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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SERIIUS-MAGEEP Visiting Scholars Program

Recent studies have assessed closed-loop supercritical carbon dioxide (s-CO 2 ) Brayton cycles to be a higher energy-density system in comparison to equivalent superheated steam Rankine systems. At turbine inlet conditions of 700°C and 20 MPa, a cycle thermal efficiency of ~50% can be achieved. Achieving these high efficiencies will help concentrating solar power (CSP) technologies to become a competitive alternative to current power generation methods. To incorporate an s-CO 2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 700°C (at 20 MPa) is necessary. To satisfy the temperature requirements of an s-CO 2 Brayton cycle with recuperation and recompression, the s-CO 2 must undergo a temperature rise of ~200°C as it flows through the solar receiver. The main objective is to develop an optical-thermal-fluid and structural model to validate a tubular receiver that will receive a heat input ~0.33 MWth from the heliostat field at the National Solar Thermal Test Facility (NSTTF), Albuquerque, NM, USA. We also commenced the development of computational models and testing of air receivers being developed by the Indian Institute of Science (IISc) and the Indian Institute of Technology in Bombay (IIT-B). The helical tubular receiver is expected to counteract the effect of thermal expansion while using a cavity to reduce the radiative and convective losses. Initially, this receiver will be tested for a temperature range of 100-300°C under 1 MPa of pressurized air. The helical air receiver will be exposed to 10kWth to achieve a temperature rise of ~200°C. Preliminary tests to validate the modeling will be performed before the design and construction of a larger scale receiver. Lastly, I focused on the development of a new computational tool that would allow us to perform a nodal creep-fatigue analysis on the receivers and heat exchangers being developed. This tool was developed using MATLAB and is capable of processing the results obtained from ANSYS Fluent and Structural combined, which was limited when using commercial software. The main advantage of this code is that it can be modified to run in parallel making it more affordable and faster compared to commercial codes available. The code is in the process of validation and is currently being compared to nCode Design Life.

25 ENERGY STORAGE↗
DOE OSTI2025

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Basic Research Needs for Microelectronics

Since the invention of the integrated circuit in 1958, advances in microelectronics have followed Moore’s law and other scaling laws. These have led to over a billion-fold increase in the number of transistors on a chip. The Department of Energy’s Office of Science (DOE-SC) programs have always been at the cutting edge of microelectronics, making major contributions to the scientific understanding, materials, and advanced instrumentation that enabled innovations to promote scaling. This has driven transformative advances in microelectronics for the challenging demands of DOE’s high performance computing and science facilities. Now, strong evidence exists that scaling is approaching its physical and economic limits, and yet, the growth of data-centric computing and sensor networks is redefining computing workloads and microelectronics needs. In addition, greatly improved microelectronics are needed for the nation’s electricity grid if it is to be energy-efficient, resilient to natural phenomena and intentional attack, and agile in adapting to fluctuations in demand and power generation. Sustained and rapid progress in microelectronics science and technology from millivolt to megavolt scales is thus essential if we are to continue pushing the boundaries of science within DOE, and more significantly, to continue to lead the global information and power technology revolution. In October 2018, DOE-SC convened a workshop to address Basic Research Needs for Microelectronics by a “co-design” approach. Participants focused on scientific issues associated with advanced microelectronics technologies for applications relevant to the DOE mission, including computing, power grid management, and science facility workloads. (Topics of direct relevance to quantum information science and quantum computing were outside the scope of this workshop.) The workshop was organized around microelectronics needs for three areas: 1) future DOE-SC facilities, 2) high performance computing beyond exascale (a billion billion calculations per second), and 3) power control, conversion, and detection for a modernized electrical grid and related high power applications. Panels were formed around each of these areas, with a fourth panel formed to address Crosscutting Research. Workshop participants were asked to focus on a co-design innovation ecosystem in which materials, chemistries, devices, systems, architectures, algorithms, and software are researched and developed in a closely integrated fashion, with feedback and interdisciplinary collaboration at each interface in this microelectronics technology hierarchy. The panels identified the five Priority Research Directions on the following page.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TH-E-209-01: Fluoroscopic Dose Monitoring and Patient Follow-Up Program at Massachusetts General Hospital

