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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Thermal-Hydraulic and Neutronic Phenomena Important in Modeling and Simulation of Liquid-Fuel Molten Salt Reactors

In this paper, we discuss liquid-fuel molten salt (cooled) reactors (MSRs); how they will operate under normal, transient, and accident conditions; and the results of an expert elicitation to determine the corresponding thermal-hydraulic and neutronic phenomena important to understanding their behavior. Identifying these phenomena will enable the U.S. Nuclear Regulatory Commission (NRC), U.S. Department of Energy, and industry to develop or identify modeling functionalities and tools required to carry out confirmatory and licensing analyses that examine the validity and accuracy of an applicant's calculations and help determine the margin of safety in plant design. The NRC frequently does an expert elicitation using a Phenomena Identification and Ranking Table (PIRT) to identify and evaluate the state of knowledge of important modeling phenomena. However, few details about the design of these reactors and the sequence of events during accidents are known, so the process used was considered a preliminary PIRT. A panel comprising a group of subject matter experts met to define phenomena that would need to be modeled and considered the impact/importance of each phenomenon with respect to specific figures of merit (FoMs) (e.g., salt temperature, velocity, and composition). Each FoM reflected a potential impact on radionuclide release or loss of a barrier to release. The panel considered what the path forward might be with respect to being able to model the phenomenon in a simulation code. Results are explained for both thermal and fast spectrum designs, with an emphasis on the thermal-hydraulic takeaways. It was concluded that compared to light water reactors, the lack of high-pressure operation, energetic break flow, depressurization, and quench front tracking may simplify some aspects of an MSR analysis. However, MSRs have new phenomena both for a license applicant and NRC confirmatory analysis. There is a need for enhanced understanding of physical properties for MSRs that encompass several individual thermophysical properties, including thermal conductivity, viscosity, specific heat, density, optical properties, thermodynamic properties, volatilities, solubilities, etc. Salt composition is closely linked to both these properties and the neutronics of the system. Additionally, the large number of MSR concepts and system designs means that there is wide variation in the potential modeling needs for these systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Overview of the SAS4A Metallic Fuel Models and Extended Analysis of a Postulated Severe Accident in the Prototype Gen-IV Sodium-Cooled Fast Reactor

The SAS4A safety analysis code, originally developed for the analysis of postulated severe accidents in oxide fuel sodium-cooled fast reactors (SFRs), has been significantly extended to allow the mechanistic analysis of severe accidents in metallic fuel SFRs. The SAS4A metallic fuel models simulate the metallic fuel thermomechanical and chemical behavior and track the evolution and relocation of multiple fuel and cladding components during the pretransient irradiation and during the postulated accident, allowing an accurate description of the changes in the local fuel composition. The local fuel composition determines the fuel thermophysical properties, such as freezing and melting temperatures, which in turn affect the fuel relocation behavior and ultimately the core reactivity and power history during the postulated accidents. Models describing the fuel-cladding interaction and eutectic formation, the effects of the in-pin sodium on the in-pin fuel relocation, and the postfailure reentry of the molten fuel and fission gas from the pin plenum have also been added. This paper provides an overview of the SAS4A key metallic fuel models emphasizing the postfailure metallic fuel relocation models included in the LEVITATE-M module of SAS4A. The capabilities of the SAS4A metallic fuel models are illustrated through an extended SAS4A analysis of a postulated unprotected loss-of-flow and transient-overpower accident in the metallic fuel prototype Gen-IV sodium fast reactor. The results show that the maximum relative power reached during the postulated accident is 1.19 P 0 . The favorable characteristics of the metallic fuel cause a significant decrease in net reactivity and relative power due to prefailure in-pin fuel relocation. Furthermore, negative net reactivity values persist after cladding failure, and the postfailure fuel relocation events occur at low and decreasing power levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Containerization of Phase-2 Tracker Data Acquisition and Control Framework

The CMS Experiment has started an extensive upgrade program in the context of the High-Luminosity phase of the LHC (Phase-2). In order to cope with the highly demanding High-Luminosity conditions, CMS will need a completely new inner and outer tracking detectors. On top of R&D development, a Data AcQuisition (DAQ) software is being developed along with different applications to control, monitor and validate the newly produced modules of the future tracker. As more and more developers are getting involved to maintain all those codes, an environment where software and applications can work independently of the host machine operating system is crucial. The Phase-2 Tracker group decided to make use of Docker as containerization solution for its framework. This poster describes the containerization of DAQ software/applications utilized to test and validate the Tracker modules. This includes continuous integration and continuous deployment (so-called CI/CD) and running GUI applications inside containers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Memory object tagged memory monitoring method and system

