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Performance Study of an aSi Flat Panel Detector for Fast Neutron Imaging of Nuclear Waste

Radioactive waste must be characterized to check its conformance for intermediate storage and final disposal according to national regulations. For the determination of radio-toxic and chemo-toxic contents of radioactive waste packages non-destructive analytical techniques are preferentially used. Fast neutron imaging is a promising technique to assay large and dense items providing, in complementarity to photon imaging, additional information on the presence of structures in radioactive waste packages. Therefore the feasibility of a compact Neutron Imaging System for Radioactive waste Analysis (NISRA) using 14 MeV neutrons is studied in a cooperation framework of Forschungszentrum Juelich GmbH, RWTH Aachen University and Siemens AG. However due to the low neutron emission of neutron generators in comparison to research reactors the challenging task resides in the development of an imaging detector with a high efficiency, a low sensitivity to gamma radiation and a resolution sufficient for the purpose. The setup is composed of a commercial D-T neutron generator (Genie16GT, Sodern) with a surrounding shielding made of polyethylene, which acts as a collimator and an amorphous silicon flat panel detector (aSi, 40 x 40 cm{sup 2}, XRD-1642, Perkin Elmer). Neutron detection is achieved using a general propose plastic scintillator (EJ-260, Eljen Technology) linked to the detector. The thermal noise of the photodiodes is reduced by employing an entrance window made of aluminium. Optimal gain and integration time for data acquisition are set by measuring the response of the detector to the radiation of a 500 MBq {sup 241}Am-source. Detector performance was studied by recording neutron radiography images of materials with various, but well known, chemical compositions, densities and dimensions (Al, C, Fe, Pb, W, concrete, polyethylene, 5 x 8 x 10 cm{sup 3}). To simulate gamma-ray emitting waste radiographs in presence of a gamma-ray sources ({sup 60}Co, {sup 137}Cs, {sup 241}Am) were performed. A homemade algorithm was developed to determine a value which is related to the neutron absorption of the sample with the analysis of the raw detector data. The detector was placed 42 cm away from the neutron source. Distance between detector and the samples was 0.5 cm. At the sample position the fast neutron flux was estimated to 9x10{sup 3} n cm{sup -2} s{sup -1} for a neutron emission of 10{sup 8} n s{sup -1}. The acquisition time was 15 minutes. First neutron radiographs were successfully recorded despite the low detector efficiency and low neutron emission. Analysis of the data shows a correlation between the measured signal and determined neutron absorption. Thus discrimination between different materials of same thicknesses may be achieved. The measurements and results will be presented and discussed in details.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems, etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.

97 MATHEMATICS AND COMPUTING↗

Virtual Design Studio (VDS) - Development of an Integrated Computer Simulation Environment for Performance Based Design of Very-Low Energy and High IEQ Buildings

Executive Summary The objective of this study was to develop a “Virtual Design Studio (VDS)”: a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. This VDS is intended to assist collaborating architects, engineers and project management team members throughout from the early phases to the detailed building design stages. It can be used to plan design tasks and workflow, and evaluate the potential impacts of various green building strategies on the building performance by using the state of the art simulation tools as well as industrial/professional standards and guidelines for green building system design. Engaged in the development of VDS was a multi-disciplinary research team that included architects, engineers, and software developers. Based on the review and analysis of how existing professional practices in building systems design operate, particularly those used in the U.S., Germany and UK, a generic process for performance-based building design, construction and operation was proposed. It distinguishes the whole process into five distinct stages: Assess, Define, Design, Apply, and Monitoring (ADDAM). The current VDS is focused on the first three stages. The VDS considers building design as a multi-dimensional process, involving multiple design teams, design factors, and design stages. The intersection among these three dimensions defines a specific design task in terms of “who”, “what” and “when”. It also considers building design as a multi-objective process that aims to enhance the five aspects of performance for green building systems: site sustainability, materials and resource efficiency, water utilization efficiency, energy efficiency and impacts to the atmospheric environment, and IEQ. The current VDS development has been limited to energy efficiency and IEQ performance, with particular focus on evaluating thermal performance, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via the internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predicts the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a simple 3-zone case building. The application of the VDS concepts and framework for building design and performance analysis has been illustrated by using a medium-sized, five story office building that received LEED Platinum Certification from USGBC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Qualitative Assessment of Current CCF Guidance Based on a Review of Safety System Digital Implementation Changes with Evolving Technology

