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DOE OSTI2023

Energy Resilience for Mission Assurance, Agile Co-simulation for Cyber Energy System Security (ACCESS) Model Advancements for Resilience Analysis (Version 3, July 2023)

Agile Co-simulation for Cyber Energy System Security (ACCESS) is a co-simulation platform developed by Lawrence Livermore National Laboratory (LLNL). The primary high-level use-case for ACCESS is to study existing or new cyber-physical critical infrastructure systems, with a heavy emphasis on 1) systems that utilize communication networks, and 2) studies that seek to understand cyber-related system impacts. ACCESS is currently used for several energy system resilience projects at LLNL. In the Energy Resilience for Mission Assurance (ERMA) project, ACCESS is used in the Mod eling for Metric Calculation task (specifically, subtask 4.3, Communications and Cyber Modeling) to model and simulate the cyber and communication system aspects of Defense Critical Electric Infrastructure (DCEI) systems, with a focus on computing specific communication system metrics that can impact system resilience and mission performance. Simulated communication system per formance will be fed back to other ERMA system components so that mission performance can be evaluated holistically. This report describes several enhancements to the ACCESS platform that were implemented during the execution of the ERMA project in support of reslience analysis. This includes the addition of new models and subsystems, enhancements to existing models, and integration with external systems. The remainder of this report is structured as follows. In Section 2, a brief background description of the ACCESS platform is provided, including an outline of ACCESS components, example use cases, and a set of communication network resilience metrics that can be computed with ACCESS. Section 3 describes the ACCESS model enhancements for ERMA in detail. Finally, Section 4 briefly outlines future integration opportunities between ACCESS and project participant capabilities identified during the progression of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

A performance spectrum for parallel computational frameworks that solve PDEs

Summary Important computational physics problems are often large‐scale in nature, and it is highly desirable to have robust and high performing computational frameworks that can quickly address these problems. However, it is no trivial task to determine whether a computational framework is performing efficiently or is scalable. The aim of this paper is to present various strategies for better understanding the performance of any parallel computational frameworks for solving PDEs. Important performance issues that negatively impact time‐to‐solution are discussed, and we propose a performance spectrum analysis that can enhance one's understanding of critical aforementioned performance issues. As proof of concept, we examine commonly used finite element simulation packages and software and apply the performance spectrum to quickly analyze the performance and scalability across various hardware platforms, software implementations, and numerical discretizations. It is shown that the proposed performance spectrum is a versatile performance model that is not only extendable to more complex PDEs such as hydrostatic ice sheet flow equations but also useful for understanding hardware performance in a massively parallel computing environment. Potential applications and future extensions of this work are also discussed.

Chang, J.↗

DOE OSTI2014

Nuclear Fuel Cycle System Simulation Tool Based on High-Fidelity Component Modeling

The DOE is currently directing extensive research into developing fuel cycle technologies that will enable the safe, secure, economic, and sustainable expansion of nuclear energy. The task is formidable considering the numerous fuel cycle options, the large dynamic systems that each represent, and the necessity to accurately predict their behavior. The path to successfully develop and implement an advanced fuel cycle is highly dependent on the modeling capabilities and simulation tools available for performing useful relevant analysis to assist stakeholders in decision making. Therefore a high-fidelity fuel cycle simulation tool that performs system analysis, including uncertainty quantification and optimization was developed. The resulting simulator also includes the capability to calculate environmental impact measures for individual components and the system. An integrated system method and analysis approach that provides consistent and comprehensive evaluations of advanced fuel cycles was developed. A general approach was utilized allowing for the system to be modified in order to provide analysis for other systems with similar attributes. By utilizing this approach, the framework for simulating many different fuel cycle options is provided. Two example fuel cycle configurations were developed to take advantage of used fuel recycling and transmutation capabilities in waste management scenarios leading to minimized waste inventories.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Intrusion Detection System Alarm Station Operator Interface Improvements

To address Alarm Station operator performance, Portable Intrusion Detection System team gathered information concerning AS operator data needs when assessing alarms. The purpose was to improve the Portable Intrusion Detection System operator interface to ensure that critical information was quickly presented and easily accessible. To gather the data, the team used a Goal Directed Task Analysis approach. The method of analysis was to prepare a set of interview questions, interview selected AS operator experts, conduct the interviews, create a goal/decision/information hierarchy based on information gathered, and then apply the results to the operator interface. In applying the results, the team had to consider not only the Goal Directed Task Analysis -determined information needs of the Alarm Station operator end-user population, but also account for customer requirements and differences in domain. The constraints in implementing all situation awareness recommendations are summarized and initial potential solutions presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

