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About

MPCPy is a Python package that facilitates the testing and implementation of occupant-integrated model predictive control (MPC) for building systems. The package focuses on the use of data-driven, simplified physical or statistical models to predict building performance and optimize control. Four main modules contain object classes to import data, interact with real or emulated systems, estimate and validate data-driven models, and optimize control input. While MPCPy provides an integration platform, it relies on free, open-source, third-party software packages for model implementation, simulators, parameter estimation algorithms, and optimization solvers. This includes Python packages for scripting and data manipulation as well as other more comprehensive software packages for specific purposes. In particular, modeling and optimization for physical systems currently rely on the Modelica language specification.

About

XPS, or eXtended Particle Simulations, is a state-of-the-art Discrete Element Method simulation software developed by RCPE and distributed globally by InSilicoTrials for high-fidelity particle-based process simulation. Designed specifically for pharmaceutical applications, XPS accurately predicts powder and granular behavior, helping teams better understand, predict, and control pharmaceutical unit operations. It relies on advanced contact models to describe the flow behavior of granular materials and uses massively parallel algorithms optimized for modern GPUs to accelerate simulations, including simulations with up to 100 million particles. XPS helps pharmaceutical engineers assess process configurations in unprecedented detail, explore decision space virtually, reduce costly and time-consuming physical experiments, and support data-driven process development.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Plants and companies requiring an open-source platform to improve their Model Predictive Control (MPC) in their buildings

Audience

Pharmaceutical process engineers and manufacturing R&D teams who need a DEM tool to simulate powder behavior and particle-based manufacturing processes

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MPCPy
United States
github.com/lbl-srg/MPCPy

Company Information

InSilicoTrials
Founded: 2016
United States
insilicotrials.com/xps/

Alternatives

Cybernetica CENIT

Cybernetica CENIT

Cybernetica

Alternatives

Aspherix

Aspherix

DCS Computing
LIGGGHTS

LIGGGHTS

CFDEM
COLUMBO

COLUMBO

PiControl Solutions
INCA MPC

INCA MPC

Inca Tools
AVEVA APC

AVEVA APC

AVEVA

Categories

Categories

Integrations

Python
Ubuntu

Integrations

Python
Ubuntu
Claim MPCPy and update features and information
Claim MPCPy and update features and information
Claim XPS (eXtended Particle Simulations) and update features and information
Claim XPS (eXtended Particle Simulations) and update features and information