The US Nuclear Regulatory Commission (NRC) is initiating a new rulemaking project to develop a digital system common-cause failure (CCF) rule. This rulemaking will review and modify or affirm the NRC's current digital system CCF policy as discussed in the Staff Requirements Memorandum to the Secretary of the Commission, Office of the NRC (SECY) 93-087, Policy, Technical, and Licensing Issues Pertaining to Evolutionary and Advanced Light Water Reactor (ALWR) Designs, and Branch Technical Position (BTP) 7-19, Guidance on Evaluation of Defense-in-Depth and Diversity in Digital Computer-Based Instrumentation and Control Systems, as well as Chapter 7, Instrumentation and Controls, in NRC Regulatory Guide (NUREG)-0800, Standard Review Plan for Review of Safety Analysis Reports for Nuclear Power Plants (ML033580677). The Oak Ridge National Laboratory (ORNL) is providing technical support to the NRC staff on the CCF rulemaking, and this report is one of several providing the technical basis to inform NRC staff members. For the task described in this report, ORNL examined instrumentation and controls (I&C) technology implementations in nuclear power plants in the light of current CCF guidance. The intent was to assess whether the current position on CCF is adequate given the evolutions in digital safety system implementations and, if gaps in the guidance were found, to provide recommendations as to how these gaps could be closed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity

The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However, the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.

big data↗

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↗

Cyber / Physical Security Vulnerability Assessment Integration

Abstract Both physical protection and cyber security domains offer solutions for the discovery of vulnerabilities through the use of various assessment processes and software tools. Each vulnerability assessment (VA) methodology provides the ability to identify and categorize vulnerabilities, and quantifies the risks within their own areas of expertise. Neither approach fully represents the true potential security risk to a site and/or a facility, nor comprehensively assesses the overall security posture. The technical approach to solving this problem was to identify methodologies and processes that blend the physical and cyber security assessments, and develop tools to accurately quantify the unaccounted for risk. SMEs from both the physical and the cyber security domains developed the blending methodologies, and cross trained each other on the various aspects of the physical and cyber security assessment processes. A local critical infrastructure entity volunteered to host a proof of concept physical/cyber security assessment, and the lessons learned have been leveraged by this effort. The four potential modes of attack an adversary can use in approaching a target are; Physical Only Attack, Cyber Only Attack, Physical Enabled Cyber Attack, and the Cyber Enabled Physical Attack. The Physical Only and the Cyber Only pathway analysis are two of the most widely analyzed attack modes. The pathway from an off-site location to the desired target location is dissected to ensure adversarial activity can be detected and neutralized by the protection strategy, prior to completion of a predefined task. This methodology typically explores a one way attack from the public space (or common area) inward towards the target. The Physical Enabled Cyber Attack and the Cyber Enabled Physical Attack are much more intricate. Both scenarios involve beginning in one domain to affect change in the other, then backing outward to take advantage of the reduced system effectiveness, before penetrating further into the defenses. The proper identification and assessment of the overlapping areas (and interaction between these areas) in the VA process is necessary to accurately assess the true risk.

Vulnerability Analysis, Risk Analysis, Cyber Secur↗

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.

97 MATHEMATICS AND COMPUTING↗

Quantitative Characterization of Impacts of Coupled Geomechanics and Flow on Safe and Permanent Geological Storage of CO 2 in Fractured Aquifers