Electrical Substation Configuration Effect on Substation Reliability

It is crucial that the U.S. electrical grid be reliable, due to its critical role in the economy and our national defense/security. Many common tasks and industrial operations rely on proper electrical power distribution. In designing new bus systems or evaluating existing ones, the type of configuration employed affects the level of risk, reliability, maintenance, and cost involved. The present work utilizes Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) to perform a probabilistic risk assessment (PRA)-based sensitivity study on substation reliability in regard to different bus configurations. This study examines single bus, main and transfer, breaker and a half, double bus/double breaker, and ring bus configurations applied to busses with different numbers of lines. The case variances, methods, and rankings presented herein can help guide bus configurations for electrical grid design/analysis in the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Development of Real-Time Quantitative Safety Evaluation Method for Nuclear Power Plants

Human operators involved with large process control systems such as nuclear power plants (NPPs) perform significant roles in the operation of systems. In this reason, deficiencies in human factors such as poor HSI (Human System Interface) design, procedure, and training, are significant contributing factors to NPPs incidents and accidents. In this regard, many kinds of studies including human reliability analysis (HRA), operation support system, automation, have been conducted in order to reduce human errors. Among these fields of studies, automation has its own specialty since it mainly focuses on eliminating the human error-inducing tasks to reduce human error, while other topics are primarily focusing on reducing human error by aiding human operators during operation. It is commonly believed that replacing human operators to the automated system would guarantee greater efficiency, lower workloads, and fewer human errors. However, these beliefs are not always true in large and complex systems such as NPP, since excessive automation can generate new roles for human operators, change human operators' activities in unexpected ways, and inducing 'out-of-the-loop' (OOTL) problem. Especially, although human error probability drastically increases during abnormal situations in NPP due to overload of information, high workload, and short time available for diagnosis, automation is not actively adopted since conventional machine learning techniques are neither capable nor reliable to handle overwhelmingly complex abnormal situations in NPP. Recently, newly developed 'deep learning' techniques have been actively applied to many fields, and some of these studies proved that the artificial intelligences (AI) based on deep learning techniques show better performance than that of human being. In 2015, deep Q-network (DQN) which is one of the deep learning techniques was developed and applied to train AI that automatically plays various Atari 2800 games, and this AI surpassed the human-level playing in many kind of games. Also in 2016, 'AlphaGo', which was developed by 'Google Deepmind' based on deep learning technique to play the game of Go, was defeated Se-dol Lee who is the World Go champion with score of 4:1. In the point of view that the game of Go is considered as one of the challenging area in machine learning field, it is verified that these new machine learning techniques can perform well, even better than the human being in high-complexity tasks. Previously, most of AI applications in nuclear field were focusing on supporting human operators' tasks such as diagnosis and decision making by rapid classification and prediction, based on fixed training data sets. However, it is expected that AI can be applied to solve more complicated problems (i.e. automation during abnormal states in NPP) by adopting advanced machine learning methodologies. In order to apply the automation system in NPP, firstly it is needed to evaluate the status of the plant quantitatively in real-time, since the information about which state is better (i.e. safe) or worse (i.e. unsafe) is essential for training properly working automation AI. Currently, there are several methodologies for NPP safety evaluation such as probabilistic safety assessment (PSA), safety performance indicator (SPI). However, existing methodologies are not feasible for development of automated system since they are not capable for the cases which are not included in the underlying model, not able to consider delicate changes in the NPP, and hard to evaluate in real-time. Therefore, development of new NPP safety evaluation methodology which can cover previously mentioned requirements is needed to conduct the study on NPP automation further. In this study, the concept of early warning score (EWS) in medical field was adopted to develop the methodology which can evaluate the safety level of the NPP quantitatively and in real-time. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization “map” designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter. Conclusions: Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]

The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors. In Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges. The Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit. The Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards. The Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program. The Badges Toolkit includes five pieces: "How to Use the Badges Toolkit" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit. The "Badges Toolkit: Worksheet" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program. The "Crew Leader Job Task Analysis Spreadsheet" indicates how the Badges align with specific areas of the JTA. The "Installer Badges Passport" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed. The "Installer Badges Verification Criteria" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges. Note: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.

