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At least 361 records · Page 20

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

NIRP Core Software Suite v. 1.0

The NIRP Core Software Suite is a core set of code that supports multiple applications. It includes miscellaneous base code for data objects, mathematic equations, and user interface components; and the framework includes several fully-developed software applications that exist as stand-alone tools to compliment other applications. The stand-alone tools are described below. Analyst Manager: An application to manage contact information for people (analysts) that use the software products. This information is often included in generated reports and may be used to identify the owners of calculations. Radionuclide Viewer: An application for viewing the DCFPAK radiological data. Compliments the Mixture Manager tool. Mixture Manager: An application to create and manage radionuclides mixtures that are commonly used in other applications. High Explosive Manager: An application to manage explosives and their properties. Chart Viewer: An application to view charts of data (e.g. meteorology charts). Other applications may use this framework to create charts specific to their data needs.

Whitener, Dustin Heath↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

BuildingSync® [SWR-18-28]

BuildingSync® is a standardized language for commercial building energy audit data that software developers can use to exchange data between audit tools. Taking the form of an XML schema, BuildingSync can be required by building owners and audit program managers to allow data analysis and aggregation across multiple buildings in order to evaluate program performance and analyze trends. BuildingSync was developed using the standard energy data terminology defined in the Building Energy Data Exchange Specification (BEDES). BuildingSync is one of the first implementations of BEDES Version 1.0, and it was developed in close collaboration with the BEDES working groups. BuildingSync standardizes the format of the energy audit data itself. It is not intended to standardize the calculations performed on these data by engineers, analysts, software packages, or other audit tools. For more, see: https://buildingsync.net/

Long, Nicholas↗

Enhancing Monte Carlo Workflows for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo codes are essential components of many reactor physics simulation workflows as high-fidelity continuous-energy neutron transport solvers. Among Monte Carlo radiation transport codes, MCNP is particularly notable due to its diverse simulation capabilities, large user base, and long validation history. Despite being a powerful simulation tool, MCNP provides limited capabilities to allow automated execution, model transformation, or support for user-defined logic and abstractions that limit its compatibility with modern workflows. Here, to better integrate MCNP into a modern scientific workflow, we have developed an intuitive yet full-featured MCNP Application Program Interface (API) in Python, named MCNPy, which provides a specialized set of classes for MCNP input development. Moreover, to guarantee that our reading, writing, and modeling capabilities remain self-consistent (and to render the huge scope of the MCNP API manageable), we have adopted a strategy of model-driven software development in which a generalized model of the MCNP input format has been created. From this generalized model, or “metamodel,” problem-specific implementations such as an engine for input validation or a codebase for programmatic operations may be automatically generated. Since MCNPy primarily acts as a Python front-end to the underlying Java API that directly interfaces with the metamodel, it is intrinsically linked to the metamodel and thus remains maintainable. With MCNPy, users can programmatically read, write, and modify any syntactically valid MCNP input file regardless of its origin. These capabilities allow users to automate complicated tasks like design optimization and model translation for nuclear systems. As examples, this work demonstrates the use of MCNPy to find the critical radius of a plutonium sphere and to translate a 9000+ line MCNP input file into a corresponding OpenMC model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modernization efforts for the R -Matrix code SAMMY [Abstract]

The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

ROBOT: A Tool for Automating Ontology Workflows

BACKGROUND:Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms. For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool. RESULTS:ROBOT (a recursive acronym for "ROBOT is an OBO Tool") is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems. CONCLUSIONS:ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A Prototype {sup 212}Pb Medical Dose Calibrator for Alpha Radioimmunotherapy

AREVA Med, an AREVA group subsidiary, is developing innovative cancer-fighting therapies involving the use of {sup 212}Pb for alpha radioimmunotherapy. Canberra Industries, the nuclear measurement subsidiary of AREVA, has been working with AREVA Med to develop a prototype measurement system to assay syringes containing a {sup 212}Pb solution following production by an elution system. The relative fraction of emitted radiation from the source associated directly with the {sup 212}Pb remains dynamic for approximately 6 hours after the parent is chemically purified. A significant challenge for this measurement application is that the short half-life of the parent nuclide requires assay prior to reaching equilibrium with progeny nuclides. A gross counting detector was developed to minimize system costs and meet the large dynamic range of source activities. Prior to equilibrium, a gross counting system must include the period since the {sup 212}Pb was pure to calculate the count rate attributable to the parent rather than the progeny. The dynamic state is determined by solving the set of differential equations, or Bateman equations, describing the source decay behavior while also applying the component measurement efficiencies for each nuclide. The efficiencies were initially estimated using mathematical modeling (MCNP) but were then benchmarked with source measurements. The goal accuracy of the system was required to be within 5%. Independent measurements of the source using a high resolution spectroscopic detector have shown good agreement with the prototype system results. The prototype design was driven by cost, compactness and simplicity. The detector development costs were minimized by using existing electronics and firmware with a Geiger-Mueller tube derived from Canberra's EcoGamma environmental monitoring product. The acquisition electronics, communications and interface were controlled using Python with the EcoGamma software development kit on a Raspberry Pi Linux computer mounted inside a standard project box. The results of initial calibration measurements are presented. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a Web-Based Graphical User Interface for Fermilab Robots

This project provides the students/faculty team with the unique opportunity to work with several robots. Additionally, the student team will be able to learn from the experience of the Robotics Initiative members who have a wide variety of technical backgrounds outside of software development. Working with an interdisciplinary group to solve a complex problem that is unique to our facility, is a valuable experience that the lab can provide. This project aligns with the ACORN projects R&D efforts regarding the integration of robotics status/control with the accelerator control system.

