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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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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-T-596: P3DVHStats - a Novel, Automatic, Institution Customizable Program to Compute and Report DVH Quantities On Philips Pinnacle TPS

Purpose: To implement a novel, automatic, institutional customizable DVH quantities evaluation and PDF report tool on Philips Pinnacle treatment planning system (TPS) Methods: An add-on program (P3DVHStats) is developed by us to enable automatic DVH quantities evaluation (including both volume and dose based quantities, such as V98, V100, D2), and automatic PDF format report generation, for EMR convenience. The implementation is based on a combination of Philips Pinnacle scripting tool and Java language pre-installed on each Pinnacle Sun Solaris workstation. A single Pinnacle script provide user a convenient access to the program when needed. The activated script will first export DVH data for user selected ROIs from current Pinnacle plan trial; a Java program then provides a simple GUI interface, utilizes the data to compute any user requested DVH quantities, compare with preset institutional DVH planning goals; if accepted by users, the program will also generate a PDF report of the results and export it from Pinnacle to EMR import folder via FTP. Results: The program was tested thoroughly and has been released for clinical use at our institution (Pinnacle Enterprise server with both thin clients and P3PC access), for all dosimetry and physics staff, with excellent feedback. It used to take a few minutes to use MS-Excel worksheet to calculate these DVH quantities for IMRT/VMAT plans, and manually save them as PDF report; with the new program, it literally takes a few mouse clicks in less than 30 seconds to complete the same tasks. Conclusion: A Pinnacle scripting and Java language based program is successfully implemented, customized to our institutional needs. It is shown to dramatically reduce time and effort needed for DVH quantities computing and EMR reporting.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS)

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. Overall, this protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Time-gated single-photon detection module with 110 ps transition time and up to 80 MHz repetition rate

We present the design and characterization of a complete single-photon counting module capable of time-gating a silicon single-photon avalanche diode with ON and OFF transition times down to 110 ps, at repetition rates up to 80 MHz. Thanks to this sharp temporal filtering of incoming photons, it is possible to reject undesired strong light pulses preceding (or following) the signal of interest, allowing to increase the dynamic range of optical acquisitions up to 7 decades. A complete experimental characterization of the module highlights its very flat temporal response, with a time resolution of the order of 30 ps. The instrument is fully user-configurable via a PC interface and can be easily integrated in any optical setup, thanks to its small and compact form factor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗
DOE OSTI2024

Visual Analytics of Multivariate Networks With Representation Learning and Composite Variable Construction

Multivariate networks are commonly found in real-world data-driven applications. Uncovering and understanding the relations of interest in multivariate networks is not a trivial task. This article presents a visual analytics workflow for studying multivariate networks to extract associations between different structural and semantic characteristics of the networks (e.g., what are the combinations of attributes largely relating to the density of a social network?). The workflow consists of a neural-network-based learning phase to classify the data based on the chosen input and output attributes, a dimensionality reduction and optimization phase to produce a simplified set of results for examination, and finally an interpreting phase conducted by the user through an interactive visualization interface. A key part of our design is a composite variable construction step that remodels nonlinear features obtained by neural networks into linear features that are intuitive to interpret. We demonstrate the capabilities of this workflow with multiple case studies on networks derived from social media usage and also evaluate the workflow with qualitative feedback from experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

libMSR library and msr-safe kernel module

Modern processors offer a wide range of control and measurement features. While those are traditionally accessed through libraries like PAPI, some newer features no longer follow the traditional model of counters that can be used to only read the state of the processor. For example, Precise Event Based Sampling (PEBS) can generate records that requires a kernel memory for storage. Additionally, new features like power capping and thermal control require similar new access methods. All of these features are ultimately controlled through Model Specific Registers (MSRs). We therefore need new mechanisms to make such features available to tools and ultimately to the user. libMSR provides a convenient interface to access MSRs and to allow tools to utilize their full functionality.

Source record↗
DOE OSTI2022

MPICPP

SAND2022-3385 O MPICPP is a library that helps users use the Message Passing Interface (MPI), which is defined in the C language. MPICPP is lightweight and thoroughly applies the most tried-and-true features of the C++ language while avoiding the features that are not stable. 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.

