Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computer Programming and software”

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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

gpCAM v8

gpCAM is a Python software for large-scale Gaussian-Process driven uncertainty quantification, Bayesian Optimization, and Autonomous Experimentation. It is designed with maximum flexibility and customizability while offering record-breaking computing capabilities. In 2023 gpCAM broke the world record for Gaussian processes on large datasets set in 2019. Through clever programming and math, Gaussian Process building blocks, such as prior mean, kernel, and noise functions maintain their mathematical flexibility while supporting acceleration and scaling. This flexibility means that the approximation and uncertainty quantification can be domain-aware and extended over exotic input and output spaces.

Noack, Marcus↗
DOE OSTI2021

FAST-1.0.1 User Installation and Verification Guide

The purpose of this document is to provide the user information about the installation of FAST-1.0.1 on their computers or servers. General information about the code and supported operating systems is described in Section 1.0.1. Self-service oriented FAST-1.0.1 software licensing steps are described in Section 2.0. An installation verification test suite is provided with FAST-1.0.1 and described in Section 3.0. A convenience script for converting FRAPCON to FAST inputs is discussed in Section 4.0. FAST-1.0.1 was developed and released under a software quality assurance program based upon NQA-1-2017. FAST-1.0.1 is the latest baseline code and the result of a bug fixes to FAST-1.0 with other software and methodology developments. The installation verification test suite contains both steady state and transient Anticipated Operation Occurrences (AOOs). Capability to model accident conditions, such as Reactivity Initiated Accidents (RIAs) and Loss Of Coolant Accidents (LOCAs), are targeted for a later release of FAST. FRAPTRAN-2.0 will continue to be used for accident conditions until the release of FAST with accident condition modeling capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2018

Speeding up software with VecCore

Portable and efficient vectorization is a significant challenge in large software projects such as GeantV, ROOT, and experiments’ frameworks. Nevertheless, fully exploiting SIMD parallelism will be a required step in order to bridge the widening gap between the needs and availability of computing resouces for data analysis and processing in particle physics. Although there are SIMD libraries that wrap compiler intrinsics into a convenient interface, they do not always support all available architectures, or they only perform well in some of them. The VecCore library was created to address some of these performance and portability issues by providing a unified abstraction layer on top of existing libraries, such as Vc or UME::SIMD. In this article, we discuss VecCore’s programming model for SIMD code and some use cases in HEP software packages such as VecGeom and GeantV.

Amadio, G.↗
DOE OSTI2025

ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creating a collection of reliable, highly specialized, and optimized AI assistants for HPC based on the cost-effective and fast Code Llama fine-tuning processes and expert supervision. We target major components of the HPC software stack, including programming models, runtimes, I/O, tooling, and math libraries. Thanks to AI, ChatHPC provides a more productive HPC ecosystem by boosting important tasks related to portability, parallelization, optimization, scalability, and instrumentation, among others. With relatively small datasets (on the order of KB), the AI assistants, which are created in a few minutes by using one node with two NVIDIA H100 GPUs and the ChatHPC library, can create new capabilities with Meta’s 7-billion parameter Code Llama base model to produce high-quality software with a level of trustworthiness of up to 90% higher than the 1.8-trillion parameter OpenAI ChatGPT-4o model for critical programming tasks in the HPC software stack.

Young, Aaron [ORNL] (ORCID:0000000254484667)↗
DOE OSTI2014

National Computational Infrastructure for Lattice Gauge Theory: SciDAC-2 Closeout Report

Under its SciDAC-1 and SciDAC-2 grants, the USQCD Collaboration developed software and algorithmic infrastructure for the numerical study of lattice gauge theories. This work was carried out jointly by high energy and nuclear physicists within USQCD, in collaboration with applied mathematicians and computer scientists. The software and its documentation is publicly available at the USQCD software web site http://www.usqcd.org/usqcd-software. The code has been widely adopted within the United States, and is used extensively abroad. It has been instrumental in our effective use of leadership class computers, and of the dedicated computers funded for USQCD through the LQCD Computing Project. The committees which review our hardware program on a yearly basis have consistently emphasized the importance of the work done under our SciDAC grants, and the need for their continuation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Goma 6.0

