tag:joss.theoj.org,2005:/papers/tagged/uncertainty?page=2Journal of Open Source Software2022-07-05T13:03:35ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/33202022-07-05T13:03:35Z2022-07-06T00:01:01ZRHEIA: Robust design optimization of renewable Hydrogen and dErIved energy cArrier systemsacceptedv1.0.02022-02-03 12:59:31 UTC752022-07-05 13:03:35 UTC720224370DiederikCoppittersInstitute of Mechanics, Materials and Civil Engineering, Université catholique de Louvain, Fluid and Thermal Dynamics, Vrije Universiteit Brussel0000-0001-9480-2781PanagiotisTsirikoglouLimmat Scientific AGWardDe PaepeThermal Engineering and Combustion Unit, University of Mons0000-0001-5008-2946KonstantinosKyprianidisDepartment of Automation in Energy and Environment, School of Business, Society and Engineering, Malardalen University0000-0002-8466-356XAnestisKalfasDepartment of Mechanical Engineering, Aristotle University of Thessaloniki0000-0002-0025-9392FrancescoContinoInstitute of Mechanics, Materials and Civil Engineering, Université catholique de Louvain0000-0002-8341-435010.21105/joss.04370https://doi.org/10.5281/zenodo.6782705Pythonhttps://joss.theoj.org/papers/10.21105/joss.04370.pdfhydrogen-based systems, robust design optimization, uncertainty quantificationtag:joss.theoj.org,2005:Paper/24322021-12-09T17:58:26Z2021-12-10T00:02:12ZMUQ: The MIT Uncertainty Quantification Libraryacceptedv0.3.22021-02-26 17:04:54 UTC682021-12-09 17:58:26 UTC620213076MatthewParnoDepartment of Mathematics, Dartmouth College, Hanover, NH USA0000-0002-9419-2693AndrewDavisCourant Institute of Mathematical Sciences, New York University, New York, NY USA0000-0002-6023-0989LinusSeelingerInstitute for Scientific Computing, Heidelberg University, Heidelberg, Germany0000-0001-8632-849310.21105/joss.03076https://doi.org/10.5281/zenodo.5770267C++, Objective-Chttps://joss.theoj.org/papers/10.21105/joss.03076.pdfPython, Bayesian Inference, Inverse Problems, Uncertainty Quantificationtag:joss.theoj.org,2005:Paper/26972021-11-21T18:30:33Z2021-11-22T00:01:47Zogs6py and VTUinterface: streamlining OpenGeoSys workflows in Pythonacceptedv0.312021-05-31 10:02:05 UTC672021-11-21 18:30:33 UTC620213673JörgBuchwaldHelmholtz Center for Environmental Research - UFZ, Leipzig, Germany, Technische Universität Bergakademie Freiberg, Germany0000-0001-5174-3603OlafKolditzHelmholtz Center for Environmental Research - UFZ, Leipzig, Germany, Technische Universität Dresden, Germany, TUBAF-UFZ Center for Environmental Geosciences, Germany0000-0002-8098-4905ThomasNagelTechnische Universität Bergakademie Freiberg, Germany, TUBAF-UFZ Center for Environmental Geosciences, Germany0000-0001-8459-461610.21105/joss.03673https://doi.org/10.5281/zenodo.5705727Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.03673.pdfPython, physics, THMC, VTU, time-series, sensitivity analysis, uncertainty quantification, OpenGeoSystag:joss.theoj.org,2005:Paper/24852021-10-28T17:50:32Z2021-10-31T11:00:31ZQlunc: Quantification of lidar uncertaintyacceptedv0912021-03-12 11:46:34 UTC662021-10-28 17:50:32 UTC620213211FranciscoCostaStuttgart Wind Energy (SWE), Allmandring 5b, 70569 Stuttgart, Germany0000-0003-1318-9677AndrewCliftonStuttgart Wind Energy (SWE), Allmandring 5b, 70569 Stuttgart, Germany0000-0001-9698-5083NikolaVasiljevicDTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde Denmark0000-0002-9381-9693InesWürthStuttgart Wind Energy (SWE), Allmandring 5b, 70569 Stuttgart, Germany0000-0002-1365-024310.21105/joss.03211https://doi.org/10.5281/zenodo.5592248Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.03211.pdfwind lidar, lidar hardware uncertainty, OpenScience, OpenLidar, digital twintag:joss.theoj.org,2005:Paper/28372021-08-31T16:05:50Z2021-12-08T13:31:16ZNoisySignalIntegration.jl: