Open Source Python Simulation Software

The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. - CPU-compatible desktop build The standard desktop release requires AVX2. For older CPUs, the runtime-compatible variant can be found with the suffix "-rtcompat-".

PyAMS (Python for Analog and Mixed Signals) is used to simplify modeling analog elements and simulate electronic circuit The objectives of PyAMS is: - Drawing circuit by schematic (CAD approach); - Simulating the circuit; - Creating new symbols for models; - Creating new models of electrical elements by using Python language with pyams_lib; - Presenting simulation results in waveform or in probe; - PyAMS is developed with Python 3+, ElectronJS and NodeJs - Licensed under: PyAMS is free to use. GPLv3 . - Open source.

AirTSP is also named AirTSP (TSP standing for Travel Service Provider). That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline Schedule Management System. It is intended to be used in simulated environments only: it is not designed to work in the real-world of Airline IT operations. AirTSP/AirTSP makes an extensive use of existing open-source libraries for increased functionality, speed and accuracy. In particular the Boost (C++ Standard Extensions: http://www.boost.org) library is used. AirTSP/AirTSP is the one of the components of the Travel Market Simulator (http://www.travel-market-simulator). However, it may be used in a stand-alone mode.

That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline-related Inventory Management system. That library uses the Standard Airline IT C++ object model (http://sf.net/projects/stdair).

That project aims at providing a clean API, and the corresponding C++ implementation, for the basis of Airline IT Business Object Model (BOM), ie, to be used by several other Open Source projects, such as RMOL, Air-Sched, Travel-CCM, OpenTREP, etc.

experimaestro is an experiment manager, and is composed of (1) a job scheduler that handles dependencies and locking (2) a modular experiment description framework, that allows easy description of the various parts of an experiments.

The GNNPCSAFT Chat is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, you can chat with LLM models (Gemini or Ollama) with GNNPCSAFT tools, allowing you to ask questions about the PC-SAFT parameters of various compounds, predict thermodynamic properties, and get insights into the GNNPCSAFT's performance. - CPU-compatible desktop build The standard desktop release requires AVX2. For older CPUs, the runtime-compatible variant can be found with the suffix "-rtcompat-".

That project aims at delivering a reference implementation of a library, estimating and serving average prices paid for air travel products. It is not intended for use by an actual airline, but rather by simulators or other airline-related modules of

Create your own distributed computer that can distributed javascript based applications to any computer with a web browser, headless browser or node.js installation. For more information and updates please see our website - http://reorjs.com.

That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.

That project aims at studying the impact of IT systems interactions on traveller demand and airline revenues. Passenger demand is generated (Monte Carlo) and injected into simulated CRS and airline IT systems. Differential analysis is then performed on various changes compared to a bottom line scenario.