Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “toolkit”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DRiFT - Release 1.1.1: Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator, gas, and semiconductor features, the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

DRiFT - Release 2.1.0: Organic Scintillators and Gas Detectors

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that post-processes output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. The focus of this release is on organic scintillator, gas detector, and associated capabilities, while semiconductor features are still under development. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. DRiFT also has several diagnostic and detector physics features relevant to neutron gas detector simulations including: gas detector wall effects, inactive areas at the end of detector tubes, and effects of a preamplifier. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗
DOE OSTI2023

Athena-I CUBIT Journal Files

The Monte Carlo N-Particle (MCNP)1 transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into con structive solid geometry (CSG) cells. This feature has been developed for performing calculations of complex geometry models because manually creating CSG models is a time-consuming and error prone process as the complexities of geometries increase. The UM capability was originally designed to work with UM models created with the Abaqus software and ASCII input files that it generates. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. Starting with version 6.3, MCNP can also process HDF5 mesh input files. External codes must be used to generate Abaqus input files for MCNP UM calculations. CUBIT, the Sandia National Laboratory automated mesh generation toolkit, can generate a UM model formatted as an Abaqus input file. However, the Abaqus input files exported from CUBIT cannot be used for MCNP simulations because it lacks the proper syntax. A Python script was developed to convert an Abaqus file created by CUBIT to an Abaqus file format that MCNP can process. Creating UM models for complex geometries is not an easy task. The process of creating UM models in CUBIT for MCNP simulations is detailed in. CUBIT provides several user interface options including a graphical user interface (GUI) and a command line interface. A GUI provides an easy way to use CUBIT without learning the CUBIT command syntax. When using CUBIT with either interface option, command lines are written into an ASCII file known as a journal file; this journal file can be edited and archived so that it can be played back in CUBIT to automatically generate a UM model. This report describes the CUBIT journal files of the UM models developed for Athena-I. The Athena platform, an energy-tuning assembly, was developed to spectrally shape the National Ignition Facility (NIF) deuterium-tritium fusion neutron source to a thermonuclear (fusion) plus prompt fission neutron spectrum with capability to act as a short-pulse neutron source. MCNP6 was used for the Athena experiment design analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Open Source Evaluation Framework for Solar Forecasting

The Solar Forecast Arbiter is an open-source evaluation framework for solar forecasting. The framework enables evaluations of solar irradiance, solar power, and net-load forecasts that are impartial, repeatable and auditable. The Solar Forecast Arbiter addresses stakeholder-informed use cases including evaluation of forecast skill, comparisons to reference data sets, private forecast trials, and evaluation of probabilistic forecast skill. The framework includes a data validation toolkit, reference data sources, data privacy protocols, and benchmark forecast capabilities for intra-hour and day ahead forecast horizons. Reports and metrics communicate the relative merits of the test and benchmark forecasts. The reports are created from standardized templates and include graphics for qualitatively evaluating deterministic and probabilistic forecasts and standard metrics for quantitatively evaluating forecasts. The Solar Forecast Arbiter is designed to support all solar forecasting stakeholders, including Solar Forecasting 2 Topic Area 2 and Topic Area 3 teams.

14 SOLAR ENERGY↗
DOE OSTI2023

Demonstrating Safeguards Applications of DRiFT Gas Detector Capabilities [Slides]

DRiFT, a Detector Response Function Toolkit, post-processes MCNP output to model detector response. Three primary components: scintillator (focus of FY 21 TED work), gas detectors (focus of this FY), and semiconductor detectors. Capability to model scintillator detectors has previously been demonstrated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Viruses in soils: Key modulators of microbiomes and nutrient cycling? (Final report)

Microbes play essential roles in keeping soils healthy, but it remains a mystery if the viruses that infect them are also impacting soil health. In soils, microbes drive local energy and vital biogeochemical cycles (e.g., nitrogen transformations), which become bioavailable nutrients for plants and other microscopic animals. Viruses of bacteria (called ‘phages’) are abundant in soils (a billion per gram!), and are a normal component of the soil microbiome. However, we have no clear models on what viruses do (e.g., are they actively infecting or dormant?) or what impacts they have at a system level (e.g., is carbon assimilation rates affected by virus infection?). Problematically, we do not yet have the tools to study viruses in soils – even being able to detect them is a challenge. Therefore, the core of the VirSoil project was to develop a toolkit to study soil viruses, and use it to derive a baseline ecological understanding of virus diversity and impacts in climate-critical soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Expanded verification and validation studies of hypersonic aerodynamics with multiple physics-fidelity models

