(Non-)Steady State Kinetics Simulation

NSKinetics is a fast, flexible Python package for simulating steady- and non-steady-state reaction kinetics — including microbial fermentation and enzyme kinetics — and connecting them to techno-economic analysis (TEA) and life-cycle assessment (LCA) under uncertainty. Watch it run end to end in the interactive Quickstart demo below.

Quickstart

Kinetic models are declared as SBML — most easily authored as Antimony text — and wrapped in a KineticModel, which adds unit-aware value access and a Python event API (Event, and the higher-level FeedSpike for fed-batch feeding) over a Tellurium RoadRunner ODE engine. The same model can then drive a biosteam process unit through the NSKBatchReactor bridge — with ready-made flowsheet sections shipping as factories in nskinetics.processes — coupling kinetics directly to TEA.

One factory call builds a complete, industrially configured process around a real kinetic model: create_sugar_prep_and_fermentation_system assembles the sugar-solution preparation and fed-batch fermentation section of an actual biorefinery model — a splitter feeding parallel initial-feed and spike-feed conditioning trains (multi-effect evaporator, pumps, dilution-water mixer, heat exchanger), a FermentationSaccharomycesEthanolIsobutanol fermentor driven by the shipped S. cerevisiae kinetic model, and a compressed-air aeration loop. The interactive demo below runs it end to end: build, simulate, change the fed-batch strategy, and inspect the reactor.

Interactive quickstart demo — open in a new tab.

See the full tutorial for the rest of the workflow — writing and simulating a kinetic model from scratch, the Event/FeedSpike API used inside the fermentor here, a tour of the shipped S. cerevisiae kinetic model, and the kinetics-to-biosteam bridge behind V406.

Getting Started

Tutorials on NSKinetics

Tutorial

Key Concepts

The ideas behind NSKinetics

Key Concepts

API Reference

Detailed documentation

API Reference

Installation

Get the latest version of NSKinetics from PyPI. If you have an installation of Python with pip, simply install it with:

$ pip install nskinetics

To get the git version, use:

$ git clone git://github.com/sarangbhagwat/nskinetics

Or download directly from the GitHub page.

Common Issues

• Cannot install/update NSKinetics:

  If you are having trouble installing or updating NSKinetics, it may be due to dependency issues. You can bypass these using:

  $ pip install --user --ignore-installed nskinetics
  

  You can make sure you install the right version by including the version number:

  $ pip install nskinetics==<version>
  

  E.g., for version 0.1.4:

  $ pip install nskinetics==0.1.4