Described are a method and processing apparatus to tag and track objects related to memory allocation calls. An application or software adds a tag to a memory allocation call to enable object level tracking. An entry is made into an object tracking table, which stores the tag and a variety of statistics related to the object and associated memory devices. The object statistics may be queried by the application to tune power/performance characteristics either by the application making runtime placement decisions, or by off-line code tuning based on a previous run. The application may add a tag to a memory allocation call to specify the type of memory characteristics requested based on the object statistics.

Roberts, David A.↗
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Improvements to Contributions from Neutron Inelastic Scattering for Next-Event Estimators in MCNP ® Software

An improvement to the handling of contributions from neutron inelastic scattering to next-event estimators has been implemented in the MCNP6 ® software for release with version 6.3.1. The kinematic equations that govern the outgoing energy of inelastic neutron scattering contributions to next-event estimators have two roots. Historically, the implementation in the MCNP coding has only used the upper root to the quadratic equation. This includes all versions predating version 6.3.1 including all versions of MCNP5 and MCNPX software. However, a review of the neutron next-event estimator physics has shown that this does not reproduce the track-length estimator results at low energies. Several examples are presented that test single neutron inelastic scattering reaction types, Level Scattering (Law 3), Tabulated Energy Angle (Law 61), and Kalbach-Mann distribution (Law 44). The test problems compare the track-length estimator (f4 tally) in the MCNP software, with the existing implementation of the neutron next-event estimator (f5 tally), and the modified changes to the neutron next-event estimator implementation. As the MCNP implementation ignores the lower root, the unmodified neutron next-event estimators will generally underestimate the lower energy contribution. However, a second issue with the Kalbach-Mann distribution (Law 44) implementation allows contributions to backward scattering in the center-of-mass frame that is not kinematically possible, thus overestimating backward scattering contributions. A third issue with the way the MCNP implementation handles floating point comparison for scattering directly ahead or directly backward in the center-of-mass frame generally leads to underestimation (except for backwards scattering for Law 44).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Evolution of an Asteroid Family under YORP, Yarkovsky, and Collisions

Any population of asteroids, like asteroid families, will disperse in semimajor axis due to the Yarkovsky effect. The amount of drift is modulated by the asteroid spin state evolution, which determines the balance between the diurnal and seasonal Yarkovsky forces. The asteroid’s spin state is, in turn, controlled in part by the Yarkovsky–O’Keefe–Radzievskii–Paddack (YORP) effect. The otherwise smooth evolution of an asteroid can be abruptly altered by collisions, which can cause impulsive changes in the spin state and can move the asteroid onto a different YORP track. In addition, collisions may also alter the YORP parameters by changing the superficial features and overall shape of the asteroid. Thus, the coupling between YORP and Yarkovsky is also strongly affected by the impact history of each body. To investigate this coupling, we developed a statistical code modeling the time evolution of semimajor axis under YORP–Yarkovsky coupling. It includes the contributions of NYORP (normal YORP), TYORP (tangential YORP), and collisions whose effects are deterministically calculated and not added in a statistical way. We find that both collisions and TYORP increase the dispersion of a family in semimajor axis by making the spin axis evolution less smooth and regular. We show that the evolution of a family’s structure with time is complex and collisions randomize the YORP evolution. In our test families, we do not observe the formation of a “YORP-eye” in the semimajor axis versus diameter distribution, even after a long period of time. If present, the “YORP-eye” might be a relic of an initial ejection velocity pattern of the collisional fragments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Accurate effective fluid approximation for ultralight axions