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

graphenv: a Python library for reinforcement learning on graph search spaces

Many important and challenging problems in combinatorial optimization (CO) can be expressed as graph search problems, in which graph vertices represent full or partial solutions and edges represent decisions that connect them. Graph structure not only introduces strong relational inductive biases for learning (Battaglia et al., 2018) - in this context, by providing a way to explicitly model the value of transitioning (along edges) between one search state (vertex) and the next - but lends itself to problems both with and without clearly defined algebraic structure. For example, classic CO problems on graphs such as the Traveling Salesman Problem (TSP) can be expressed as either pure graph search or integer programs. Other problems, however, such as molecular optimization, do no have concise algebraic formulations and yet are readily implemented as a graph search (V. et al., 2022; Zhou et al., 2019). Such "model-free" problems constitute a large fraction of modern reinforcement learning (RL) research owing to the fact that it is often much easier to write a forward simulation that expresses all of the state transitions and rewards, than to write down the precise mathematical expression of the full optimization problem. In the case of molecular optimization, for example, one can use domain knowledge alongside existing software libraries to model the effect of adding a single bond or atom to an existing but incomplete molecule, and let the RL algorithm build a model of how good a given decision is by "experiencing" the simulated environment many times through. In contrast, a model-based mathematical formulation that fully expresses all the chemical and physical constraints is intractable. In recent years, RL has emerged as an effective paradigm for optimizing searches over graphs and led to state-of-the-art heuristics for games like Go and chess, as well as for classical CO problems such as the TSP. This combination of graph search and RL, while powerful, requires non-trivial software to execute, especially when combining advanced state representations such as Graph Neural Networks (GNN) with scalable RL algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Nek5000 developments in support of industry and the NRC

This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics verification and validation (V&V) work has focused in three areas of Nek5000 V&V-driven development. First, in a close collaborative effort with the U. S. Nuclear Regulatory Commission (NRC) staff, we have continued V&V efforts for the HYMERES-2 project using the OECD/NEA sponsored testing in the PSI PANDA facility. This year’s focus of ANL-NRC collaboration involves Nek5000 setups and validation for a range of problems relevant to and including the HYMERES-2 benchmark from PSI. The primary outcome of this year efforts is a more efficient geometry and inlet modeling simplification after a careful sensitivity study of the inlet profiles and pipe geometries. The resulting modeling choice of a short recycling/fully-developed turbulent inlet is within the experimental uncertainty estimate. This finding simplifies the next step of the cross-V&V HYMERES-2 project. In addition, the ANL team continue to provide assistance to the NRC staff in the form of Nek5000 application support in general and on the use of the HPC platforms of ALCF and INL in particular. This supports the NRC’s assessment of Nek5000 for use with the NRC Blue CRAB code suite. Second, we have implemented and tested more robust model of URANS, namely the k – τ model, a variant of the k-ω model, along with other improvements to RANS Nek5000 modeling in general. Because of its demonstrated robustness and stability, the k – τ model is the only RANS model that has been implemented in the new GPU version of the Nek5000 code, nekRS. Lastly, we report the initial implementation of Jacobian-free Newton Krylov approach to the direct Newton method for steady fluid solvers aimed at acceleration of RANS modeling and at IC improvement for LES campaigns. Also leveraging the Exascale Computing Project (ECP) ANL/CEED & SMR team’s software development effort to support NEAMS problems at large scale of the advanced computing architectures, NekRS, a GPU variant of Nek5000, built on top of kernels from libParanumal using OCCA for portability, has been successfully run on the full system of Summit (4608 nodes, 27648 GPUs).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
DOE OSTI2019

Performance and energy impact of OpenMP runtime configurations on power constrained systems

Energy consumption of an application has attained the same vitality as execution time in current HPC systems, primarily due to the massive energy consumption of these systems and consequently substantial energy bills. This fact forced software developers as well as hardware vendors to put an extensive focus on energy consumption. This focus becomes even more crucial in power constrained systems, where the amount of power dedicated to applications is limited. In such systems, finding the optimal balance between execution time and energy consumption has a significant impact on utilizing these systems efficiently. A programming model is a necessary layer where optimizations can be applied to find the optimal balance. OpenMP is a standard programming model for intra-node parallelism. In this paper, we give a detailed analysis of how to optimize the execution time and energy consumption of an OpenMP application using the OpenMP runtime environment at different power levels. We studied twenty-eight OpenMP parallel regions from five NAS Parallel Benchmark (NPB) applications. Based on the study, we show that for a given power level, a suitable selection of OpenMP runtime parameters can improve the execution time and energy consumption of a parallel region up to 67% and 72%, respectively. We also show that these fine-grained improvements resulted in up to 26% of execution time and 38% of energy consumption improvement for a given OpenMP application. We finally observed that optimizing the energy consumption behavior alone across all power levels regardless of execution time behavior can lead to an additional energy consumption improvement of up to 55%. However, this improvement comes at the expense of execution time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-48: A Multi-Institutional Study of Independent Dose Verification for Conventional, SRS and SBRT