This is the final scientific report for the award DE-FE0023305, entitled “Quantitative Characterization of Impacts of Coupled Geomechanics and Flow on Safe and Permanent Geological Storage of CO 2 in Fractured Aquifers.” The work has been divided into six tasks. In Task 2, we characterized rock properties, which are important when developing a quantitative approach for understanding and predicting geomechanical effects on large-scale CO 2 injection and long-term storage in the subsurface. Rock properties of interest for this characterization include porosity, permeability, elastic constants, strength, and heat capacity. We measured rock properties for three different rock types: concrete, sandstone and shale. These properties were obtained from the acoustic measurement, permeability and porosity measurement, Brazilian test, the uniaxial compressive test, and heat capacity measurement. Then, using the Brazilian technique to fracture samples, we measured their permeability under brine injection for varying effective stresses, followed by similar measurements of permeability under sc-CO 2 injection. Permeability to brine and sc-CO 2 decreased as the effective stress increased. The apparent permeability to sc-CO 2 was an order of magnitude less than that for brine, a consequence of CO 2 being the non-wetting fluid. In Task 3, we developed understandings and correlations for CO 2 injection pressure induced fracturing. We initially fractured four eight inch cubes of concrete with brine to establish a standard test procedure. Then, additional concrete samples were fractured using brine. Confining stresses were exerted on the samples and brine was injected at a constant rate into a borehole that was previously drilled into the concrete cube. The borehole pressure was measured and fracture initiation was identified as a peak in the pressure profile. That was followed by fracture propagation, which was identified as a plateau in the pressure profile, and finally the fracture reached the sample surface. The sample surfaces were photographed before and after fracturing, which enabled determination of where the fracture reached the sample surface. Afterwards, aqueous food dye solution was injected into the fractured concrete samples to color the fracture planes. The borehole was filled with food dye solution in advance, a gas pulse was transmitted to the borehole, and the borehole was then shut in to allow the food dye to be driven into existing fractures. Then, the concrete samples were broken down by high-pressure gas injection to reveal the geometry and morphology of the hydraulic fractures. In addition, acoustic measurements were conducted on multiple locations on each face of the concrete samples before and after injection for comparison. This comparison was used to confirm changes in the internal structure of the concrete sample, namely the formation of fractures. There were six concrete samples fractured with brine. Afterwards, concrete samples were fracture using sc-CO 2 . The main change in experimental procedure was the inclusion of temperature control, since in the field, we mostly encounter temperature and pressure conditions above the supercritical point of CO 2 . The concrete samples were pre-heated in an oven to elevate their temperature, and thermal tape was used to heat the CO 2 to a temperature above its supercritical temperature. Two concrete samples were fractured using liquid CO 2 , four concrete samples were fractured using gaseous CO 2 , and twenty two concrete samples were fractured using sc-CO 2 . For the concrete samples fractured using sc-CO 2 , three had pre-existing hydraulic fractures on the surface near the wellbore, and two were water saturated (as opposed to containing only air). Two concrete samples were composite samples, with a high permeability ball in the center, in order to represent CO 2 injection into a high permeability zone surrounded by a low permeability sealing formation. Later, we fractured five shale samples, obtained from the Niobrara shale outcrop, with sc-CO 2 . The injection rate was constant, confining stresses were applied, the shale samples were pre-heated in an oven to the desired temperature, and the sample was then fractured. An analysis of the failure type was done for many of the concrete samples, based on the predicted break down pressure for tensile and shear failure, and it was found that most samples fractured due to shear failure. Also, the presence of induced fractures has little to no effect on the fracture initiation pressure, but significantly changes the fracture morphology. The CO 2 fracturing in water saturated samples behaved much similar to brine induced fracturing. There was a significant difference of breakdown pressure for injection of CO 2 and brine, where the breakdown pressure for CO 2 induced fracturing is generally around the minimum horizontal stress and that for brine is much higher. Finally, the fracture orientation for most samples with large confining stress differential was perpendicular to the minimum horizontal stress. When the stress differential, especially the difference between the two directions with the smallest stresses was small, the fracture orientation was determined not only by the minimum stress direction, but also the magnitude of the confining