A Julia package for uncertainty evaluation of numeric integralsacceptedv0.2.12021-07-08 08:45:42 UTC642021-08-31 16:05:50 UTC620213526NilsO. b.LüttschwagerGeorg-August-University Göttingen, Institute of Physical Chemistry, Tammannstraße 6, DE-37077 Göttingen0000-0001-8459-171410.21105/joss.03526https://doi.org/10.5281/zenodo.5338743Juliahttps://joss.theoj.org/papers/10.21105/joss.03526.pdfchemistry, physics, measurement uncertainty, noisy data, numeric integrationtag:joss.theoj.org,2005:Paper/20472021-05-13T13:24:09Z2021-05-20T20:10:30ZParaMonte: A high-performance serial/parallel Monte Carlo simulation library for C, C++, Fortranacceptedv1.2.02020-09-29 21:20:03 UTC612021-05-13 13:24:09 UTC620212741AmirShahmoradiDepartment of Physics, The University of Texas, Arlington, TX, Data Science Program, The University of Texas, Arlington, TX0000-0002-9720-8937FatemehBagheriDepartment of Physics, The University of Texas, Arlington, TX10.21105/joss.02741https://doi.org/10.5281/zenodo.4749957Python, Fortranhttps://joss.theoj.org/papers/10.21105/joss.02741.pdfC, C++, Monte Carlo, Markov Chain Monte Carlo, Uncertainty Quantification, Metropolis-Hastings, adaptive sampling, MCMC, DRAMtag:joss.theoj.org,2005:Paper/21512021-04-20T17:37:58Z2021-04-21T00:01:12ZUQit: A Python package for uncertainty quantification (UQ) in computational fluid dynamics (CFD)acceptedv1.0.22020-11-09 21:35:13 UTC602021-04-20 17:37:58 UTC620212871SalehRezaeiraveshSimEx/FLOW, Engineering Mechanics, KTH Royal Institute of Technology,, Swedish e-Science Research Centre (SeRC), Stockholm, Sweden0000-0002-9610-9910RicardoVinuesaSimEx/FLOW, Engineering Mechanics, KTH Royal Institute of Technology,, Swedish e-Science Research Centre (SeRC), Stockholm, SwedenPhilippSchlatterSimEx/FLOW, Engineering Mechanics, KTH Royal Institute of Technology,, Swedish e-Science Research Centre (SeRC), Stockholm, Sweden10.21105/joss.02871https://doi.org/10.5281/zenodo.4704355Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.02871.pdfuncertainty quantification (UQ), computational fluid dynamics (CFD)tag:joss.theoj.org,2005:Paper/17102021-03-05T14:56:46Z2021-03-06T00:00:27ZVizumap: an R package for visualising uncertainty in spatial dataacceptedv1.2.02020-06-05 02:29:54 UTC592021-03-05 14:56:46 UTC620212409LydiaR.LucchesiAustralian National University, Canberra, Australia, CSIRO Data61, Canberra, AustraliaPetraM.KuhnertCSIRO Data61, Canberra, AustraliaChristopherK.WikleUniversity of Missouri, Columbia, USA10.21105/joss.02409https://doi.org/10.5281/zenodo.4554558Rhttps://joss.theoj.org/papers/10.21105/joss.02409.pdfspatial statistics, visualisation, uncertainty, mapstag:joss.theoj.org,2005:Paper/18292020-07-28T15:13:35Z2021-02-15T11:30:21ZGrama: A Grammar of Model Analysisacceptedv0.1.32020-07-05 19:36:14 UTC512020-07-28 15:13:35 UTC520202462Zacharydel RosarioVisiting Professor, Olin College of Engineering0000-0003-4676-169210.21105/joss.02462https://doi.org/10.6084/m9.figshare.12725066.v1Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.02462.pdfModeling, Uncertainty quantification, Functional programming, Pedagogy, Communication, Reproducibilitytag:joss.theoj.org,2005:Paper/11632019-11-01T14:18:49Z2021-02-15T11:31:46ZUncertainData.jl: a Julia package for working with measurements and datasets with uncertainties.acceptedv0.2.12019-08-15 22:05:32 UTC432019-11-01 14:18:49 UTC420191666KristianAgasøsterHaagaDepartment of Earth Science, University of Bergen, Bergen, Norway, K. G. Jebsen Centre for Deep Sea Research, Bergen, Norway, Bjerknes Centre for Climate Research, Bergen, Norway0000-0001-6880-872510.21105/joss.01666https://doi.org/10.5281/zenodo.3522252Juliahttps://joss.theoj.org/papers/10.21105/joss.01666.pdfuncertainty, measurements