Desai, Jal↗

DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

DOE OSTI2014

SU-F-18C-06: Prospective Patient Evaluation of Iterative Reconstruction in Radiation Oncology

Purpose: This work incorporates iterative reconstruction (IR) into a dose reduction study to characterize image quality metrics, delineation, and dosimetric assessment, with the goal of reducing imaging dose in Radiation Oncology. Methods: Three-dimensional noise power spectrum (NPS) analysis characterized noise magnitude/texture (120 kVp, 50–200 mAs, IR levels 1–6 yielding noise reduction of 0.89–0.55 compared to filtered backprojection (FBP)). Task-specific Modulation Transfer Functions (MTFtask) were characterized across varied subject contrasts. A prospective dose reduction study (500 to 150 mAs) was conducted for 12 patients (43 inter-fraction CTs) for high-dose rate brachytherapy. Three physicians performed qualitative image assessment between full-dose FBP (FD-FBP, 500 mAs), low-dose FBP (LD-FBP, 150–250 mAs), and low-dose IRL5-6 (LD-IR) scans for image noise, cuff/bladder interface detectability, spatial resolution, texture, and segmentation confidence. Comparisons between LD-FBP and LD-IR were conducted for the following metrics: delineation (bladder and rectum evaluated via overlap indices (OI) and Dice similarity coefficients (DSC)), noise, boundary changes, dose calculation, and digitally reconstructed radiographs (DRRs). Results: NPS showed ∼50% reduction in noise magnitude and ∼0.1 1/mm spatial frequency shift with IRL6. The largest MTFtask decrease between FBP and IR was 0.08 A.U. Qualitative patient image evaluation revealed LD-IR was equivalent or slightly worse than FD-FBP, and superior to LD-FBP for all metrics except low contrast interface and texture. The largest CT number discrepancy from FBP occurred at a bone/tissue interface using IRL6 (−1.2 ± 4.9 HU (range: −17.6 – 12.5 HU)). No significant contour differences (OIs and DSCs = 0.85 – 0.95) and dose calculation discrepancy (<0.02%) were observed. DRRs preserved anatomical detail and demonstrated <2% difference in intensity between LD-FBP and LD-IRL6. Conclusion: While phantom analysis showed slight noise texture differences with IR, patient results revealed that image quality, contouring ability, and dosimetric parameters were not adversely affected, thus support integrating IR into treatment planning. Research supported in part by a grant from Philips HealthCare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Electric Motor Thermal Management R&D. Annual Report

With the push to reduce component volumes, lower costs, and reduce weight without sacrificing performance or reliability, the challenges associated with thermal management increase for power electronics and electric motors. Thermal management for electric motors will become more important as the automotive industry continues the transition to more electrically dominant vehicle propulsion systems. The transition to more electrically dominant propulsion systems leads to higher-power duty cycles for electric drive systems. Thermal constraints place significant limitations on how electric motors ultimately perform, and as thermal management improves, there will be a direct trade-off between motor performance, efficiency, cost, and the sizing of electric motors to operate within the thermal constraints. The goal of this research project is to support broad industry demand for data, analysis methods, and experimental techniques to improve and better understand motor thermal management. Work in FY15 focused on two areas related to motor thermal management: passive thermal performance and active convective cooling. Passive thermal performance emphasized the thermal impact of materials and thermal interfaces among materials within an assembled motor. The research tasks supported the publication of test methods and data for thermal contact resistances and direction-dependent thermal conductivity within an electric motor. Active convective cooling focused on measuring convective heat-transfer coefficients using automatic transmission fluid (ATF). Data for average convective heat transfer coefficients for direct impingement of ATF jets was published. Also, experimental hardware for mapping local-scale and stator-scale convective heat transfer coefficients for ATF jet impingement were developed.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