stress, the tensile strength of the rock, and the breakdown pressure. In Task 4, we modified our coupled flow-geomechanical models to model fracture growth and propagation in storage formations and caprocks. These flow-geomechanical models are TOUGH2-CSM and TOUGH2-FLAC. The TOUGH2-CSM fluid and heat flow formulation is based on the TOUGH2 formulation of mass and energy conservation equations that govern fluid and heat flow in general multiphase, multicomponent, multi-porosity systems. The TOUGH2-CSM simplified geomechanical formulation is based on the linear theory of elasticity applied to multi-porosity non-isothermal (thermo-multi-poroelastic) media. We previously derived, from the fundamental relations of the linear theory of elasticity, an equation relating mean stress, pore pressures, temperatures, and body force (the Mean Stress equation) that we added to the TOUGH2-CSM fluid and heat flow equations. We extended the TOUGH2-CSM simplified geomechanical formulation to calculate the entire stress tensor by deriving equations for stress tensor components from derivatives of the Cartesian thermo-multi-poroelastic Navier equation components. In addition, we derived equations for stress tensor components in rz-coordinates. We solved these geomechanical equations using the integral finite difference method. This method utilizes momentum fluxes obtained by “factoring” a divergence operator out of each geomechanical equation. In Task 5, we did a literature survey to determine suitable correlations for fracture initiation, growth, and propagation. After surveying numerous papers, we modified TOUGH2-CSM to model stress dependent fracture initiation and growth using the Mohr-Coulomb criterion for shear failure in faults and caprock and the condition of negative minimum effective stress for tensile failure. Tensile failure results in a fracture whose width depends on the difference between fracture pressure and minimum stress and whose propagation is based on the difference between the stress intensity factor at the fracture tip and the rock toughness. The TOUGH-FLAC model is based on the FLAC3D ubiquitous joint model, extended for the modeling of permeability changes induced by changes in effective normal stress across fractures as well permeability changes caused by shearing along fractures. In Task 6, we validated our coupled flow-geomechanical models using analytical solutions and problems from the literature. We validated the TOUGH2-CSM modifications using analytical solutions to the displacement from a uniform load on a semi-infinite elastic medium and the two-dimensional Mandel-Cryer effect. Those were followed by a sample problem to test our stress tensor calculations, which was for injection into a single-phase reservoir with constant properties. Comparisons of our simulator to published results were done on for the depletion of a single-phase reservoir with stress dependent porosity, two examples from the In Salah gas project, an axisymmetric baserock–reservoir–caprock system with a normal faulting stress regime that had thermally induced shear stresses, simulations of CO 2 leakage through caprock in a two-dimensional reservoir in Cartesian coordinates, and predictions of caprock failure from CO 2 injection into an axisymmetric reservoir. Finally, we simulated CO 2 injection pressure-induced fracturing from one of our laboratory studies, Sample 39, and obtained a fracture profile. We also validated the TOUGH2-FLAC model for fluid driven fracture growth against solutions based on the KGD model and a case with an inclined fracture that was loaded from the boundaries to achieve wing-crack propagation. The strain softening tensile behavior and softening of modulus considering a simple damage approach was verified by a simulation representing hydraulic fracturing stress measurement around a vertical well. Finally, the model was validated against deep fracture zone opening and surface uplift at In Salah with inverses analysis used to improve the match of simulation with field data. In Task 7, we developed a scheme based on inverse modeling that can be used to identify caprock leakage. Injection of fluid into a reservoir results in a time varying pressure profile that depends on the properties of the rock and the fluid. The presence of significant caprock leakage would effect this pressure profile and we used inverse modeling, namely the Levenberg-Marquardt method, to determine the leakage location from the pressure profile. A two-dimensional and a three-dimensional example based on published data were presented. The published simulation was run and its results were considered as “field” data. In the two-dimensional example, a simulation of CO 2 injection into a two-dimensional aquifer-caprock system, the caprock had a vertical fault through which leakage could occur. The location of this leakage was obtained from our inverse modeling scheme. In the three-dimensional example, the simulation domain had four geological layers, one of which was the injection zone that contained a horizontal injection well. We simulated fractures as high permeability gridblocks, introduced a fracture that spanned the caprock depth, and ran a simulation to obtain “field” data. Then, using our inverse modeling scheme, we obtained the location of that fracture.

