Tests	Documentation	Coverage	Paper

RHEOS, an abbreviation of Rheology Open Source, is a software package written in the Julia programming language that provides tools for analyzing rheological data. Features include:

• Stress/Strain/Time data can be easily be fitted to a viscoelastic model

• Complex modulus G'/G''/Frequency data can easily be fitted to a viscoelastic model

• Many standard and fractional viscoelastic models have already been implemented within RHEOS new ones can easily be added by users

• A fitted model can be used to predict the behaviour of the material under other loading conditions, enabling the fit/predict paradigm of model selection

• Artificial loading conditions can be generated within RHEOS to better understand a model's response

You can try out RHEOS interactively in your browser using Binder:

A large majority of scientists and engineers who undertake rheological experiments fit their data with one or several viscoelastic models in order to classify materials, quantify their behaviour and predict their response to external perturbations.

Obtaining intuition for fractional viscoelastic theory can be difficult and learning material is sparse. Tools are needed to support researchers with their exploration of standard and advanced models and how they behave in response to idealised loading conditions, in particular when analytical expressions are difficult to obtain.

Because understanding of materials is often dependent on summarising their behaviour with a model, one must be able to test and compare a broad range of models to inform model selection and reliably identify material parameters. There are currently very limited options available in the public domain, and most research groups have to invest significant effort developing custom software. An open-source standardised library of models and fitting algorithms would support the rheology research community and make analysis more systematic, transparent and reproducible.

RHEOS addresses the issues outlined in the Statement of Need in several ways.

• As well as being able to fit and predict assuming step loading of stress or strain, RHEOS can handle arbitrary loading for non-singular and singular models, and for constant or variable sample rates.

• RHEOS includes an extensive library of both traditional and fractional viscoelastic models. Although this library will satisfy most users, it is also straightforward to add additional models to RHEOS should they need to.

• For intuition-building and model exploration, RHEOS includes signal generation features so that common loading patterns (e.g. step, ramp, stairs) can be applied to unfamiliar models.

• As a convenience to the user, RHEOS also includes easy-to-use CSV importing and exporting functions, as well as a number of preprocessing functions for resampling and smoothing.

All of the above features are linked together in a seamless interface intended to be very approachable for less experienced programmers. The different paradigms of creep, relaxation and oscillatory testing are all accounted for, and models fitted against one type of data can be used to predict against a different type of data. (For instance, fitting against relaxation data and predicting the frequency response spectrum.)

1. Install the latest version of Julia
2. From Julia interactive command-line REPL, enter pkg mode by pressing ]
3. (Optional) Enable desired Project.toml environment
4. Run the command add RHEOS

If you installed RHEOS using the instructions above then you will have the latest stable release of RHEOS; to access the documentation for this version click here or the blue docs/stable badge at the top of this README page. To access the latest documentation built directly from the master branch click here or the blue docs/dev badge at the top of this README page.

The documentation contains numerous examples of how to use RHEOS for common use cases. Each example can be explored interactively, without even downloading Julia or RHEOS, by clicking on the 'launch binder' button at the top of examples pages. Note that whenever you restart your Julia session you will have to reload RHEOS by typing using RHEOS to follow along with the examples in the documentation. To avoid repetition this line is not included in every piece of example code. For comprehensive descriptions of RHEOS types and functions, see the API section of the documentation. Any plotting library can be used but the tutorials within the documentation use the PyPlot Julia package. For corrections or clarifications to the documentation, please note the 'Contributing to RHEOS' section below and create an issue on the GitHub repository.

If you use RHEOS in your work, please consider citing the following papers as appropriate:

• J. L. Kaplan, A. Bonfanti, A. J. Kabla (2019). RHEOS.jl -- A Julia Package for Rheology Data Analysis. Journal of Open Source Software, 4(41), 1700, https://doi.org/10.21105/joss.01700

• A. Bonfanti, J. L. Kaplan, G. Charras, A. J. Kabla (2020). Fractional viscoelastic models for power-law materials. Soft Matter, 16, 6002-6020, https://doi.org/10.1039/D0SM00354A

If you believe you have found any bugs or invalid behaviour in RHEOS, please feel free to file an issue on this repository. You can also raise an issue if you feel that any part of the documentation needs clarification, or for any feature requests. Even better than just raising an issue, you could both raise an issue and issue a pull request which fixes that issue.

We generally work using a greatly simplified version of 'git flow'. Small changes and fixes are directly committed or PR'ed in to the master branch, as longs as tests pass. Larger developments are generally made in feature branches and then merged to master via a pull request, once tests are passing. Stable releases are tagged and sent to the Julia central package repository via JuliaRegistrator and TagBot.

Note that meta-documentation on running tests and building documentation locally is available at the JuliaRheology/RheoHelpDocs repository. Please be aware that RHEOS is released with a 'Contributor Code of Conduct' (CONDUCT.md) and by participating in this project you agree to abide by its terms.

• W. N. Findley, J. S. Lai, K. Onaran (1989). Creep and Relaxation of Nonlinear Viscoelastic Materials (with an Introduction to Linear Viscoelasticity), Dover Publications, New York.

• S. G. Johnson. The NLopt nonlinear-optimization package, https://github.com/stevengj/nlopt

• J. Bezanson, A. Edelman, S. Karpinski, V. B. Shah (2017). Julia: A Fresh Approach to Numerical Computing, SIAM Review, doi: 10.1137/141000671.

EditURL = "https://github.com/JuliaRheology/RHEOS.jl"