Hypersonic aerothermodynamics is an important domain of modern multiphysics simulation. The Multi-Fidelity Toolkit is a simulation tool being developed at Sandia National Laboratories to predict aerodynamic properties for compressible flows from a range of physics fidelities and computational speeds. These models include the Reynolds-averaged Navier–Stokes (RANS) equations, the Euler equations with momentum-energy integral technique (MEIT), and modified Newtonian aerodynamics with flat-plate boundary layer (MNA+FPBL) equations, and they can be invoked independently or coupled with hierarchical Kriging to interpolate between high-fidelity simulations using lower-fidelity data. However, as with any new simulation capability, verification and validation are necessary to gather credibility evidence. This work describes formal code- and solution-verification activities, as well as model validation with uncertainty considerations. Code verification activities on the MNA+FPBL model build on previous work by focusing on the viscous portion of the model. Viscous quantities of interest are compared against those from an analytical solution for flat-plate, inclined-plate, and cone geometries. The code verification methodology for the MEIT model is also presented. Test setup and results of code verification tests on the laminar and turbulent models within MEIT are shown. Solution-verification activities include grid-refinement studies on simulations that model the HIFiRE-1 wind tunnel experiments. These experiments are used for validation of all model fidelities. A thorough validation comparison with prediction error and uncertainty is also presented. Three additional HIFiRE-1 experimental runs are simulated in this study, and the solution verification and validation work examines the effects of the associated parameter changes on model performance. Finally, a study is presented that compares the computational costs and fidelities from each of the different models.

42 ENGINEERING↗
DOE OSTI2023

Spatially Adaptive Tunable Lighting Control System with Expanded Wellness and Energy Saving Benefits

Lighting design is becoming increasingly complex, including active dimming for energy savings and spectral tuning for human wellbeing. Modern commercial lighting control systems are already difficult to use, and maintain, and even with so-called Smart Lighting, optimizing light settings is rapidly exceeding the capabilities of direct human control, limiting the adoption of lighting control systems. The growing importance of Occupancy Centric Controls (OCC) for advanced building management systems can be applied to the development of autonomous lighting system controls needed to drive the adoption of advanced lighting controls for improved adaptive “sculpted illumination” for both greater energy savings and broader human wellbeing perspectives. This project, led by Rensselaer Polytechnic Institute, entitled “Spatially adaptive tunable lighting control system with expanded wellness and energy saving benefits” will develop and test an entirely new platform for automated optimized lighting design and control that requires little or no human engagement, yet contours lighting profiles automatically to minimize lighting energy use. We call this approach to lighting control “dynamic light sculpting” since the right amount of illumination is automatically delivered to occupants in real time. Since the system uses new, privacy-preserving occupant position and pose detection technologies developed by Rensselaer for broad OCC building applications, the control system will analyze how to deliver the right amount of the right type of illumination only where and when it is needed based these OCC platforms. To create these powerful autonomous lighting control platforms, the project will integrate evolving augmented reality (AR) and virtual reality (VR) tools with sophisticated lighting and interior design toolkits to create interactive lighting design and control simulators. Using the quickly growing paradigm of digital twins, these tools will integrate light fixture properties, occupancy sensor data, interior design data, and lighting specifications to accurately visualize how various design concepts interact with simulated yet realistic human activities that occur in commercial office buildings of various types. These advanced digital twin design and simulation tools will be combined with a new class of digitally-programmable LED lighting fixtures that can dynamically change the spectral content and direction of light emission. When fully integrated, the new autonomous lighting control system will take all of the guesswork out of optimizing light quality while minimizing energy consumption. Digital twin tools will simplify the design, installation, commissioning, operation, and maintenance of future energy-efficient lighting systems. It should be possible to reduce lighting energy costs from 40% to 70% with OCC based dynamic light sculpting systems. The work will be led by the Center for Lighting Enabled Systems and Applications (LESA) and the Center for Architectural Science and Ecology (CASE), both at Renssealer Polytechnic Institute; Lumileds, a global leader in the development of advanced LED systems; and HKS, a leading global architecture design firm. This interdisciplinary project team’s experience includes all of the design simulation tools, VR/AR digital twin visualization technology, advanced occupancy sensing technology, and complex control system design capabilities that will revolutionize lighting design and control technology to autonomously deliver high-quality lighting that improves human health and wellbeing while simultaneously maximizing lighting energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A comprehensive strategy for stable, high productivity cultivation of microalgae with controllable biomass composition

This project was performed primarily as a partnership between three Universities – The University of Toledo (UToledo), Montana State University (MSU) and The University of North Carolina at Chapel Hill (UNC). North Carolina State University also contributed to the project through a sub-subcontract. The project developed fundamental and applied knowhow for cultivation systems that are not restricted by (i) proximate availability of flue gas or other high concentration CO 2 sources and (ii) the energy and infrastructure burden to deliver CO 2 over long distances. To overcome these constraints, this project focused on cultivation of alkaliphilic algal cultures in high pH, high alkalinity media (pH>10, alkalinity >100mEq) and demonstrated high biomass productivity, improvement of biomass composition for fuel production, and culture stability. The high media alkalinity ensured availability of sufficient HCO 3 - in solution for high rates of carbon fixation while the high pH of the media facilitated rapid scavenging of atmospheric CO 2 . Overall, the direct air capture rates (DAC) in our system were sufficient to achieve high biomass productivities using atmospheric CO 2 alone. The project also developed and validated toolkits related to metabolic flux modeling and microbiome characterization.