58 GEOSCIENCES↗

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗

areaDetector: Software for 2-D Detectors in EPICS

areaDetector is a new EPICS module designed to support 2-D detectors. It is modular C++ code that greatly simplifies the task of writing support for a new detector. It also supports plugins, which receive detector data from the driver and process it in some way. Existing plugins perform Region-Of-Interest extraction and analysis, file saving (in netCDF, HDF, TIFF and JPEG formats), color conversion, and export to EPICS records for image display in clients like ImageJ and IDL. Drivers have now been written for many of the detectors commonly used at synchrotron beamlines, including CCDs, pixel array and amorphous silicon detectors, and online image plates.

99 GENERAL AND MISCELLANEOUS↗

Optimal Balance of Privacy and Utility with Differential Privacy Deep Learning Frameworks

As the number of online services has increased, the amount of sensitive data being recorded is rising. Simultaneously, the decision-making process has improved by using the vast amounts of data, where machine learning has transformed entire industries. This paper addresses the development of optimal private deep neural networks and discusses the challenges associated with this task. We focus on differential privacy implementations and finding the optimal balance between accuracy and privacy, benefits and limitations of existing libraries, and challenges of applying private machine learning models in practical applications. Our analysis shows that learning rate, and privacy budget are the key factors that impact the results, and we discuss options for these settings.

Kotevska, Olivera↗

Exploring Benchmarks for Self-Driving Labs using Color Matching

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.

Artificial intelligence↗

Manufacturing Cost Levelization Model – A User’s Guide

The Manufacturing Cost Levelization Model is a cost-performance techno-economic model that estimates total large-scale manufacturing costs for necessary to produce a given product. It is designed to provide production cost estimates for technology researchers to help guide technology research and development towards an eventual cost-effective product. The model presented in this user’s guide is generic and can be tailored to the manufacturing of any product, including the generation of electricity (as a product). This flexibility, however, requires the user to develop the processes and process efficiencies that represents a full-scale manufacturing facility. The generic model is comprised of several modules that estimate variable costs (material, labor, and operating), fixed costs (capital & maintenance), financing structures (debt and equity financing), and tax implications (taxable income after equipment and building depreciation, debt interest payments, and expenses) of a notional manufacturing plant. A cash-flow method is used to estimate a selling price necessary for the manufacturing plant to recover its total cost of production. A levelized unit sales price ($ per unit of product) is determined by dividing the net-present value of the manufacturing plant’s expenses ($) by the net present value of its product output. A user defined production schedule drives the cash-flow method that determines the levelized unit price. In addition, an analyst can increase the levelized unit price to include a gross profit margin to estimate a product sales price. This model allows an analyst to understand the effect that any input variables could have on the cost of manufacturing a product. In addition, the tool is able to perform sensitivity analysis, which can be used to identify the key variables and assumptions that have the greatest influence on the levelized costs. This component is intended to help technology researchers focus their research attention on tasks that offer the greatest opportunities for cost reduction early in the research and development stages of technology invention.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Compilation of PRF Canyon Floor Pan Sample Analysis Results

On September 28, 2015, debris collected from the PRF (236-Z) canyon floor, Pan J, was observed to exhibit chemical reaction. The material had been transferred from the floor pan to a collection tray inside the canyon the previous Friday. Work in the canyon was stopped to allow Industrial Hygiene to perform monitoring of the material reaction. Canyon floor debris that had been sealed out was sequestered at the facility, a recovery plan was developed, and drum inspections were initiated to verify no additional reactions had occurred. On October 13, in-process drums containing other Pan J material were inspected and showed some indication of chemical reaction, limited to discoloration and degradation of inner plastic bags. All Pan J material was sealed back into the canyon and returned to collection trays. Based on the high airborne levels in the canyon during physical debris removal, ETGS (Encapsulation Technology Glycerin Solution) was used as a fogging/lock-down agent. On October 15, subject matter experts confirmed a reaction had occurred between nitrates (both Plutonium Nitrate and Aluminum Nitrate Nonahydrate (ANN) are present) in the Pan J material and the ETGS fixative used to lower airborne radioactivity levels during debris removal. Management stopped the use of fogging/lock-down agents containing glycerin on bulk materials, declared a Management Concern, and initiated the Potential Inadequacy in the Safety Analysis determination process. Additional drum inspections and laboratory analysis of both reacted and unreacted material are planned. This report compiles the results of many different sample analyses conducted by the Pacific Northwest National Laboratory on samples collected from the Plutonium Reclamation Facility (PRF) floor pans by the CH2MHill’s Plateau Remediation Company (CHPRC). Revision 1 added Appendix G that reports the results of the Gas Generation Rate and methodology. The scope of analyses requested by CHPRC includes the determination of common anions, gamma spectrometry, metals, corrosivity, organics and alpha spectrometry (note: alpha spectrometry was cancelled during the performance of this work with concurrence from CHPRC). Results may help elucidate the components that led to the unexpected reaction in the canyon as well as inform the radiological and hazardous characteristics. The specific anions, gamma emitters, organics and metals requested by CHPRC are provided in the analytical reports sections. The individual analyses were conducted under the Plutonium Finishing Plant (PFP) Floor Pan Evaluation Project Quality Assurance Project Plan (PFP Floor Pan Evaluation QAPP, Revision 0.) developed by PNNL specifically for this project. The final reports for each analysis set are included in this compilation of the results. Each package was reviewed under the PFP Floor Pan Evaluation Project Quality Assurance Project Plan so no additional reviews were conducted in this compilation task. The Gas Generation Rates in Appendix G were conducted under the PNNL “How Do I…” quality assurance program and were NOT conducted under the Plutonium Finishing Plant (PFP) Floor Pan Evaluation Project Quality Assurance Project Plan (PFP Floor Pan Evaluation QAPP, Revision 0.).