Ultralight axions are theoretically interesting and phenomenologically rich dark sector candidates, but they are difficult to track across cosmological timescales because of their fast oscillations. We resolve this problem by developing a novel method to evolve them efficiently and accurately. We first construct an exact effective fluid which at late times matches the axion but which evolves in a simple way. We then approximate this evolution with a carefully chosen equation of state and sound speed. With our scheme we find that we can obtain subpercent accuracy for the linear theory suppression of axion density fluctuations relative to that of cold dark matter without tracking even a single complete oscillation of the axion field. Furthermore, we use our technique to test other approximation schemes and to provide a fitting formula for the transfer function for the matter power spectrum in linear theory in axion models. Implementing our approach in existing cosmological axion codes is straightforward and will help unleash the potential of high-precision next-generation experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

NGEE Arctic Plant Traits: Plant Community Composition, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

This dataset reports the characteristics of the dominant vegetation communities at the NGEE Arctic Kougarok field site, Kougarok Road Mile Marker 64 on the Seward Peninsula. Selected plots were surveyed from 18-23 July 2016. Environmental data (e.g., elevation, slope, soil moisture regime, disturbance type and degree, mean canopy height, etc.) were also recorded for each plot. Elevation measurements were updated 2020-08-18. All plant species (vascular plants, bryophytes and lichens) were recorded along with their percent cover in the plots as determined visually by the lead author. Plots were chosen subjectively in areas of homogeneous and representative vegetation and varied in size from 1-25 m2 depending on canopy structure and height. The site is an east-facing hillslope with vegetation that varies from the summit to the toeslope. The 30 total plots were selected as five replicate plots sampled from each of the six identified habitat types: 1) non-acidic mountain complex at the hillcrest, 2) dwarf-shrub lichen tundra on the shoulder, 3) alder shrublands predominantly on an elevational band across the backslope, 4) willow-birch tundra on the upper backslope, 5) tussock tundra on the footslope in inter-water tracks, and 6) tussock tundra mixed with willow-birch tundra or alder savanna in poor developed water tracks on the footslope. This dataset is comprised of two comma-separated (*.csv) files containing species and environmental data for the plant community composition plots. It also contains seven zipped folders of plot photographs, one map showing plot locations (*.pdf), one blank datasheet with the key to codes used in the field (*.pdf), select photos organized in a (*.pdf), and one User file (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

LeWRON: Agentic Analysis of Electroweak Phase Transitions

The electroweak phase transition (EWPT) is a central topic in particle physics and cosmology, connecting collider phenomenology, baryogenesis, and gravitational-wave observatories. Its analysis requires a technically demanding, convention-sensitive, and model-dependent pipeline, from constructing the finite-temperature effective potential to tracking thermal histories, computing bubble nucleation rates, and predicting gravitational-wave spectra. We present LeWRON (Learning ElectroWeak phase tRansitiON), an agentic framework that orchestrates this pipeline starting from an input Lagrangian. LeWRON combines audited toolbox construction with an Explorer module that uses the generated model-specific code for further analysis, including scans and plots. Intermediate analytic outputs are checked by auditor agents and stored as structured artifacts, enabling reproducible human inspection and downstream use through both a command-line interface and a public Python API. The framework supports a reproduction mode, which infers conventions from the literature and reproduces published results, and a discovery mode, which guides users through structured checkpoints for new models. We demonstrate LeWRON across representative beyond-the-Standard-Model scenarios and release the code on GitHub.

Wang, Isaac R. [Fermilab] (ORCID:000000030789218X)↗
DOE OSTI2021

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2020

The Rodinia Benchmark Suite in SYCL

As opposed to the Open Computing Language (OpenCL) programming model in which host and device codes are generally written in different programming languages, SYCL can combine host and device codes for an application in a type-safe way to improve development productivity and performance portability. Rodinia is a widely used benchmark suite for heterogeneous computing. Hence, we port the OpenCL implementations of the benchmark suite to SYCL manually. The SYCL benchmark suite is an opensource project for tracking the development of the mainstream SYCL compilers, and for developers and researchers interested in programming productivity, performance analysis, and portability across different computing platforms. We organize the remainder of the report as follows. Section II introduces the SYCL programming model, shows the major differences between an OpenCL program and a SYCL program, and gives a summary of the benchmark suite. In Section III, we describe our SYCL implementations in more details. We evaluate the SYCL benchmarks on the Intel® central processing units (CPUs) and graphics processing units (GPUs) in Section IV. Section V concludes the report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Accelerator Neutrino Neutron InteractionExperiment: Design, Construction and Preparationfor First Physics

This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80- channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, opensource pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80-channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