scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Developing a Dynamic and Responsive Online Learning Environment

2011 ◽  
pp. 92-109 ◽  
Author(s):  
Janet Buchan
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Appropriate Technology ◽  
Online Learning Environment ◽  
Institutional Level ◽  
Learning And Teaching ◽  
Community Source

Charles Stuart University adopted the open source software, Sakai, as the foundation for the university’s new, integrated Online Learning Environment. This study explores whether a pedagogical advantage exists in adopting such an open source learning management system. Research suggests that the community source approach to development of open source software has many inherent pedagogical advantages, but this paper examines whether this is due to the choice of open source software or simply having access to appropriate technology for learning and teaching in the 21st century. The author also addresses the challenges of the project management methodology and processes in the large-scale implementation of an open-source courseware management solution at the institutional level. Consequently, this study outlines strategies that an institution can use to harness the potential of a community source approach to software development to meet the institutional and individual user needs into the future.

Taming of ‘Openness' in Software Innovation Systems

2017 ◽  
Vol 8 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Mehmet Gencer ◽  
Beyza Oba
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Open Innovation ◽  
Large Scale ◽  
Historical Perspective ◽  
Systems Of Innovation ◽  
Innovation Potential ◽  
Emergent Community ◽  
Strategic Pattern ◽  
The Continuum

In large-scale open source software (OSS) innovation ecosystems that incorporate firms, a variety of measures are taken to tame the potentially chaotic activities and align the contributions of various participants with the strategic priorities of major stakeholders. Such taming rests on the dual desires of this emergent community of firms to unleash the innovation potential of OSS and to drive it to a certain direction, and it emerges in the form of various organizational activities. By drawing on a sample of large-scale OSS ecosystems, the authors discuss that methods employed for taming are isomorphic, and overview the emerging strategic pattern for establishing systems of innovation. This pattern involves a related set of practices to balance virtues of OSS community while introducing corporate discipline. In contrast to approaches such as open innovation, which favor isolated reasoning, they present a systemic and historical perspective to explain the continuum in emergence and establishment of strategic patterns.

scholarly journals Prediction of Fault Fix Time Transition in Large-Scale Open Source Project Data

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 109
Author(s):  
Hironobu Sone ◽  
Yoshinobu Tamura ◽  
Shigeru Yamada
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Cost Reduction ◽  
Large Scale ◽  
Project Managers ◽  
Time Data ◽  
Software Reliability Growth Model ◽  
Software Reliability Growth ◽  
The Stability ◽  
Project Data

Open source software (OSS) programs are adopted as embedded systems regarding their server usage, due to their quick delivery, cost reduction, and standardization of systems. Many OSS programs are developed using the peculiar style known as the bazaar method, in which faults are detected and fixed by developers around the world, and the result is then reflected in the next release. Furthermore, the fix time of faults tends to be shorter as the development of the OSS progresses. However, several large-scale open source projects encounter the problem that fault fixing takes much time because the fault corrector cannot handle many fault reports. Therefore, OSS users and project managers need to know the stability degree of open source projects by determining the fault fix time. In this paper, we predict the transition of the fix time in large-scale open source projects. To make the prediction, we use the software reliability growth model based on the Wiener process considering that the fault fix time in open source projects changes depending on various factors such as the fault reporting time and the assignees to fix the faults. In addition, we discuss the assumption that fault fix time data depend on the prediction of the transition in fault fixing time.

scholarly journals cando.py: Open Source Software for Predictive Bioanalytics of Large Scale Drug–Protein–Disease Data

2020 ◽  
Vol 60 (9) ◽  
pp. 4131-4136
Author(s):  
William Mangione ◽  
Zackary Falls ◽  
Gaurav Chopra ◽  
Ram Samudrala
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale

scholarly journals Computational generation of an annotated gigalibrary of synthesizable, composite peptidic macrocycles

2020 ◽  
Vol 117 (40) ◽  
pp. 24679-24690
Author(s):  
Ishika Saha ◽  
Eric K. Dang ◽  
Dennis Svatunek ◽  
Kendall N. Houk ◽  
Patrick G. Harran
Keyword(s):  
Virtual Screening ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Three Dimensional ◽  
Pharmacological Properties ◽  
Robust Methods ◽  
Small Peptide ◽  
Multistep Reaction ◽  
Condensed Heterocycles

Peptidomimetic macrocycles have the potential to regulate challenging therapeutic targets. Structures of this type having precise shapes and drug-like character are particularly coveted, but are relatively difficult to synthesize. Our laboratory has developed robust methods that integrate small-peptide units into designed scaffolds. These methods create macrocycles and embed condensed heterocycles to diversify outcomes and improve pharmacological properties. The hypothetical scope of the methodology is vast and far outpaces the capacity of our experimental format. We now describe a computational rendering of our methodology that creates an in silico three-dimensional library of composite peptidic macrocycles. Our open-source platform, CPMG (Composite Peptide Macrocycle Generator), has algorithmically generated a library of 2,020,794,198 macrocycles that can result from the multistep reaction sequences we have developed. Structures are generated based on predicted site reactivity and filtered on the basis of physical and three-dimensional properties to identify maximally diverse compounds for prioritization. For conformational analyses, we also introduce ConfBuster++, an RDKit port of the open-source software ConfBuster, which allows facile integration with CPMG and ready parallelization for better scalability. Our approach deeply probes ligand space accessible via our synthetic methodology and provides a resource for large-scale virtual screening.

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