Speaker
Description
Dynamic Material Flow Analysis (MFA) is a cornerstone method in industrial ecology, enabling systematic, time-dependent tracking of materials through their life cycles and quantifying stock accumulation. The open-source tool ODYM has provided a generalized framework for custom MFA modelling, and is widely used in the community. flodym introduces a re-implementation with significantly enhanced capabilities in flexibility, usability, and performance.
Built on the principles of ODYM, flodym simplifies multi-dimensional array operations through the FlodymArray class, which automates dimension management and enables intuitive slicing, manipulation, and computation. This allows users to write cleaner, more adaptable code, minimizing errors and easing future modifications. The library tightly integrates multi-dimensional dynamic stock models – handling inflows, outflows, and stock values over arbitrary time steps – with the overall MFA structure, achieving both conceptual clarity and computational efficiency.
flodym leverages modern Python tools such as pandas for flexible data import/export and pydantic for robust data validation. It includes built-in visualization routines using Matplotlib and Plotly.
flodym is comprehensively documented, featuring how-tos, practical examples, and a complete API reference, making it easy to learn and use. Developed with modern software engineering best practices, it is structured for clarity, maintainability, and scalability. Contributions and collaborative enhancements are highly encouraged and warmly welcomed.
The presentation will begin with an introduction to the core tools provided by the flodym library, demonstrating how to construct and compute MFA systems, as well as how to effectively use FlodymArray objects. These demonstrations will draw on examples from the official documentation. The talk will conclude with a showcase of REMIND-MFA, a large-scale, open application built using flodym, highlighting the library’s capabilities in real-world research contexts.
| How much time do you ideally wish for your contribution? | 30 minutes |
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