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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Then and Now: Improving Software Portability, Productivity, and 100× Performance

The US Exascale Computing Project (ECP) has succeeded in preparing applications to run efficiently on the first reported Exascale supercomputers in the world. To achieve this, it modernized the whole leadership software stack, from libraries to simulation codes. In this article, we contrast selected leadership software before and after ECP. We discuss how sustainable research software development for leadership computing can embrace the conversation with the hardware vendors, the leadership computing facilities, the software community, and the domain scientists who are the application developers and integrators of software products. We elaborate on how software needs to take portability as a central design principle and to benefit from interdependent teams; we also demonstrate how moving to programming languages with high momentum, like modern C++, can help improve the sustainability, interoperability, and performance of research software. Finally, we showcase how cross-institutional efforts can enable algorithm advances that are beyond incremental performance optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Leveraging OpenStudio's Application Programming Interfaces: Preprint

OpenStudio development efforts have been focused on providing Application Programming Interfaces (APIs) where users are able to extend OpenStudio without the need to compile the open source libraries. This paper will discuss the basic purposes and functionalities of the core libraries that have been wrapped with APIs including the Building Model, Results Processing, Advanced Analysis, UncertaintyQuantification, and Data Interoperability through Translators. Several building energy modeling applications have been produced using OpenStudio's API and Software Development Kits (SDK) including the United States Department of Energy's Asset ScoreCalculator, a mobile-based audit tool, an energy design assistance reporting protocol, and a portfolio scale incentive optimization analysismethodology. Each of these software applications will be discussed briefly and will describe how the APIs were leveraged for various uses including high-level modeling, data transformations from detailed building audits, error checking/quality assurance of models, and use of high-performance computing for mass simulations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

Here, we discuss the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Lastly, initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

42 ENGINEERING↗
DOE OSTI2022

Application of Manufacturing Quality Management Principles to PV System Installations

To help SETO/DOE achieve its goals, the IBTS team proposed a project addressing system reliability by improving installation standards and quality management. The proposed approach was designed to help achieve measurable reductions in installation defect density and improvements in the performance of PV systems by optimizing design and installation of residential and commercial PV systems. This approach addressed the soft costs associated with installations and quality management. The project demonstrated improved system reliability and reduced PV system installation costs. The software developed improved operations, decreased risk, and increased the overall value of PV systems across their lifecycle. The project used several data collection methods, including extensive industry surveys, face-to-face high-level interviews at industry conferences, stakeholder teleconferences, and in-depth interviews conducted by IBTS staff. Results from the research found the industry needs a uniform assessment method for national providers to be more efficient; the software should support both code officials and installers; most industry stakeholders would find value in a centralized software system that allows them to collect, report, and review information on in-process and completed solar installations; and mobile solutions that bridge existing knowledge gaps with inspectors and integrate with existing methodologies (such as permitting software) are of great value. The software solution developed is web-based, allowing for national access, and is built on a Google Firebase platform that can handle significant users and data. It can be used onsite or remotely, allowing for code compliance to continue despite ongoing pandemic related delays or shutdowns for local economies. The information provided by the software tool allows users to uniformly assess a system for compliance and use that aggregated data to identify training topics or create internal process designed to improving issues and reducing occurrence. This solution has multiple benefits in managing quality at time of use and promoting an increase in future safety and quality through education. Perhaps most importantly, this software increases public safety by ensuring compliance of installed systems and allows for local AHJs to remotely engage specialized and qualified solar specific expertise for oversite of the installation in their jurisdictions. Data analysis provides the quality feedback loop identifying the root cause of failure and drives installation practices to improve through training and education, resulting in systems with higher performance, greater reliability, and reduced operations and maintenance costs. With the successful completion of this project, the industry can expect reduced soft costs and increased performance and safety and will ultimately benefit from longer performing systems that cost less to operate.