Purpose: To show the results of a multi-institutional study of the independent dose verification for conventional, Stereotactic radiosurgery and body radiotherapy (SRS and SBRT) plans based on the action level of AAPM TG-114. Methods: This study was performed at 12 institutions in Japan. To eliminate the bias of independent dose verification program (Indp), all of the institutions used the same CT-based independent dose verification software (Simple MU Analysis, Triangle Products, JP) with the Clarkson-based algorithm. Eclipse (AAA, PBC), Pinnacle{sup 3} (Adaptive Convolve) and Xio (Superposition) were used as treatment planning system (TPS). The confidence limits (CL, Mean±2SD) for 18 sites (head, breast, lung, pelvis, etc.) were evaluated in comparison in dose between the TPS and the Indp. Results: A retrospective analysis of 6352 treatment fields was conducted. The CLs for conventional, SRS and SBRT were 1.0±3.7 %, 2.0±2.5 % and 6.2±4.4 %, respectively. In conventional plans, most of the sites showed within 5 % of TG-114 action level. However, there were the systematic difference (4.0±4.0 % and 2.5±5.8 % for breast and lung, respectively). In SRS plans, our results showed good agreement compared to the action level. In SBRT plans, the discrepancy between the Indp was variable depending on dose calculation algorithms of TPS. Conclusion: The impact of dose calculation algorithms for the TPS and the Indp affects the action level. It is effective to set the site-specific tolerances, especially for the site where inhomogeneous correction can affect dose distribution strongly.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