Ibanez-Granados, Daniel↗
DOE OSTI2018

pnnl/chissl

Interactive machine learning interface Our invention allows the user to interact with individual instances, see recommendations for similar items, and make adjustments. The scalable nature of our solution allows it to perform instantaneously from the user's perspective, even for 100K+ data items.

Arendt, Dustin↗
DOE OSTI2026

CVEVOLVE

CVEvolve is an agentic AI system for autonomous algorithm discovery for scientific data processing. It creates workflows where large language model agents freely set up and configure development environments and evaluation harnesses, develop and improve data processing algorithms with designed exploration-exploitation balancing mechanisms, log history and findings in a structured database, and run holdout testing to ensure algorithm generalizability. CVEvolve offers a zero-code interface and does not require users to provide structured data and evaluation scripts.

Cherukara, MatthewJoseph [Argonne National Laborat↗
DOE OSTI2016

Evaluating and extending user-level fault tolerance in MPI applications

The user-level failure mitigation (ULFM) interface has been proposed to provide fault-tolerant semantics in the Message Passing Interface (MPI). Previous work presented performance evaluations of ULFM; yet questions related to its programability and applicability, especially to non-trivial, bulk synchronous applications, remain unanswered. In this article, we present our experiences on using ULFM in a case study with a large, highly scalable, bulk synchronous molecular dynamics application to shed light on the advantages and difficulties of this interface to program fault-tolerant MPI applications. We found that, although ULFM is suitable for master–worker applications, it provides few benefits for more common bulk synchronous MPI applications. Furthermore, to address these limitations, we introduce a new, simpler fault-tolerant interface for complex, bulk synchronous MPI programs with better applicability and support than ULFM for application-level recovery mechanisms, such as global rollback.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Large-scale simulations require efficient computation across the entire computing hierarchy. A challenge of the Exascale Computing Project (ECP) was to reconcile highly heterogeneous hardware with the myriad of applications that were required to run on these supercomputers. Mathematical software forms the backbone of almost all scientific applications, providing efficient abstractions and operations that are crucial to harness the performance of computing systems. Ginkgo is one such mathematical software library, nurtured by ECP, providing high-performance, user-friendly, and performance portable interfaces for applications in ECP and beyond. In this paper, we elaborate on Ginkgo’s philosophy of high-performance software that is sustainable, reproducible, and easy to use. We showcase the wide feature set of solvers and preconditioners available in Ginkgo and the central concepts involved in their design. We elaborate on four different ECP software integrations: MFEM, PeleLM + SUNDIALS, XGC, and ExaSGD that use Ginkgo to accelerate their science runs. Performance studies of different problems from these applications highlight the effectiveness of Ginkgo and the benefits incurred by these ECP applications.

Cojean, Terry↗
DOE OSTI2025

CROCUS Low Cost All-in-One Weather Station AMB-004 Data Argonne National Laboratory Prairie Site

The Ambient Weather WS-2902D (AMB) is a low cost weather station that has become very useful for filling data gaps in harder to deploy locations. These low cost weather stations collect 13 second data, which is averaged to a five minute data output available to users through an Application Programming Interface (API) key. The data files contain measurements for precipitation, temperature, wind chill/heat index, relative humidity, dew point, UV index, solar radiation, wind speed, wind direction, wind gust, and with an external particulate matter 2.5 (PM 2.5) sensor. Having all of these measurements in one condense system allows for fast deploying and dense network capabilities. Three of the AMB weather stations were deployed at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The instruments are denoted by their three digit identifier (CMS-AMB-xxx) format. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (CMS-AMB-004), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or ACT-DOE.

EARTH SCIENCE > ATMOSPHERE > AEROSOLS > PARTICULAT↗
DOE OSTI2015

MueMex User's Guide

This is the user guide for the Matlab interface in MUELU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Short Distance of Nuclei - Mining the Wealth of Existing Jefferson Lab Data - Final Report