Pre-Commercial Scale-Up of a Gas-Fired Absorption Heat Pump

The project sought to advance the maturity of SMTI’s 80 kBTU/hr residential space and water heating GAHP from the engineering prototype stage (TRL-7) to pre-production readiness by addressing manufacturing, balance of system design and installation, cost, reliability, and field application questions. As part of this project, the project team has: (1) Matured the design package for a commercially ready product (2) Demonstrated compliance with relevant ANSI standards (3) Completed manufacturing and assembly process specifications (4) Completed total production cost estimates and capital equipment requirements (5) Initiated component and system level reliability assessments (6) Completed a small field demonstration including measured performance, installation requirements and expected costs, and customer/key stakeholder feedback. (7) Completed a Techno-economic analysis for representative applications and climate zones, including justification for utility incentive programs. (8) Completed a market intelligence report. Scope of Work: A multi-faceted project was completed that included: (a) design for manufacturing tasks for both the sealed system and balance of system, (b) development and trial of key manufacturing processes and techniques, (c) evaluation of component and system level reliability, (d) exploration of make/buy decisions including impact on cost and required capital. Additionally, (e) installation and monitoring of a small number of field test units was completed to demonstrate energy savings and collect customer/installer feedback, and (f) a focused market research task was completed to explore potential barriers and improve market introduction plans. These tasks addressed many of the remaining technical risks regarding long-term reliability, verification of manufacturing cost estimates and identification of cost concerns, identify installation and balance of system design criteria necessary to achieve energy savings and installed cost goals, and identify market barriers and strategies prior to product market introduction.

03 NATURAL GAS↗

DOE OSTI2024

Capability Enhancements for System-level thermal Hydraulic Modeling of Lead Fast Reactors

This project has focused on the use, assessment, and development of the SAS4A/SASSYS-1 (SAS) safety analysis software. Although SAS was originally intended as a safety analysis tool for Liquid Metal cooled Fast Reactors (LMFRs), which includes both Sodium Fast Reactors (SFRs) and Lead Fast Reactors (LFRs), the vast majority of its recent development and customization has been tailored to SFRs. In general, enhancements that are made to the software for SFRs are applicable to LFRs, however, the fuel composition and corrosive nature of lead requires careful consideration when performing safety analysis of an LFR. In this project an emphasis was placed on closing gaps that are associated with modeling LFRs using SAS. The principal objective of the project was to enhance the ability of SAS as a licensing tool for LFRs. This objective was to be accomplished through three tasks: 1) Enhance the ability of SAS to couple with external software; 2) Improve the underlying physics models in SAS, with priority given to models that are highly relevant to LFRs; 3) Extend the Verification and Validation (V&V) basis of the software

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

International collaboration in disposal research: comparative modeling of coupled processes in the DECOVALEX project

Abstract. This presentation gives an overview of an international research collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. The creation of the international DECOVALEX project, now running for more than 25 years, was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of state-of-the-art field and laboratory experiments, across a range of host rock options and repository designs. Participating research teams are from radioactive waste management organizations, national research institutes, regulatory agencies, universities, and consulting groups, providing a wide range of perspectives and solutions to these complex problems. The presentation provides examples of the research contributions made collectively in past DECOVALEX tasks and also touches on the unique modeling challenges tackled in the ongoing project phase, referred to as DECOVALEX-2023. The current phase comprises 17 partner organizations, about 50 modeling teams, and 7 modeling tasks, which cover a broad portfolio from fundamental studies on gas migration to full-scale in situ heater experiments in different host rocks to performance assessment studies. Together, these examples illustrate that the insight and scientific knowledge gained within the DECOVALEX project would not have been possible if one group had studied these complex THMC modeling challenges alone rather than within a truly collaborative setting.

Birkholzer, Jens T.↗

DOE OSTI2015

Effects of Field of View and Visual Complexity on Virtual Reality Training Effectiveness for a Visual Scanning Task

Virtual reality training systems are commonly used in a variety of domains, and it is important to understand how the realism of a training simulation influences training effectiveness. The paper presents a framework for evaluating the effects of virtual reality fidelity based on an analysis of a simulation’s display, interaction, and scenario components. Following this framework, we conducted a controlled experiment to test the effects of fidelity on training effectiveness for a visual scanning task. The experiment varied the levels of field of view and visual realism during a training phase and then evaluated scanning performance with the simulator’s highest level of fidelity. To assess scanning performance, we measured target detection and adherence to a prescribed strategy. The results show that both field of view and visual realism significantly affected target detection during training; higher field of view led to better performance and higher visual realism worsened performance. Additionally, the level of visual realism during training significantly affected learning of the prescribed visual scanning strategy, providing evidence that high visual realism was important for learning the technique. The results also demonstrate that task performance during training was not always a sufficient measure of mastery of an instructed technique. That is, if learning a prescribed strategy or skill is the goal of a training exercise, performance in a simulation may not be an appropriate indicator of effectiveness outside of training—evaluation in a more realistic setting may be necessary.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Southeast Offshore Storage Resource Assessment (SOSRA) (Final Technical Report)

