The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 16, 2023

Filed:

Aug. 30, 2019
Applicant:

Wentech Solutions Inc., Fredericton, CA;

Inventors:

Kenneth Blair Kent, Fredericton, CA;

Amir Allaf-Akbari, Fredericton, CA;

Konstantin Nasartschuk, Fredericton, CA;

Kevin John Shiell, Berwick, CA;

Farough Motasemi, Fredericton, CA;

Assignee:

WEnTech Solutions Inc., Fredericton, CA;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 30/20 (2020.01); G06F 30/27 (2020.01); C02F 11/04 (2006.01); C02F 3/28 (2006.01); G06N 3/126 (2023.01); G06N 20/00 (2019.01); G06N 3/086 (2023.01); G06F 119/02 (2020.01);
U.S. Cl.
CPC ...
G06F 30/20 (2020.01); C02F 3/28 (2013.01); G06F 30/27 (2020.01); G06N 3/086 (2013.01); G06N 3/126 (2013.01); G06N 20/00 (2019.01); C02F 11/04 (2013.01); G06F 2119/02 (2020.01);
Abstract

Systems and methods are described for performing at least one of assessing, optimizing and/or controlling the performance of an Anaerobic Digestion (AD) plant. The system comprises a server that provides a user interface for allowing a user to enter user inputs to define various aspects of the AD plant operation and to view results of the simulation; a database for storing the inputs used for the simulation of the anaerobic digestion plant, the inputs including feedstock inputs, AD operational inputs, and simulation criteria; and a simulation engine that can be operated in an at least one of an off-line simulation mode for generating off-line simulator predictions, a near-line simulation mode for optimizing the performance of the system and an online mode for using machine learning to tune the performance of various models used in simulating the operation of the AD plant.


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