University Coalition for Fossil Fuel Energy Research

Following a nationwide open competition, the University Coalition for Fossil Energy Research (UCFER) was established in October 2015 through a cooperative agreement between Penn State and the Department of Energy (DOE) National Energy Technology Laboratory (NETL). Penn State lead UCFER with the objective of advancing basic and applied research for clean and low-carbon energy based on fossil fuels in support of the DOE’s mission. UCFER focused on research that improves the efficiency of production and use of fossil energy resources, while minimizing the environmental impacts and reducing greenhouse gas emissions. Penn State lead a team of nine universities (Massachusetts Institute of Technology, The Pennsylvania State University, Princeton University, Texas A&M University, University of Kentucky, University of Southern California, The University of Tulsa, University of Wyoming, and Virginia Polytechnic and State University) during the competition stage, adding seven more universities in 2017 (Carnegie Mellon University, Louisiana State University, The Ohio State University, University of North Dakota, University of Pittsburgh, University of Utah, and West Virginia University). This Coalition exhibited a wide geographical distribution across the U.S. bringing a wide variety of fossil energy expertise. This national university alliance was a major collaborative effort with NETL to address specific topics of R&D in NETL’s mission area, which involved one or more of NETL’s five core competencies (Geologic and Environmental Systems, Materials Engineering and Manufacturing, Energy Conversion Engineering, Systems Engineering and Analysis, and Computational Science and Engineering). The first five to six months of the project was the definitization stage. During this period, Penn State worked closely with NETL to finalize the Coalition organizational structure and By- Laws, prepare a statement of substantial involvement and a statement of project objectives, and develop operations and membership plans. A major component of this stage included preparing an execution plan to solicit research, evaluate proposals, recommend selected projects to NETL, and award projects. In addition, a plan was prepared to monitor projects, review projects, disseminate knowledge from research projects and develop an online system for Coalition research portfolio management. This included developing a website and several databases. The first of six rounds of solicitations started in mid-2016. Projects from the sixth solicitation started February 1, 2021, and ended January 31, 2023. Projects that were selected represented twelve technology lines. Approximately $16.6 million in funding was available for the six solicitations. Most of the funding was provided by DOE, Office of Fossil Energy (DOEFE) with the DOE Fuel Cells Technologies Office (DOE-FCTO) providing funding for a few projects. Coalition universities submitted 259 proposals in response to the solicitations, requesting approximately $67.0 million in funding, and forty-three projects were selected. However, one project withdrew after the principal investigator left the university. The management of the Coalition projects was a major activity by Penn State. Managing the Coalition projects consisted of monitoring the projects, reviewing the projects through annual technical review meetings, disseminating knowledge from the research projects, and developing an online system for Coalition research portfolio management. Penn State’s OMT monitored projects to ensure that all milestones (technical, schedule, budget) were met, expenditures were allowable, cost share (when applicable) were reported, and all technical reports were submitted. The OMT also posted the technical reports electronically on a secure members-only website for access and review by the Coalition members. Disseminating knowledge from the research projects was done through a website, newsletters, various meetings, conferences, journal articles, publicity/press releases, and project summaries that were prepared after each project was completed. Penn State kept NETL apprised of UCFER progress through quarterly reports (thirtyone were submitted by Penn State), verbal and written communications, yearly updates at the annual technical review meetings, and cost accrual reports. The UCFER project had a significant impacty. The UCFER program established the first national university alliance in fossil energy research with a major collaboration effort with DOE NETL that addressed specific topics in NETL’s research and development mission areas. It generated inter-university collaborations, which was another program interest. Twenty-two out of 259 proposals contained collaborations (≈8.5%) and three of forty-two funded projects involved inter-university collaborations (≈7.0%). The forty-two funded projects provided support at fourteen universities involving 269 personnel. Research was conducted by 106 faculty, 115 graduate and undergraduate students, forty-six research staff and post-doctoral scholars, and two visiting scholars. Students and post-doctoral scholars were also on-site at NETL through CRADAs. In addition, non-Coalition participants included six universities and sixteen companies and national laboratories. The non-Coalition participants were involved as subcontractors, providers of cost share, performed unpaid consultation and sample analysis, served as advisory board members, or were providers of samples and materials for testing. UCFER also produced visibility in that fifty-six refereed journal articles were published, fifty-seven conference papers and twenty-three posters were prepared, 190 presentations were given, eight patent applications were filed, two books/book chapters were written, and ten software codes were developed. Collaboration between NETL and the individual projects was a major requirement for all funded projects. This included NETL staff time to support collaboration, consultation, technical guidance, sample preparation and analysis, internships at NETL, on-site testing and equipment usage by Coalition participants at NETL, co-mentoring students, and coauthoring journal articles and conference papers. Collaboration was impacted by COVID-19 in that not all on-site activities could be performed. NETL personnel were coauthors on eight of the conference papers (fourteen percent of the conference papers that were prepared) and seventeen of the journal articles (thirty percent of the journal articles that were prepared). A website was developed for an online proposal solicitation and review process and to provide exposure to UCFER. A website analysis highlighted the large amount of member and general public interest in UCFER by interpreting access statistics from March 2016 through June 2023. Visitors to the site originated from many different organizations, businesses, and countries. The website provided a means to disseminate information to both the general public and the UCFER members and was successfully used for outreach activities. In addition, NETL required that RFP release, proposal submission, and proposal reviews all be performed online. Penn State successfully developed these capabilities in a secure section of the website, which were used throughout the UCFER project. It is recognized that each project had its technical successes. In addition, highlighted successes were compiled and summarized from the research projects. Information was requested from the PIs of completed projects. In addition, Penn State’s Operations Management Team reviewed subcontract reports to identify project successes. Examples of information requested from PIs included (not all-inclusive): new projects that have been funded as a result of UCFER funding; new commercial products; establishment of a new center; new patent; new software; best paper awards; highly-cited work; and graduate student successes. A total of forty-eight highlighted successes were reported.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities

Scientific user facilities, such as synchrotron beamlines, are equipped with a wide array of hardware and software tools that require a codebase for human-computer-interaction. This often necessitates developers to be involved to establish connection between users/researchers and the complex instrumentation. The advent of generative AI presents an opportunity to bridge this knowledge gap, enabling seamless communication and efficient experimental workflows. Here we present a modular architecture for the Virtual Scientific Companion by assembling multiple AI-enabled cognitive blocks that each scaffolds large language models (LLMs) for a specialized task. With VISION, we performed LLM-based operation on the beamline workstation with low latency and demonstrated the first voice-controlled experiment at an x-ray scattering beamline. The modular and scalable architecture allows for easy adaptation to new instruments and capabilities. Development on natural language-based scientific experimentation is a building block for an impending future where a science exocortex—a synthetic extension to the cognition of scientists—may radically transform scientific practice and discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accessible, uniform protein property prediction with a scikit-learn based toolset AIDE