Over the last fifteen years of operation, the Jefferson Lab CLAS Collaboration has performed many experiments using nuclear targets. Because the CLAS detector has a very large acceptance and because it used a very open (i.e., nonspecific) trigger, there is a vast amount of data on many different reaction channels yet to be analyzed. The goal of the Jefferson Lab Nuclear Data Mining grant was to (1) collect the data from nuclear target experiments using the CLAS detector, (2) collect the associated cuts and corrections used to analyze that data, (3) provide non-expert users with a software environment for easy analysis of the data, and (4) to search for interesting reaction signatures in the data. We formed the Jefferson Lab Nuclear Data Mining collaboration under the auspices of this grant. The collaboration successfully carried out all of our goals. Dr. Gavalian, the data mining scientist, created a remarkably user-friendly web-based interface to enable easy analysis of the nuclear-target data by non-experts. Data from many of the CLAS nuclear target experiments has been made available on servers at Old Dominion University. Many of the associated cuts and corrections have been incorporated into the data mining software. The data mining collaboration was extraordinarily successful in finding interesting reaction signatures in the data. Our paper Momentum sharing in imbalanced Fermi systems was published in Science. Several analyses of CLAS data are continuing and will result in papers after the end of the grant period. We have held several analysis workshops and have given many invited talks at international conferences and workshops related to the data mining initiative. Our initiative to maximize the impact of data collected with CLAS in the 6-GeV era was very successful. During the hiatus between the end of 6-GeV experiments and the beginning of 12-GeV experiments, our collaboration and the physics community at large benefited tremendously from the Jefferson Lab Nuclear Data Mining effort.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Maritime Fuel Cell Generator Project [FY2018]

Fuel costs and emissions in maritime ports are an opportunity for transportation energy efficiency improvement and emissions reduction efforts. Ocean-going vessels, harbor craft, and cargo handling equipment are still major contributors to air pollution in and around ports. Diesel engine costs continually increase as tighter criteria pollutant regulations come into effect and will continue to do so with expected introduction of carbon emission regulations. Diesel fuel costs will also continue to rise as requirements for cleaner fuels are imposed. Both aspects will increase the cost of diesel-based power generation on the vessel and on shore. Although fuel cells have been used in many successful applications, they have not been technically or commercially validated in the port environment. One opportunity to do so was identified in Honolulu Harbor at the Young Brothers Ltd. wharf. At this facility, barges sail regularly to and from neighboring islands and containerized diesel generators provide power for the reefers while on the dock and on the barge during transport, nearly always at part load. Due to inherent efficiency characteristics of fuel cells and diesel generators, switching to a hydrogen fuel cell power generator was found to have potential emissions and cost savings. Deployment in Hawaii showed the unit needed greater reliability in the start-up sequence, as well as an improved interface to the end-user, thereby presenting opportunities for repairing/upgrading the unit for deployment in another locale. In FY2018, the unit was repaired and upgraded based on the Hawaii experience, and another deployment site was identified for another 6-month deployment of the 100 kW MarFC.

08 HYDROGEN↗
DOE OSTI2022

Useability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: increased support of face variables, arbitrary spatial and temporal evaluation of material properties, and the addition of a triangular meshing library in libMesh.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

User-oriented Improvements in the MOOSE Framework in Support of Multiphysics Simulation

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: chainable execution objects or executors, support for transfers between same-level applications in a coupling scheme, support for boundary/subdomain restricted transfers, support for transfers between applications with different coordinate or unit systems, support for MOOSE applications in the NEAMS Workbench, deployment of the MOOSE application of the Idaho National Laboratory (INL) high-performance computing (HPC) OnDemand platform, the addition of a triangular meshing library in libMesh, and increased support of face variables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantum Computing – Real-Time Data Processing from a Dilution Refrigerator

This poster presents a real-time data visualization system for monitoring and displaying data from a Bluefors control unit connected to a dilution refrigerator. The goal is to provide an aesthetically pleasing and user-friendly web-based interface that continuously updates and displays critical data such as temperature and flow rates at various points within the refrigerator. Leveraging WebSocket technology, the system establishes multiple connections to the dilution refrigerators, enabling simultaneous monitoring of several units. The interactive webpage dynamically updates the data, providing researchers and operators with instant insights into the system's performance. The system's ability to stream and visualize data in real-time enhances the understanding of the dilution refrigerator's behavior, aiding in optimizing its operation and ensuring efficient scientific experiments. The application's web-based nature makes it easily accessible from any device with internet connectivity, promoting seamless collaboration and remote monitoring capabilities. Overall, this poster offers a comprehensive solution for real-time data visualization and analysis of dilution refrigerators, catering to the needs of researchers and scientists working in low-temperature physics and quantum computing fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