AthenaVisual, Inc.

AthenaVisual, Inc.

State of the Art Technology Integrated for Process Modeling, Parameter Estimation, Model Discrimination and Optimal Design

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Testimonials

“Athena Visual Studio combines strong and efficient numerical solvers with straightforward syntax coding and GUI. This allows also non-experts to solve complex chemical engineering problems. I am a happy user of the package for both consultancy and teaching since almost 20 years.”

Rob Berger - Consultant in Catalysis & Reactor Engineering and Reaction Kinetics

"The Athena visual software is a powerful tool that allows our group estimate parameters for many different adsorption isotherm models and model the separation process of gas mixtures. With the user-friendly interface it is convenient to build models."

De-Li Chen (陈德利) - Associate Professor
Institute of Physical Chemistry
Zhejiang Normal University

Eighteen years ago, I started to use Athena for developing a sophisticated methodology of multi-parameter estimation for the characterization of the pore structure of catalyst carriers. Since then, Athena has been a valuable tool for our research concerning, among others, the migration of pollutants in subsurface and study of advanced methods of soil and groundwater remediation. It’s worth mentioning the extensive use of Athena for the multi-scale numerical simulation of multiphase transport and reactive processes in porous media, and inverse modeling of datasets from relevant laboratory experiments.

Christos Tsakiroglou, Ph.D. - Research Director

“Athena Visual Studio is an excellent tool for our PhD and MSc research and education for Food Technology students. It’s extremely versatile for estimation parameters of processes and (bio)chemical reactions related to food.”

Dr. ir. Matthijs Dekker - Associate Professor Food Quality and Design Group Department of Agrotechnology and Food Sciences

"We use Athena to derive fundamental models for complex gas-solid reactions from experimental data. The statistical analysis features are user-friendly and are a critical research tool for discriminating which models best describe the data."

Dante Simonetti, Ph. D. - Assistant Professor
Chemical & Biomolecular Engineering
UCLA


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