Summary Protein property prediction via machine learning with and without labeled data is becoming increasingly powerful, yet methods are disparate and capabilities vary widely over applications. The software presented here, “Artificial Intelligence Driven protein Estimation (AIDE)”, enables instantiating, optimizing, and testing many zero-shot and supervised property prediction methods for variants and variable length homologs in a single, reproducible notebook or script by defining a modular, standardized application programming interface (API), i.e. drop-in compatible with scikit-learn transformers and pipelines. Availability and implementation AIDE is an installable, importable python package inheriting from scikit-learn classes and API and is installable on Windows, Mac, and Linux. Many of the wrapped models internal to AIDE will be effectively inaccessible without a GPU, and some assume CUDA. The newest stable, tested version can be found at https://github.com/beckham-lab/aide_predict and a full user guide and API reference can be found at https://beckham-lab.github.io/aide_predict/. Static versions of both at the time of writing can be found on Zenodo.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Reverse engineering (RE) analysts struggle to address critical questions about the safety of binary code accurately and promptly, and their supporting program analysis tools are simply wrong sometimes. The analysis tools have to approximate in order to provide any information at all, but this means that they introduce uncertainty into their results. And those uncertainties chain from analysis to analysis. We hypothesize that exposing sources, impacts, and control of uncertainty to human binary analysts will allow the analysts to approach their hardest problems with high-powered analytic techniques that they know when to trust. Combining expertise in binary analysis algorithms, human cognition, uncertainty quantification, verification and validation, and visualization, we pursue research that should benefit binary software analysis efforts across the board. We find a strong analogy between RE and exploratory data analysis (EDA); we begin to characterize sources and types of uncertainty found in practice in RE (both in the process and in supporting analyses); we explore a domain-specific focus on uncertainty in pointer analysis, showing that more precise models do help analysts answer small information flow questions faster and more accurately; and we test a general population with domain-general sudoku problems, showing that adding "knobs" to an analysis does not significantly slow down performance. This document describes our explorations in uncertainty in binary analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Reactivity Effects at Mayak Production Association January 2, 1958 Criticality Accident Using Serpent 2 and OpenFOAM

The process nuclear criticality accident that occurred at the Mayak Production Association (Chelyabinsk 40) on January 2, 1958 involving a vessel of uranyl nitrate solution claimed the lives of three workers and left a fourth worker with continuing health problems. There are a myriad of uncertain parameters involved with this accident: What was the molarity of the solution? How much solution was in the vessel at the time of the accident? In what position was the vessel and the solution when it went critical? How important was the impact of reflection due to the workers and/or the floor? These uncertain parameters have made this accident particularly difficult to analyze in the past. This work aims to lower the uncertainty on some of these parameters. A most-probable solution composition is determined by comparing literature on the physical properties of uranyl nitrate solutions to those presented in LA-13638, which describes the accident in question. Using this most-probable solution, the main contributions to the reactivity of the system and hence the eventual accident, are identified through Serpent 2 and OpenFOAM analyses. Serpent 2, a Monte Carlo software tool, is used to perform calculations of the reactivity effects of lowering the vessel toward the floor and the reactivity added by the close proximity of workers. OpenFOAM, a C++ partial differential equation solver toolkit, is used to simulate the fluid inside the vessel as the vessel is tipped. This is done by treating the solution and air inside the vessel as two incompressible, isothermal, and immiscible fluids using a volume of fluid (VoF) approach. The goal of this approach is simply to track the interface between the two fluids, and hence give an accurate description of the geometrical structure of the solution as the vessel is tipped. These two unique tools are then coupled to provide a time-dependent flow simulation to study the effect that the changing geometrical structure had on the criticality of the system, which is novel to the criticality safety field. This work provides a more accurate picture of the accident going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

