady state values can be used to completely construct the generator of the coherent errors. Using these results, we develop two experimental protocols to characterize the unitary errors based on these results, one of which requires single-qubit addressing and the other one doesn't. We also develop a protocol to characterize non-Markovian errors. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design and Implementation of Automated Characterization of T-type based Power Module for PV Inverter Reliability Assessment

Reliability of power electronics holds the key for future power and energy systems since it is essential for system integration with renewables and energy storage systems. Variation of power module characteristics over the converter’s operational lifetime is a critical indicator to assess its reliability. Device characterization consists of different steps to collect, process, and visualize results, which is usually time-consuming, especially for power modules based on a non-phase-leg configuration, such as T-type circuits, widely applied for PV inverters. To reduce the time, ensure repeatability, and guarantee consistency, an automated test bench can be helpful. This paper focuses on a T-type-based power module and proposes a unique characterization platform and corresponding automation procedure and implementation. Considering the major characterization difference between T-type power modules over the conventional phase-leg power module, first, the special consideration for static characterization is highlighted. Second, the unique dynamic characterization design associated with the T-type power module is described. Finally, the automation of the power module characterization and the test platform is presented along with results and special considerations.

Siraj, Ahmed↗

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗

Tank 22 Settled Sludge Core Sample Characterization and Testing

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) Engineering (SRR-E) to provide sample characterization and analyses of Tank 22 settled sludge core sample and the supernatant liquids (supernate) in support of Tank 22 re-baseline data, inhalation dose potential/hydrogen generation and suspension/removal of settled sludge from the bottom of Tank 22. The approximately 9.5 inches of intact Tank 22 core sample from SRR-E, after extrusion in the SRNL Shielded Cells, showed three visually different stratification layers or regions of solids in the extruded core material. Part of the initial physical characterization of these three segments of the Tank 22 core sample included density, weight percent total solids, particle size distribution, X-ray diffractions and scanning electron microscope of each segment material. Given the dissimilarity of the three Tank 22 segment materials after the physical characterization results and the fact that there was no clear line of demarcation to indicate where each segment began and ended across the entire length of the core sample, SRNL in conjunction with the SRR-E customer decided to blend all three segments of the material to form a composite Tank 22 core sample for further analysis and characterization without taking into consideration the proportional weight or mass contribution of each segment. This compositing approach assumes that the errors introduced in any characterization of the Tank 22 core sample will be comparable to the errors when the three segments are separated and combined proportionally by weight to form the composite Tank 22 sample. This compositing approach maximized the quantity of composited Tank 22 material needed for radionuclide and other physical characterizations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Status Report on Characterization of High Burnup Fuel with Advanced Nondestructive Pulsed Neutron PIE

Characterizing irradiated or spent nuclear fuels with pulsed neutron techniques provides microstructural data such as phase fractions as well as crystallographic data, e.g. lattice parameters, from diffraction analysis. Diffraction characterization is complemented by spatially resolved mapping of isotope densities from energy-resolved neutron imaging, in particular neutron absorption resonance imaging, and overall bulk isotope assay with better sensitivity for minority isotopes from neutron absorption resonance spectroscopy without spatial resolution. Furthermore, after characterization at ambient condition, heating of irradiated or spent fuel will allow to characterize differences of e.g. lattice thermal expansion or phase transition temperature and kinetics compared to fresh fuel as well as enable the study of disappearance of irradiation defects. This data enables benchmarking of predictions of properties of irradiated fuels for which otherwise experimental data is sparse. The effort described here strives to characterize a section cut from a high-burnup fuel. Volumes smaller than entire fuel pellets or rodlets as proposed here, e.g. sections cut from a fuel pellet, to pave the way to characterize entire pellets or rodlets in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