14 SOLAR ENERGY↗
DOE OSTI2018

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

SAM Photovoltaic Model Technical Reference 2016 Update

This manual describes the photovoltaic performance model in the System Advisor Model (SAM) software, Version 2016.3.14 Revision 4 (SSC Version 160). It is an update to the 2015 edition of the manual, which describes the photovoltaic model in SAM 2015.1.30 (SSC 41). This new edition includes corrections of errors in the 2015 edition and descriptions of new features introduced in SAM 2016.3.14, including: 3D shade calculator Battery storage model DC power optimizer loss inputs Snow loss model Plane-of-array irradiance input from weather file option Support for sub-hourly simulations Self-shading works with all four subarrays, and uses same algorithm for fixed arrays and one-axis tracking Linear self-shading algorithm for thin-film modules Loss percentages replace derate factors. The photovoltaic performance model is one of the modules in the SAM Simulation Core (SSC), which is part of both SAM and the SAM SDK. SAM is a user-friedly desktop application for analysis of renewable energy projects. The SAM SDK (Software Development Kit) is for developers writing their own renewable energy analysis software based on SSC. This manual is written for users of both SAM and the SAM SDK wanting to learn more about the details of SAM's photovoltaic model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Bayesian and HRA-Aided Method for the Novel Reliability Analysis of Software

Technological advancements and nuclear power plant modernization has inspired considerable research in the areas of safety and reliability, yet there remains a lack of consensus for the reliability assessment of digital instrumentation and control (I&C) systems. Motivated by the lack of consensus for reliability analysis methods, this work employs a novel framework that incorporates Bayesian, human reliability, and common-cause failure (CCF) modeling techniques. The novel framework allows the use of state-of-the-art or classical modeling techniques when accounting for human and CCF effects on system reliability. The Bayesian and HRA-Aided Method for the Reliability Analysis of Software (BAHAMAS) is demonstrated by a case study for the quantification of software hazards found in a previous analysis of a digital reactor trip system. The results demonstrate the ability of BAHAMAS to account for human activities during the software development life cycle and their influence on software reliability. BAHAMAS is a flexible tool for extending the coverage of conventional probabilistic risk assessments to include modernized digital I&C systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Modernising ATLAS Software Build Infrastructure

In the last year ATLAS has radically updated its software development infrastructure hugely reducing the complexity of building releases and greatly improving build speed, flexibility and code testing. The first step in this transition was the adoption of CMake as the software build system over the older CMT. This required the development of an automated translation from the old system to the new, followed by extensive testing and improvements. This resulted in a far more standard build process that was married to the method of building ATLAS software as a series of 12 separate projects from Subversion. We then proceeded with a migration of the code base from Subversion to Git. As the Subversion repository had been structured to manage each package more or less independently there was no simple mapping that could be used to manage the migration into Git. Instead a specialist set of scripts that captured the software changes across official software releases was developed. With some clean up of the repository and the policy of only migrating packages in production releases, we managed to reduce the repository size from 62 GiB to 220 MiB. After moving to Git we took the opportunity to introduce continuous integration so that now each code change from developers is built and tested before being approved. With both CMake and Git in place we also dramatically simplified the build management of ATLAS software. Many heavyweight homegrown tools were dropped and the build procedure was reduced to a single bootstrap of some external packages, followed by a full build of the rest of the stack. This has reduced the time for a build by a factor of 2. It is now easy to build ATLAS software, freeing developers to test compile intrusive changes or new platform ports with ease. We have also developed a system to build lightweight ATLAS releases, for simulation, analysis or physics derivations which can be built from the same branch.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

GridKit

GridKit is a software development kit for interfacing power systems and power grid application software with high performance computing (HPC) libraries developed at National Labs and academia. It is also intended as interoperability layer between different numerical libraries. GridKit is not a standalone application, but comes with a suite of test examples illustrating possible usage.

Peles, Slaven↗
DOE OSTI2015

Development of an Advanced Stimulation / Production Predictive Simulator for Enhanced Geothermal Systems

There are several well-known obstacles to the successful deployment of EGS projects on a commercial scale, of course. EGS projects are expected to be deeper, on the average, than conventional “natural” geothermal reservoirs, and drilling costs are already a formidable barrier to conventional geothermal projects. Unlike conventional resources (which frequently announce their presence with natural manifestations such as geysers, hot springs and fumaroles), EGS prospects are likely to appear fairly undistinguished from the earth surface. And, of course, the probable necessity of fabricating a subterranean fluid circulation network to mine the heat from the rock (instead of simply relying on natural, pre-existing permeable fractures) adds a significant degree of uncertainty to the prospects for success. Accordingly, the basic motivation for the work presented herein was to try to develop a new set of tools that would be more suitable for this purpose. Several years ago, the Department of Energy’s Geothermal Technologies Office recognized this need and funded a cost-shared grant to our company (then SAIC, now Leidos) to partner with Geowatt AG of Zurich, Switzerland and undertake the development of a new reservoir simulator that would be more suitable for EGS forecasting than the existing tools. That project has now been completed and a new numerical geothermal reservoir simulator has been developed. It is named “HeatEx” (for “Heat Extraction”) and is almost completely new, although its methodology owes a great deal to other previous geothermal software development efforts, including Geowatt’s “HEX-S” code, the STAR and SPFRAC simulators developed here at SAIC/Leidos, the MINC approach originally developed at LBNL, and tracer analysis software originally formulated at INEL. Furthermore, the development effort was led by engineers with many years of experience in using reservoir simulation software to make meaningful forecasts for real geothermal projects, not just software designers. It is hoped that, as a result, HeatEx will prove useful during the early stages of the development of EGS technology. The basic objective was to design a tool that could use field data that are likely to become available during the early phases of an EGS project (that is, during initial reconnaissance and fracture stimulation operations) to guide forecasts of the longer-term behavior of the system during production and heat-mining.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry

An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized the spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Optical Mode Converters Final Report CRADA No. TC-0838-94

The information age was maturing, and photonics was emerging as a significant technology with important'national security and commercial implications at the time of the CRADA. This was largely due to the vast information carrying capacity of optical beams and the availability of cheap.and effective optical fiber waveguides to guide the light. However, a major limitation to the widespread deployment of photonic systems was the high-cost (in an economic and performance sense) associated with coupling optical power between optoelectronic waveguide devices or between a device and an optical fiber. The problem was critical in the case of single-mode waveguide devices. Mitigating these costs would be a significant and pervasive enabler of the technology for a wide variety of applications that would have crucial defense and economic impact. The partners worked together to develop optical mode size converters on silicon substrates. Silicon was chosen because of its compatibility with the required photolithographic and micromachining techniques. By choosing silicon, these techniques could enable the close coupling of high-speed, high density silicon electronic circuitry to efficient low-cost photonics. The efficient coupling of electronics and photonics technologies would be important for many information age technologies. The joint nature of this project was intended to allow HP to benefit from some unique LLNL capabilities, and LLNL would be in a position to learn from HP and enhance its value to fundamental DP missions. Although the CRADA began as a hardware development project to develop the mode converter, it evolved into a software development venture. LLNL and HP researchers examined literature, performed some preliminary calculations, and evaluated production trade-offs of several known techniques to determine the best candidates for an integrated system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker

The High-Luminosity upgrade of the Large Hadron Collider (LHC) will see the accelerator reach an instantaneous luminosity of 7 × 10 34 cm −2 s −1 with an average pileup of 200 proton-proton collisions. These conditions will pose an unprecedented challenge to the online and offline reconstruction software developed by the experiments. The computational complexity will exceed by far the expected increase in processing power for conventional CPUs, demanding an alternative approach. Industry and High-Performance Computing (HPC) centers are successfully using heterogeneous computing platforms to achieve higher throughput and better energy efficiency by matching each job to the most appropriate architecture. In this paper we will describe the results of a heterogeneous implementation of pixel tracks and vertices reconstruction chain on Graphics Processing Units (GPUs). The framework has been designed and developed to be integrated in the CMS reconstruction software, CMSSW. The speed up achieved by leveraging GPUs allows for more complex algorithms to be executed, obtaining better physics output and a higher throughput.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

NJOY21: A Successor to the NJOY Nuclear Data Processing System

NJOY21 is an initiative at Los Alamos National Laboratory (LANL) to develop software to succeed the NJOY nuclear data processing system. Specifically, the aim of the project is to provide: - a stand-alone executable for nuclear data processing in the vein of the original NJOY and, - a hierarchy of reusable loosely-coupled, object-oriented component libraries. The name NJOY21 was chosen to denote a commitment to provide software suitable for the 21. Century; integrating modern development practices and tools from the inception of the project. This summary will expand upon the current goals and design of the project. Before going onto discuss NJOY21, it is worthwhile to briefly establish the historical context and motivating factors. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Safety software release options to support plant start-up and commissioning activities - 285

The schedule demands on new nuclear power plant site testing and commissioning programs challenge the plant's Instrumentation and Control (I and C) supplier's ability to provide certified safety software releases to meet the needs of these programs. This paper outlines the typical certified safety software development and certification process which follows a Waterfall software life-cycle model. The conflicts that result between supporting the site program and the safety software supplier's internal certification program are identified. An adapted 'functional' safety release process is presented that supports the site program's needs for software changes and in parallel enables the safety software certification process to proceed. Comparisons between the two safety software release processes are examined and the benefits realized through the use of the adapted 'functional' safety software release process are discussed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