Subsurface geologic storage of CO 2 can play a major role in offsetting greenhouse gas emissions in a manner that is safe, economical, and acceptable to the public. Due to legal advantages and potential vast resource capacity, offshore storage offers an attractive alternative to onshore storage. Indeed, the success of the Sleipner project in the North Sea demonstrates the technical feasibility of offshore storage as not only a viable option, but as an early opportunity for commercial deployment. Although the storage capacity of offshore reservoirs is expected to be vast, no comprehensive assessment of the offshore storage resource in the southeastern United States had been performed. In a preliminary analysis of a 10,000 mi 2 area of offshore Alabama and the western Florida Panhandle, Hills and Pashin (2010) suggested that about 170 Gt of CO 2 could be stored in Miocene sandstone and that at least 30 Gt could be stored in deeper Cretaceous formations. A task force convened by the Southern States Energy Board (SSEB) and the Interstate Oil and Gas Compact Commission (IOGCC) found that no assessment had been made of the offshore storage resource potential in the shelf areas of the Atlantic seaboard and the eastern Gulf of Mexico in the southeastern US. Considering that the U.S. Environmental Protection Agency estimates that about 40% of anthropogenic CO 2 emissions in the US are generated in the southeast, the lack of an offshore CO 2 assessment constitutes a major gap in understanding of the regional storage resource. In order to address this significant gap in knowledge of the regional storage resources and geologic capacity the Southern States Energy Board (SSEB) led a coalition of southern universities and technical experts to assess prospective geologic storage resources for carbon dioxide (CO 2 ) in the State and Federal waters of three planning areas: The Mid-Atlantic; The South Atlantic; and The eastern Gulf of Mexico. The Southeast Offshore Storage Resource Assessment (SOSRA) project developed a high-level approximation of the amount of CO 2 that might be stored utilizing key geologic and environmental factors which influence the storage potential. The research included significant advances in knowledge and technology that will facilitate assessment and quantification of offshore CO 2 storage resources in the SOSRA region and provide a pathway toward commercialization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Discovery of the First Leaking Double-Shell Tank - Hanford Tank 241-AY-102

A routine video inspection of the annulus space between the primary tank and secondary liner of double-shell tank 241-AY-102 was performed in August 2012. During the inspection, unexpected material was discovered. A subsequent video inspection revealed additional unexpected material on the opposite side of the tank, none of which had been observed during inspections performed in December 2006 and January 2007. A formal leak assessment team was established to review the tank's construction and operating histories, and preparations for sampling and analysis began to determine the material's origin. A new sampling device was required to collect material from locations that were inaccessible to the available sampler. Following its design and fabrication, a mock-up test was performed for the new sampling tool to ensure its functionality and capability of performing the required tasks. Within three months of the discovery of the unexpected material, sampling tools were deployed, material was collected, and analyses were performed. Results indicated that some of the unknown material was indicative of soil, whereas the remainder was consistent with tank waste. This, along with the analyses performed by the leak assessment team on the tank's construction history, lead to the conclusion that the primary tank was leaking into the annulus. Several issues were encountered during the deployment of the samplers into the annulus. As this was the first time samples had been required from the annulus of a double-shell tank, a formal lessons learned was created concerning designing equipment for unique purposes under time constraints.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Method and apparatus for offloading compute resources to a flash co-processing appliance

Solid-State Drive (SSD) burst buffer nodes are interposed into a parallel supercomputing cluster to enable fast burst checkpoint of cluster memory to or from nearby interconnected solid-state storage with asynchronous migration between the burst buffer nodes and slower more distant disk storage. The SSD nodes also perform tasks offloaded from the compute nodes or associated with the checkpoint data. For example, the data for the next job is preloaded in the SSD node and very fast uploaded to the respective compute node just before the next job starts. During a job, the SSD nodes perform fast visualization and statistical analysis upon the checkpoint data. The SSD nodes can also perform data reduction and encryption of the checkpoint data.

97 MATHEMATICS AND COMPUTING↗