Goma 6.0, open-sourced in 2013, is finite element software that excels in the analyses of multiphysics processes, particularly those involving the major branches of mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SIMULATED PERFORMANCE OF TIMESCALE METRICS FOR APERIODIC LIGHT CURVES

Aperiodic variability is a characteristic feature of young stars, massive stars, and active galactic nuclei. With the recent proliferation of time-domain surveys, it is increasingly essential to develop methods to quantify and analyze aperiodic variability. We develop three timescale metrics that have been little used in astronomy—Δm-Δt plots, peak-finding, and Gaussian process regression—and present simulations comparing their effectiveness across a range of aperiodic light curve shapes, characteristic timescales, observing cadences, and signal to noise ratios. We find that Gaussian process regression is easily confused by noise and by irregular sampling, even when the model being fit reflects the process underlying the light curve, but that Δm-Δt plots and peak-finding can coarsely characterize timescales across a broad region of parameter space. We make public the software we used for our simulations, both in the spirit of open research and to allow others to carry out analogous simulations for their own observing programs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Preventing Run-Time Bugs at Compile-Time Using Advanced C++

When writing software, we develop algorithms that tell the computer what to do at run-time. Our solutions are easier to understand and debug when they are properly modeled using class hierarchies, enumerations, and a well-factored API. Unfortunately, even with these design tools, we end up having to debug our programs at run-time. Worse still, debugging an embedded system changes its dynamics, making it tough to find and fix concurrency issues. This paper describes techniques using C++ to detect run-time bugs *at compile time*. A concurrency library, developed at Fermilab, is used for examples in illustrating these techniques.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

PIPER: Performance Insights for Programmers and Exascale Runtimes

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.

42 ENGINEERING↗
DOE OSTI2014

Gamma Detector Response and Analysis Software - Detector Response Function

GADRAS-DRF uses a Detector Response Function (DRF) to compute the response of gamma-ray detectors incident radiation. The application includes provision for plotting measured and computed spectra and for characterizing detector response parameters based on measurements of a series of calibration sources (e.g., Ba-133, Cs-137, Co-60, and Th-228). An application program interface enables other programs to access the dynamic-link library that is used to compute spectra.

Source record↗
DOE OSTI2025

Refining PeakDecoder Version 2

Novel computational tools for processing multidimensional mass spectrometry (MS) data are necessary to enable deeper and automated detection and quantification of metabolites in complex backgrounds. Multidimensional MS data includes measurements from liquid chromatography (LC) and ion mobility spectrometry (IM) separations, and precursor and fragment ion spectra collected in data-independent acquisition (DIA) mode. PeakDecoder is an artificial intelligence (AI)-based software that enables automated interpretation of this kind of data to identify and quantify individual metabolites in complex mixtures. The goal of this project was to improve and re-implement PeakDecoder in a better suited programming language to enable its commercialization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-T-524: Web-Based Radiation Oncology Incident Reporting and Learning System (ROIRLS)

Purpose: Describe a Web-based Radiation Oncology Incident Reporting and Learning system that has the potential to improve quality of care for radiation therapy patients. This system is an important facet of continuing effort by our community to maintain and improve safety of radiotherapy.Material and Methods: The VA National Radiation Oncology Program office has embarked on a program to electronically collect adverse events and near miss data of radiation treatment of over 25,000 veterans treated with radiotherapy annually. Software used for this program is deployed on the VAs intranet as a Website. All data entry forms (adverse event or near miss reports, work product reports) utilize standard causal, RT process step taxonomies and data dictionaries defined in AAPM and ASTRO reports on error reporting (AAPM Work Group Report on Prevention of Errors and ASTROs safety is no accident report). All reported incidents are investigated by the radiation oncology domain experts. This system encompasses the entire feedback loop of reporting an incident, analyzing it for salient details, and developing interventions to prevent it from happening again. The operational workflow is similar to that of the Aviation Safety Reporting System. This system is also synergistic with ROSIS and SAFRON. Results: The ROIRLS facilitates the collection of data that help in tracking adverse events and near misses and develop new interventions to prevent such incidents. The ROIRLS electronic infrastructure is fully integrated with each registered facility profile data thus minimizing key strokes and multiple entries by the event reporters. Conclusions: OIRLS is expected to improve the quality and safety of a broad spectrum of radiation therapy patients treated in the VA and fulfills our goal of Effecting Quality While Treating Safely The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations Inc. and is deployed on the VA intranet as a Website. The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations Inc. and is deployed on the VA intranet as a Website.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP2-04: Comprehensive Machine Isocenter Evaluation with Separation of Gantry, Collimator, and Table Variables