DASAO: software tool for the management of safeguards, waste and decommissioning

Decommissioning of nuclear facilities is a complex process involving operations such as detailed surveys, decontamination and dismantling of equipment's, demolition of buildings and management of resulting waste and nuclear materials if any. This process takes place in a well-developed legal framework and is controlled and followed-up by stakeholders like the Safety Authority, the Radwaste management Agency and the Safeguards Organism. In the framework of its nuclear waste and decommissioning program and more specifically the decommissioning of the BR3 reactor, SCK-CEN has developed different software tools to secure the waste and material traceability, to support the sound management of the decommissioning project and to facilitate the control and the follow-up by the stakeholders. In the case of Belgium, it concerns the Federal Agency for Nuclear Control, the National Agency for radioactive waste management and fissile material and EURATOM and IAEA. In 2005, Belgonucleaire decided to shutdown her Dessel MOX fuel fabrication plant and the production stopped in 2006. According to the final decommissioning plan ('PDF') approved by NIRAS, the decommissioning works should start in 2008 at the earliest. In 2006, the management of Belgonucleaire identified the need for an integrated database and decided to entrust SCK-CEN with its development, because SCK-CEN relies on previous experience in comparable applications namely already approved by authorities such as NIRAS, FANC and EURATOM. The main objectives of this integrated software tool are: - simplified and updated safeguards; - waste and material traceability; - computerized documentation; - support to project management; - periodic and final reporting to waste and safety authorities. The software called DASAO (Database for Safeguards, Waste and Decommissioning) was successfully commissioned in 2008 and extensively used from 2009 to the satisfaction of Belgonucleaire and the stakeholders. SCK-CEN is now implementing a simplified release of the software for the management of the decommissioning of the Thetis reactor. Its decommissioning will start in March 2013 and will be completed by the end of 2014. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

SU-E-T-372: Evaluation and Comparison of Second-Check Monitor Unit Calculation Software with Pinnacle Treatment Planning System

Purpose: The purpose of this study was to evaluate and compare the accuracy of dose calculation algorithms in the second check software programs Radcalc, Diamond, IMSure, and MUcheck, against the Pinnacle3 treatment planning system (TPS). Methods: Baseline accuracy of the second check software was established by comparison against Pinnacle TPS data using open square fields of 5, 10, 20, 30 and 40cm in a SAD setup. 18 previously treated patients’ files were exported from the Pinnacle3 TPS to each of the four second check softwares, consisting of 146 step and shoot intensity modulated radiotherapy (IMRT) beams and 60 Smart Arcs. Monitor unit (MU) calculated in each of the software were compared with the TPS and the values were represented as a percent difference. Open fields were calculated as a baseline for each software’s accuracy using 5×5, 10×10, 20×20, 30×30, and 40×40 fields. Box plots, Pearson correlation, and Bland-Altman analysis were used for comparison of the results. Results: The baseline accuracy was established to within 0.6%, −1.4%, −0.2%, and −1.0% for Diamond, IMSure,MUcheck, and Radcalc, respectively. In the clinical data, the dose difference represented as mean ± 1 standard deviation were 0.7%±0.1%, −0.3%±0.1%, −1.5%±0.1%, and 0.4%±0.0% for Diamond, IMSure, MUcheck, and Radcalc, respectively Conclusion: The implementation of Clarkson algorithm for the dose calculation between each of the software in question can vary considerably. The currently used second check software, Radcalc has shown the best agreement on average, variance, and smallest percent range from Pinnacle3 TPS values. The closest in average percent difference from the TPS data was the IMSure software, but has significantly larger variance and percent range. The mean percent differences in Diamond and MUcheck were significantly larger than Radcalc and IMSure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-11: A New Optical Method to Register Patient External Motion

Purpose: To devise and implement a new system to measure and register the patient motion during radiotherapy treatments. Methods: The system can obtain the position of several points in the 3D-space, through their projections in the 2D-images recorded by two cameras. The algorithm needs a series of constants, that are obtained using the images of a calibrated phantom.To test the system, some adhesive labels were placed on the surface of an object. Two cameras recorded the moving object over time. An in-house developed software localized the labels in each image. In the first pair of images, the program used a first approximation given by the user. In the subsequent images, it used the last position as an approximate location. The final exact coordinates of the point were obtained in a two-step process using the contrast of the images. From the 2D-positions of the point in each frame, the 3D-trajectories of each of these marks were obtained.The system was tested with linear displacements, oscillations of a mechanical oscillator, circular trajectories of a rotating disk, and with respiratory motion of a volunteer. Results: Trajectories of several points were reproduced with sub-millimeter accuracy in the three directions of the space. The system was able to follow periodic motion with amplitudes lower than 0.5mm; and trajectories of rotating points at speeds up to 200mm/s. The software could also track accurately the respiration motion of a person. Conclusion: A new, inexpensive optical tracking system for patient motion has been demonstrated. The system detects motion with high accuracy. Installation and calibration of the system is simple and quick. Data collection is not expected to involve any discomfort for the patient, nor any delay for the treatment. The system could be also used as a method of warning for patient movements, and for gating. We acknowledge financial support from Fundacion Mutua Madrilena, Madrid, Spain.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