43 PARTICLE ACCELERATORS↗

ARM Data Integrator

The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Source record↗

ARM Data Integrator

The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Source record↗

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics

This project was part of a coordinated software development effort which the nuclear physics lattice QCD community pursues in order to ensure that lattice calculations can make optimal use of present, and forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The UW team improved and extended software libraries used in lattice QCD calculations related to multi-nucleon systems, enhanced production running codes related to load balancing multi-nucleon production on large-scale computing platforms, and developed SQLite (addressable database) interfaces to efficiently archive and analyze multi-nucleon data and developed a Mathematica interface for the SQLite databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mesoscale Numerical Characterization of Kevlar and Carbon–Kevlar Hybrid Plain-Woven Fabric Compression Behavior

A mesoscale finite element model (FEM) of the plain-woven fabric representative elementary volume (REV/unit cell) is developed. The developed FEM is used to predict the nonlinear compaction behavior of monolithic and intraply hybrid fabric made of high-strength carbon and Kevlar fibers. For geometrical modeling of the fabric REV, TexGen, an open-source geometrical modeling software (developed at Nottingham University), is utilized, and for mechanical characterization, FE simulation tool Abaqus{sup ®} is used. Geometrical nonlinearity of the fabric, including periodic boundary conditions and yarn interactions, is incorporated in the REV FE model. Material nonlinearity caused by transversely isotropic behavior of fibrous yarns is implemented through the user material subroutine form in FE simulation along with local orientation assigned to each yarn in the REV. Material properties of fibers are extracted from the literature and supplier data. The compression behavior of monolithic Kevlar and hybrid carbon–Kevlar (carbon warp and Kevlar weft yarns, C–K) fabric is predicted using the proposed FE model. FEM-predicted results were found to have good agreement with the experimentally obtained ones. Results depict that C–K hybrid fabrics have improved compression strength. Hybridization effect is governed by yarns mutual interaction, yarn area at crossovers, and transverse in-plane properties of the interyarn hybridized fabric. The proposed FE model can be used to predict the mechanical behavior of woven fabrics with different weaving patterns, unit cell geometry, material properties, and loading conditions.

36 MATERIALS SCIENCE↗

The study on knowledge transferring incentive for information system requirement development

Information system requirement development is a process of users’ knowledge sharing and transferring. However the tacit requirements developing is a main problem during requirement development process, for the reason of difficult to encoding, express, and communicate. Knowledge fusion and corporate effort is needed to finding tacit requirements. Under this background, our paper try to find out the rule of effort dynamic evolutionary of software developer and user by building an evolutionary game model on the condition of incentive system. And in addition this paper provides an in depth discussion at the end of this paper.

97 MATHEMATICS AND COMPUTING↗

Development of a Whole Container Seal

This paper outlines a technique for utilizing electrically conductive textiles as a whole container seal. This method has the potential to provide more robustness for ensuring that the container has not been breached versus conventional sealing methods that only provide tamper indication at the area used for normal access. The conductive textile is used as a distributed sensor for detecting and localizing container tamper or breach. For sealing purposes, the conductive fabric represents a bounded, near-infinite grid of resistors. The well-known infinite resistance grid problem was used to model and confirm the expected accuracy and validity of this approach. An experimental setup was built that uses a multiplexed Wheatstone bridge measurement to determine the resistances of a coarse electrode grid across the conductive fabric. Non-uniform resistance values of the grid infer the presence of damage or tears in the fabric. Results suggest accuracy proportional to the electrode spacing in determining the presence and location of disturbances in conductive fabric samples. Current work is focused on constructing experimental prototypes for field and environmental testing to gauge the performance of these whole container seals in real world conditions. We are also developing software and hardware to interface with the whole container seals. The latest prototypes are expected to provide more accuracy in detecting and localizing events, although detection of a penetration should be adequate for most sealing applications. We are also developing smart sensing nodes that integrate digital hardware and additional sensors (e.g., motion, humidity) into the electrode nodes within the whole container seal.

Kuhn, Michael J↗

A Scientific Data Processing Framework for Time Series NetCDF Data

ARM Data Integrator (ADI) is a framework to streamline the development of scientific algorithms that analyze time-series NetCDF data, and to improve the content and consistency of the output data products produced by these algorithms. ADI achieves these goals by automating the process of retrieving and preparing data for analysis, supporting the definition of output data products through a graphical interface, and providing a modular, flexible software development architecture. The input data, preprocessing, and output data specifications are defined through a graphical interface and stored in a database. ADI also includes a workflow for data integration, a library of software modules to support the workflow, and a source code generator that produces C, IDL and Python templates. Data preparation support includes automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog. The variable and attribute definitions of the existing data products can be used to build new output data products. In addition, the rules that make up the ARM archive’s data standards are laid on top of the view of the new data product providing the user with a visual cue indicating where their output violates an archive standard. The necessary configurations are stored in a database that is accessed by the ADI libraries. This paper discusses the ADI framework, its supporting components, and how ADI can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Atmospheric Science↗

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

59 BASIC BIOLOGICAL SCIENCES↗

Sandia GNU Radio Utilities

The Sandia Utilities form an RF toolkit extending the GNU Radio framework for straightforward interaction with bursty RF systems which can be cumbersome using built in capabilities of the framework or other open source extensions. Motivated by the abstract exercise of responding to a modulated burst of information with a unique modulated burst of information, the Sandia Utilities provide several dozen additional debug and signal processing blocks through four software modules. These blocks manifest their utility through a new general concept of operation for GNU Radio applications and extend many existing streaming capabilities to the PDU-based message passing API. Using these concepts and tools, it is straightforward to develop software capabilities to interact with existing and new bursty RF devices.

47 OTHER INSTRUMENTATION↗