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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Journal of Open Source Software (JOSS): Bringing Open-Source Software Practices to the Scholarly Publishing Community for Authors, Reviewers, Editors, and Publishers

Open-source software (OSS) is a critical component of open science, but contributions to the OSS ecosystem are systematically undervalued in the current academic system. The Journal of Open Source Software (JOSS) contributes to addressing this by providing a venue (that is itself free, diamond open access, and all open-source, built in a layered structure using widely available elements/services of the scholarly publishing ecosystem) for publishing OSS, run in the style of OSS itself. A particularly distinctive element of JOSS is that it uses open peer review in a collaborative, iterative format, unlike most publishers. Additionally, all the components of the process—from the reviews to the papers to the software that is the subject of the papers to the software that the journal runs—are open. We describe JOSS’s history and its peer review process using an editorial bot, and we present statistics gathered from JOSS’s public review history on GitHub showing an increasing number of peer reviewed papers each year. We discuss the new JOSSCast and use it as a data source to understand reasons why interviewed authors decided to publish in JOSS. JOSS’s process differs significantly from traditional journals, which has impeded JOSS’s inclusion in indexing services such as Web of Science. In turn, this discourages researchers within certain academic systems, such as Italy’s, which emphasize the importance of Web of Science and/or Scopus indexing for grant applications and promotions. JOSS is a fully diamond open-access journal with a cost of around US$\$$5 per paper for the 401 papers published in 2023. The scalability of running JOSS with volunteers and financing JOSS with grants and donations is discussed.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

The case for free and open source software in research and scholarship

Free and open source software (FOSS) is any computer program released under a licence that grants users rights to run the program for any purpose, to study it, to modify it, and to redistribute it in original or modified form. Here, our aim is to explore the intersection between FOSS and computational reproducibility. We begin by situating FOSS in relation to other ‘open’ initiatives, and specifically open science, open research, and open scholarship. In this context, we argue that anyone who actively contributes to the research process today is a computational researcher, in that they use computers to manage and store information. We then provide a primer to FOSS suitable for anyone concerned with research quality and sustainability—including researchers in any field, as well as support staff, administrators, publishers, funders, and so on. Next, we illustrate how the notions introduced in the primer apply to resources for scientific computing, with reference to the GNU Scientific Library as a case study. We conclude by discussing why the common interpretation of ‘open source’ as ‘open code’ is misplaced, and we use this example to articulate the role of FOSS in research and scholarship today.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Building Energy Management Open Source Software

This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture – BEMOSS is an open source operating system that is built upon VOLTTRON – a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play – BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability – BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness – Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment – With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring – BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security – In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee – BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.

Source record↗
DOE OSTI2017

Building Energy Management Open Source Software

This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture – BEMOSS is an open source operating system that is built upon VOLTTRON – a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play – BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability – BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness – Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment – With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring – BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security – In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee – BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.

Source record↗
DOE OSTI2022

PyOECP: A flexible open-source software library for estimating and modeling the complex permittivity based on the open-ended coaxial probe (OECP) technique

Here, we present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on three different methods. The software library contains the dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) in the field of science and engineering are required only so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov Chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, electrode polarization, a typical measurement artifact for interpreting dielectric spectra, can be incorporated into the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem), is also included. This open-source software enables users to freely adjust the physical parameters to obtain physical insight into their materials under test and will be consistently updated for more accurate measurement and interpretation of dielectric spectra in an automated manner. This work describes the theoretical and mathematical background of the software, lays out the workflow, and validates the software functionality based on both synthetic and empirical data included in the software.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

A Flexible Method for Producing F.E.M. Analysis of Bone Using Open-Source Software

This project, performed in support of the NASA GRC Space Academy summer program, sought to develop an open-source workflow methodology that segmented medical image data, created a 3D model from the segmented data, and prepared the model for finite-element analysis. In an initial step, a technological survey evaluated the performance of various existing open-source software that claim to perform these tasks. However, the survey concluded that no single software exhibited the wide array of functionality required for the potential NASA application in the area of bone, muscle and bio fluidic studies. As a result, development of a series of Python scripts provided the bridging mechanism to address the shortcomings of the available open source tools. The implementation of the VTK library provided the most quick and effective means of segmenting regions of interest from the medical images; it allowed for the export of a 3D model by using the marching cubes algorithm to build a surface mesh. To facilitate the development of the model domain from this extracted information required a surface mesh to be processed in the open-source software packages Blender and Gmsh. The Preview program of the FEBio suite proved to be sufficient for volume filling the model with an unstructured mesh and preparing boundaries specifications for finite element analysis. To fully allow FEM modeling, an in house developed Python script allowed assignment of material properties on an element by element basis by performing a weighted interpolation of voxel intensity of the parent medical image correlated to published information of image intensity to material properties, such as ash density. A graphical user interface combined the Python scripts and other software into a user friendly interface. The work using Python scripts provides a potential alternative to expensive commercial software and inadequate, limited open-source freeware programs for the creation of 3D computational models. More work will be needed to validate this approach in creating finite-element models.