Purpose: To develop and demonstrate application of a method that characterizes deviation of linac x-ray beams from the centroid of the volumetric radiation isocenter as a function of gantry, collimator, and table variables. Methods: A set of Winston-Lutz ball-bearing images was used to determine the gantry radiation isocenter as the midrange of deviation values resulting from gantry and collimator rotation. Also determined were displacement of table axis from gantry isocenter and recommended table axis adjustment. The method, previously reported, has been extended to include the effect of collimator walkout by obtaining measurements with 0 and 180 degree collimator rotation for each gantry angle. Twelve images were used to characterize the volumetric isocenter for the full range of available gantry, collimator, and table rotations. Results: Three Varian True Beam, two Elekta Infinity and four Versa HD linacs at five institutions were tested using identical methodology. Varian linacs exhibited substantially less deviation due to head sag than Elekta linacs (0.4 mm vs. 1.2 mm on average). One linac from each manufacturer had additional isocenter deviation of 0.3 to 0.4 mm due to jaw instability with gantry and collimator rotation. For all linacs, the achievable isocenter tolerance was dependent on adjustment of collimator position offset, transverse position steering, and alignment of the table axis with gantry isocenter, facilitated by these test results. The pattern and magnitude of table axis wobble vs. table angle was reproducible and unique to each machine. Conclusion: This new method provides a comprehensive set of isocenter deviation values including all variables. It effectively facilitates minimization of deviation between beam center and target (ball-bearing) position. This method was used to quantify the effect of jaw instability on isocenter deviation and to identify the offending jaw. The test is suitable for incorporation into a routine machine QA program. Software development was performed by Radiological Imaging Technology, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Havens: Explicit Reliable Memory Regions for HPC Applications

Supporting error resilience in future exascale-class supercomputing systems is a critical challenge. Due to transistor scaling trends and increasing memory density, scientific simulations are expected to experience more interruptions caused by transient errors in the system memory. Existing hardware-based detection and recovery techniques will be inadequate to manage the presence of high memory fault rates. In this paper we propose a partial memory protection scheme based on region-based memory management. We define the concept of regions called havens that provide fault protection for program objects. We provide reliability for the regions through a software-based parity protection mechanism. Our approach enables critical program objects to be placed in these havens. The fault coverage provided by our approach is application agnostic, unlike algorithm-based fault tolerance techniques.

exascale computing↗
DOE OSTI2017

OSiRIS: a distributed Ceph deployment using software defined networking for multi-institutional research

We report on the first year of the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) which is targeting the creation of a distributed Ceph storage infrastructure coupled together with software-defined networking to provide high-performance access for wellconnected locations on any participating campus. The projects goal is to provide a single scalable, distributed storage infrastructure that allows researchers at each campus to read, write, manage and share data directly from their own computing locations. The NSF CC*DNI DIBBS program which funded OSiRIS is seeking solutions to the challenges of multi-institutional collaborations involving large amounts of data and we are exploring the creative use of Ceph and networking to address those challenges. While OSiRIS will eventually be serving a broad range of science domains, its first adopter will be the LHC ATLAS detector project via the ATLAS Great Lakes Tier-2 (AGLT2) jointly located at the University of Michigan and Michigan State University. Part of our presentation will cover how ATLAS is using the OSiRIS infrastructure and our experiences integrating our first user community. The presentation will also review the motivations for and goals of the project, the technical details of the OSiRIS infrastructure, the challenges in providing such an infrastructure, and the technical choices made to address those challenges. We will conclude with our plans for the remaining 4 years of the project and our vision for what we hope to deliver by the projects end.

97 MATHEMATICS AND COMPUTING↗