36 MATERIALS SCIENCE↗

Potential Research and Development Opportunities for Light Water Reactor Spent Nuclear Fuel at INL

This report documents the commercial spent nuclear fuel currently in storage at Idaho National Laboratory with a specific focus on the potential research and development (R&D) opportunities for this material. Commercial spent nuclear fuel is stored in dry casks on the INL site at the Idaho Nuclear Technology and Engineering Center (INTEC, formerly the Idaho Chemical Processing Plant or ICPP). This spent fuel was part of the DOE-industry cooperative dry cask demonstration project that began in 1983 and from historical fuel testing and treatment activities that had been performed at the Test Area North (TAN)-607 facility. Most of the fuel is “low burnup,” but given that it was removed from the respective reactors between 1970 and 1985, it was representative for its time. The majority of the fuel is of the 15×15 Westinghouse PWR variety, though additional fuel types (e.g., TN-BRP) and configurations are also stored. Potential R&D opportunities identified are (1) the REA-2023 cask, (2) the TN-BRP cask, and (3) the Castor V/21 cask. Fuel from the TN-24P may be an alternative to the intact assemblies in the Castor V/21. Specifically, the REA-2023 cask contains 9 rods that have been exposed to air since 2005. These rods have a detailed pre-loading characterization and thus any changes in corrosion or geometry can most likely be attributed to the storage environment. In addition, similar rods to the nine in REA-2023 reside in the Castor V/21 cask whose environment has been maintained with inert nitrogen. The Castor V/21 cask also contains intact PWR assemblies that could be used to perform limited confirmation of the pyroprocessing approach. An alternative to the use of the Castor assemblies for pyroprocessing is the consolidated fuel that is stored in the TN-24P, which would not require removal from the assembly grid since it has already been packaged in accessible two-piece shell strongback containers. The TN-BRP cask contains a number of Gd-doped, low burnup assemblies that could be of use to validate code packages used to justify burnup-up credit for boiling water reactors (BWRs). The INL dry casks are stored on the CPP-2707 pad at INTEC, adjacent to the CPP-603 Irradiated Fuel Storage Facility, which incorporates a dry hot cell that has the potential to receive a full scale commercial cask of the types identified. Several evaluations have been made regarding this task, including full scale mockup testing of the physical clearances required to remove and handle fuel assemblies and components. A proposed schedule of 14 months and cost of $5.3 million was the outcome of analysis performed by Fluor Idaho and is included as Appendix A & B. In addition to the spent fuel at INL, there is also a full-scale mockup assembly that was fabricated for the Protypical Consolidation Demonstration Project to validate fuel rod consolidation approaches. The assembly was fabricated by Westinghouse as a 15 x 15 PWR, using Zircaloy-4 tubing and steel end fittings in accordance with product specifications. The only departure from specification is the use of copper metal in lieu of uranium oxide pellets to achieve a weight that is within 10% of the standard.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