gravitational physiology↗
DOE OSTI2024

A Survey of Open Source Software Repositories in the U.S. Department of Energy’s National Laboratories

There are 17 national laboratory systems in the United States operating under the auspices of the U.S. Department of Energy (DOE). These government labs employ tens of thousands of people engaging in research software engineering activities across a variety of missions. To support this work, many open source projects are maintained. Further, many of these projects have broad utility to the computing community at large and domain scientists in a variety of fields. However, the complexity and decentralized nature of the laboratory system has resulted in a situation where no one entity even knows about all the open source software projects in this ecosystem, let alone crude metrics of their health. In this article, we do the first external inventory of open source software repositories with a nexus to DOE labs. We posit that a project’s need for sustainability support can be determined by comparing measures of active use to measures of active maintenance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Algorithm Performance Dataset from NASA Open-Source Software

NASA Langley Research Center has recently developed and released the open-source software Multi Model Monte Carlo with Python (MXMCPy- LAR-19756-1) as a general capability for computing the statistics of outputs from an expensive, high-fidelity model by leveraging faster, low-fidelity models for speedup. Given a fixed computational budget and a collection of models with varying cost/accuracy, multi model Monte Carlo (MC) seeks a sample allocation strategy across the models that results in an estimator with optimal variance reduction. MXMCPy is a versatile tool that enables convenient access to many existing multi-model MC approaches (over a dozen algorithms available) within one modular and extensible package [1]. With MXMCPy, users can easily compare existing methods to determine the best choice for their particular problem,while developers have a basis for implementing and sharing new variance reduction approaches. However,there is currently very little understanding about which algorithm will perform best for a given problem (defined by the correlation between and relative cost of the available models) without a brute force search.

Geoffrey F Bomarito↗
DOE OSTI2017

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data

We introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Building Energy Management Open Source Software

Funded by the U.S. Department of Energy in November 2013, a Building Energy Management Open Source Software (BEMOSS) platform was engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. According to the Energy Information Administration (EIA), small- (5,000 square feet or smaller) and medium-sized (between 5,001 to 50,000 square feet) commercial buildings constitute about 95% of all commercial buildings in the U.S. These buildings typically do not have Building Automation Systems (BAS) to monitor and control building operation. While commercial BAS solutions exist, including those from Siemens, Honeywell, Johnsons Controls and many more, they are not cost effective in the context of small- and medium-sized commercial buildings, and typically work with specific controller products from the same company. BEMOSS targets small and medium-sized commercial buildings to address this gap.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

PSCF+: An Extended and Improved Open-Source Software Package for Polymer Self-Consistent Field Calculations

This work introduces PSCF+, a freely available open‑source software tool for modeling how block copolymers self‑assemble into ordered nanoscale structures. The software allows researchers to study a wide range of polymer models and interaction types, making it possible to directly compare theoretical predictions with molecular and simulation‑based studies in a consistent way. PSCF+ incorporates several recently developed numerical methods that significantly reduce computer memory requirements and speed up calculations, enabling efficient use of modern GPU hardware. Here, it also provides automated tools to calculate free‑energy landscapes and phase boundaries, which are essential for understanding and predicting material behavior. Together, these advances make PSCF+ a powerful and flexible platform for studying polymer self‑assembly and support the design of new polymeric materials for scientific and technological applications.

Chemical calculations↗
DOE OSTI2021

PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient

We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.

Yoon, Tae-Jun↗
DOE OSTI2017

TRACC: An open source software for processing sap flux data from thermal dissipation probes

Here, thermal dissipation probes (TDPs) have become a widely used method of monitoring plant water use in recent years. The use of TDPs requires calibration to a theoretical zero-flow value (ΔT0); usually based upon the assumption that at least some nighttime measurements represent zero-flow conditions. Fully automating the processing of data from TDPs is made exceedingly difficult due to errors arising from many sources. However, it is desirable to minimize variation arising from different researchers’ processing data, and thus, a common platform for processing data, including editing raw data and determination of ΔT0, is useful and increases the transparency and replicability of TDP-based research. Here, we present the TDP data processing software TRACC (Thermal dissipation Review Assessment Cleaning and Conversion) to serve this purpose. TRACC is an open-source software written in the language R, using graphical presentation of data and on screen prompts with yes/no or simple numerical responses. It allows the user to select several important options, such as calibration coefficients and the exclusion of nights when vapor pressure deficit does not approach zero. Although it is designed for users with no coding experience, the outputs of TRACC could be easily incorporated into more complex models or software.

60 APPLIED LIFE SCIENCES↗