09 BIOMASS FUELS↗
DOE OSTI2023

Technical Justifications for Liquid Hydrogen Exposure Distances

The previous separation distances in the National Fire Protection Association (NFPA) Hydrogen Technologies Code (NFPA 2, 2020 Edition) for bulk liquid hydrogen systems lack a well-documented basis and can be onerous. This report describes the technical justifications for revisions of the bulk liquid hydrogen storage setback distances in NFPA 2, 2023 Edition. Distances are calculated based on a leak area that is 5% of the nominal pipe flow area. Models from the open source HyRAM+ toolkit are used to justify the leak size as well as calculate consequence-based separation distances from that leak size. Validation and verification of the numerical models is provided, as well as justification for the harm criteria used for the determination of the setback distances for each exposure type. This report also reviews mitigations that could result in setback distance reduction. The resulting updates to the liquid hydrogen separation distances are well-documented, retrievable, repeatable, revisable, independently verified, and use experimental results to verify the models.

08 HYDROGEN↗
DOE OSTI2024

GEANT4 Simulations on Faraday Cup Design for PIP-II Laser Wire Scanner System

The PIP-II accelerator upgrade at Fermilab represents a groundbreaking leap forward in high-energy physics research. This ambitious initiative involves enhancing Fermilab's accelerator complex by replacing the current linear accelerator with a warm front end (WFE) capable of accelerating H- beams up to 2.1 MeV. Subsequently, a superconducting linac further accelerates these beams up to 800 MeV. To precisely measure the transverse beam profile, a combination of traditional wire scanners at the WFE section and Laser wire scanners along the superconducting linac are planned for implementation. This investigation centers on refining the Faraday cup design for the PIP-II Laser wire scanners by utilizing GEANT4, a Monte Carlo simulation toolkit. Leveraging this method enables a comprehensive analysis of particle trajectories, energy deposition, secondary electron emission, backscattering, etc., facilitating optimization through adjustments to cup geometries, materials, and placement to maximize its efficiency.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

DRiFT Current Mode, Trigger Settings and Flexible Detector Specifications Applied to Scintillator Arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

SPECs Early-Stage Decision Model: User Manual

The SPECs Early-Stage Decision (ESD) model is central to the SPECs procurement solutions toolkit. The ESD model is an Excel-based spreadsheet model, which provides information about the economic and strategic value of a proposed battery-storage project or solar-plus-storage (solar-plus) project. The model can be used to explore combinations of storage-related project value streams in order to define a potential project, while educating co-op decision-makers about project benefits and costs. A sensitivity analysis function speeds the development of "what-if" scenarios. A gap analysis function solves for top-priority metrics and supports the inclusion of hard-to-monetize strategic values, such as the value of storage to defer costly system upgrades in light of increasing distributed solar and other distributed energy resources (DERs). Model outputs include the utility data, assumptions, and use-case scenarios that are recommended content for the requests for proposals (RFPs). The model may also provide an initial "sanity check" for RFP responses, supporting further discussions among utility staff, vendors and stakeholders. The ESD is not a "finance-grade" modeling tool, and users are cautioned to be mindful of its limitations, but the model has been reviewed by users, who recommend it as a way to drive faster and better project design and planning, as well as to facilitate better communications with vendors, grid partners, and stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2024

Powered by dsgrid [Slides]

NREL's demand-side grid (dsgrid) toolkit harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The primary purpose of dsgrid is to create comprehensive electricity load data sets at high temporal, geographic, sectoral, and end-use resolution. These data sets enable detailed analyses of current patterns and future projections of end-use loads. This presentation will include NREL power grid researcher Elaine Hale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Development of a Fast-Spectrum Self-Powered Neutron Detector for Molten Salt Experiments in the Versatile Test Reactor

Abstract—The self-powered neutron detector (SPND) is a widely used flux monitor in thermal nuclear reactors. Although this is a mature technology, the current state of the art is tuned for a thermal neutron spectrum, so many of the devices currently in use lack sensitivity to fast neutrons. Because current in SPNDs is produced through nuclear reactions with the neutron flux inside a reactor, sensitivity in SPNDs is determined by the neutron cross section of the neutron-sensitive portion of the detector, termed the emitter. This neutron cross section drops by orders of magnitude between thermal and fast neutron energies for many emitters in currently used SPNDs, with a corresponding drop in current from the detector. This paper discusses efforts to develop a fast-spectrum self-powered neutron detector (FS-SPND) that is sensitive to neutrons with energies ranging from 0.025 eV up to 1 MeV. An in-depth analysis of Evaluated Nuclear Data File (ENDF)/B-VII.1 neutron-capture cross sections was performed, and four new materials were identified that are suitable emitter candidates for use in measuring fast neutrons. All four materials are stable mid-shell nuclei in the region between doubly magic 132Sn and 208Pb. Each candidate was simulated with the Geant4 Monte Carlo simulation toolkit to optimize overall detector efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Python UQ Workflows Progress [Poster]

Project Overview and Goal: Create a Python Toolkit for UQ (PyTUQ) to facilitate the interoperability of FASTMath UQ tools (Dakota, UQTk, KLPC), as well as other ASCR funded capabilities for UQ workflows.

97 MATHEMATICS AND COMPUTING↗