Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Introduction to MATLAB

Introduction to MATLAB

MATLAB stands for Matrix Laboratory. MathWorks developed MATLAB as a multi-paradigm numerical computing environment and proprietary programming language. It has evolved significantly over the years to become a tool utilized by engineers, scientists, and mathematicians for various tasks, including matrix calculations, developing algorithms, data analysis, and visualization. MATLAB's applications span various industries and disciplines. It's used in image and signal processing, communications,...

Multimachine Stability

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Strategic framework for sustainable centralisation of wastewater treatment plants: integrating economic and environmental analysis.

Bioresource technology·2026

Same author

Series of Molecularlike Doubly Excited States of a Quasi-Three-Body Coulomb System.

Physical review letters·2025

Same author

An ingestible capsule for luminance-based diagnosis of mesenteric ischemia.

Science robotics·2025

Same author

Modelling the longitudinal dynamics of paranoia in psychosis: A temporal network analysis over 20 years.

Schizophrenia research·2024

Same author

City-wide model-based analysis of heat recovery from wastewater using an uncertainty-based approach.

The Science of the total environment·2022

Same author

Modelling temperature dynamics in sewer systems - comparing mechanistic and conceptual modelling approaches.

Water science and technology : a journal of the International Association on Water Pollution Research·2021

Search research articles

Related Experiment Video

Updated: Jul 19, 2026

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

Implementing ADM1 for plant-wide benchmark simulations in Matlab/Simulink.

C Rosen¹, D Vrecko, K V Gernaey

¹Department of Industrial Electrical Engineering and Automation, Lund University, Sweden. christian.rosen@iea.lth.se

Water Science and Technology : a Journal of the International Association on Water Pollution Research

|October 14, 2006

Summary

Implementing the complex IWA Anaerobic Digestion Model No.1 (ADM1) in dynamic simulations is feasible. Proper implementation ensures high-quality results for plant-wide systems without significant computational burden.

More Related Videos

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

Related Experiment Videos

Last Updated: Jul 19, 2026

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

Area of Science:

Environmental Engineering
Biochemical Engineering
Process Systems Engineering

Background:

The IWA Anaerobic Digestion Model No.1 (ADM1) is a state-of-the-art model for anaerobic digestion processes.
Its complexity presents challenges for implementation in dynamic simulations, especially for plant-wide or integrated systems.

Purpose of the Study:

To present experiences from implementing the ADM1 model in Matlab/Simulink within the Benchmark Simulation Model 2 (BSM2).
To discuss computational aspects crucial for successful dynamic simulations using ADM1.

Main Methods:

Implementation of ADM1 within the extended COST/IWA Benchmark Simulation Model (BSM2) using Matlab/Simulink.
Analysis of system stiffness, model interfacing, mass balances, acid-base equilibrium, and algebraic solvers.
Evaluation of numerical solvers and simulation time.

Main Results:

Successful integration of ADM1 into dynamic plant-wide simulations is demonstrated.
Computational challenges including system stiffness and pH variable handling were addressed.
The implementation allows for simulations including noise and discrete sub-systems.

Conclusions:

The ADM1 can be effectively implemented for high-quality dynamic plant-wide simulations.
Proper implementation mitigates extensive computational efforts, making ADM1 viable for complex systems.
The study provides practical insights for researchers and engineers working with ADM1.