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At least 577 records · Page 32

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling

PyApprox is a Python-based one-stop-shop for probabilistic analysis of numerical models such as those used in the earth, environmental and engineering sciences. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent a wide range of methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of new or existing algorithms for a wide range of model analyses. Here, this paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in groundwater.

54 ENVIRONMENTAL SCIENCES↗

X-Ray Toolkit Mobile (Android)

X-Ray Toolkit Mobile (Android) is a software application for acquiring and processing digital images. The application runs on mobile devices running Android operating systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-1981 O

Harris, JamesZ.↗

Remote Target Engagement System (RTES) Generation 4 ("Gen 4")

RTES is designed to provide teleoperation of remote weapon platform capability at defensive physical protection locations requiring active lethal capabilities for final access denial. Multiple operator consoles allow for coordinated engagement of many weapon platforms by one or more operator consoles. This results in faster response times, increased effectiveness, and increased survivability from removing response force from harm's way increasing survivability. This software is developed against DoD requirements and has been safety and functionally reviewed and approved for operational use. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1935 O

Klingler, KristopherR.↗

Mnemosyne

SAND2024-08570O Mnemosyne is an interactive tool for finding, retrieving, and exploring information about U.S. nuclear tests documented in the National Nuclear Security Administration’s NV-209 report. It also acts as an information architecture and codebase for integrating additional information and computational tools related to these tests at the unclassified and classified levels. Users can search by any number of nuclear test attributes—name, yield range, altitude ranges, purpose of a test—and find all matching tests. Users can also retrieve specific test information published in NV-209. The tool displays geospatial and topological data about test location, and it provides an information architecture for storing additional contextual material, such as photographs. Mnemosyne provides a capability of interfacing with HYCHEM, Sandia's nuclear detonation optical waveform tool. The software is designed for use by government, academia, military, and research institutions. The software will likely be advanced to integrate seismic data and the nuclear detonation optical signal simulation code radCTH. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fisher, Dustin↗

Datashare

Datashare facilitates communication and data sharing within local networks in potentially dangerous situations such as an explosive ordnance disposal. During such events, there is a need to transmit information rapidly around the incident area. It is a distributed database that does not require an internet connection for operation. In addition, Datashare interfaces with XTK and other software applications, allowing for seamless integration and data management. Datashare supports video calls over the network, enabling real-time communication among users. This software serves to organize, package, and share between responders on location and export data to those off location. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Eldridge, Bryce [Sandia National Lab. (SNL-CA), Li↗

Simulation-Based Design and Optimization of Waste Heat Recovery Systems

This fact sheet features an R&D project that will develop a modeling platform that can quantify the value of a district energy system and its potential for waste heat recovery. The new software analysis platform will evaluate and optimize district energy systems to better utilize low-temperature waste heat from nearby commercial and industrial buildings. The platform will help project developers and engineers easily quantify the potential value and cost savings of community energy systems for both producers and consumers of waste heat.

Combined heat and power, CHP, District energy, Was↗

HeatMap

SAND2021-14230 O HeatMap generates geospatial wildfire fuel models by applying machine learning algorithms to satellite imagery and weather station data. The code then leverages wildfire behavior software FlamMap to determine fire spread. It also uses PSLF software to model grid impacts and display data analytics for grid components that have been impacted by wildfire. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Danford, Forest↗

Tiered Energy Use in Buildings (TEB)

This tool creates a set of building energy simulations and organizes them according to a tier-based model representing circuits that will be on or off depending on a microgrid controller (not included in this software). This Python based code uses the open-source RCBuildingSimulator that is under an amended MIT license. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2528 O

Villa, Daniel↗

POEM

User manual for software POEM (Platform of Optimal Experiment Management).

42 ENGINEERING↗

Three-Dimensional CFD Analysis of Construction Design Alternatives for an ERDC Coastal and Hydraulics Laboratory Flow Accelerator

The U.S. Army Engineer Research and Development Center, ERDC, Coastal and Hydraulics Laboratory in Vicksburg Mississippi is planning to build a large flume with a 10-foot-wide flow channel. Three-dimensional Computational Fluid Dynamics (CFD) analysis was used in the design of the flume entry and flow accelerator sections that feed into the 10-foot-wide channel. The design is based on the plans of the existing fiberglass flume inlet at the Turner-Fairbank Highway Research Center (TFHRC) J. Sterling Jones Hydraulics Research Laboratory in McLean Virginia. The TFHRC flume inlet feeds water to a 6-foot-wide flume channel, and therefore a scale up factor of 10/6 in the width of the inlet section of the TFHRC flume would meet the width requirement of the ERDC flume channel. The CFD analysis was performed using STAR-CCM+ commercial CFD software. Additional analysis was done with the open-source CFD software, OpenFOAM, to cross-check the analysis of one of the cases with a code-to-code comparison.

42 ENGINEERING↗

Designing a Magnetic Measurement Data Acquisition and Control System With Reuse in Mind: A Rotating Coil System Example

Accelerator magnet test facilities frequently need to measure different magnets on differently equipped test stands and with different instrumentation. Designing a modular and highly reusable system that combines flexibility built-in at the architectural level as well as on the component level addresses this need. Specification of the backbone of the system, with the interfaces and dataflow for software components and core hardware modules, serves as a basis for building such a system. The design process and implementation of an extensible magnetic measurement data acquisition and control system are described, including techniques for maximizing the reuse of software. The discussion is supported by showing the application of this methodology to constructing two dissimilar systems for rotating coil measurements, both based on the same architecture and sharing core hardware modules and many software components. The first system is for production testing 10 m long cryo-assemblies containing two MQXFA quadrupole magnets for the high-luminosity upgrade of the Large Hadron Collider and the second for testing IQC conventional quadrupole magnets in support of the accelerator system at Fermilab.

43 PARTICLE ACCELERATORS↗

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗

Simulating gas-filled neutron detector responses with DRiFT

– Gas-filled neutron detectors have numerous applications across the nuclear engineering and nuclear physics fields. The ability to accurately model and simulate these detectors is important for those applications but is currently limited by the lack of readily-useable detector response software. Recently, the capabilities of DRiFT, a Detector Response Function Toolkit, were expanded to model gas-filled, He-3 and BF3, neutron detectors so that, combined with the radiation transport capabilities of the MCNP code, a high-fidelity treatment of gas-filled neutron detectors can be obtained. Further, this model has been validated by an experiment carried out with the Epithermal Neutron Multiplicity Counter and its capabilities have been demonstrated in two additional experiments. This work shows that utilizing DRiFT to post-process MCNP outputs produces more accurate results than using the MCNP code alone, reducing the difference between experimental and simulated results for measurements taken near the end of a He-3 tube, where the MCNP code struggles to model inactive regions of the detector, from a maximum of 35% with the MCNP code alone to 15% with the MCNP code plus DRiFT. DRiFT's diagnostic capabilities are also demonstrated with measurements for scenarios when pulse pileup or room return effects are significant and must be considered. Altogether, these measurements underpin the ability of DRiFT to accurately model and predict the behavior of gas-filled neutron detectors, making it a valuable tool for the design and testing of systems and experiments that utilize these detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SignalGen

PNNL contribution to project managed by federal agency. SignalGen is a software application that generates synthetic RDF graphs that satisfy the constraints specified in a search template. The purpose of this tool is most to aid in the development of the graph search engine and ensure it is able to find known graph patterns.

Avila, Andrew↗