Cyber-Physical Systems

Linked Data

Chemical engineering and engineering in general is changing rapidly in the 21st century. The Internet of Things and its industrial equivalent Industry 4.0 are notions frequently used to describe this change. We are applying and developing new techniques in the area of Artificial Intelligence, Semantic Web, Machine Learning, Big Data, Blockchain technology, and Statistics to create a cyber-physical system offering new ways to solve classical engineering problems like process optimisation, reduction of CO2, implementation of Smart Grid, and many others.

Smart Grid

The cyber-physical system we are currently developing is called J-Park Simulator (JPS) which is the signature project in the C4T programme of CARES at the University of Cambridge. The JPS consists of a network of IRIs comprising domain ontologies, a knowledge base and different types of agents. One important application is the modelling and optimisation of eco-industrial parks. This includes the electrical grid, various networks of materials, for example, waste heat network along with a detailed model of each industrial process.

Associated Preprints

197: Learning based Evolutionary Assistive Paradigm for Surrogate Selection (LEAPS2)

ref: Technical Report 197, c4e-Preprint Series, Cambridge, 2018 by Sushant S. Garud, Iftekhar A. Karimi, and Markus Kraft

189: An ontology framework for information modeling and management of eco-industrial parks

ref: Technical Report 189, c4e-Preprint Series, Cambridge, 2017 by Li Zhou, Chuan Zhang, Iftekhar A. Karimi, and Markus Kraft

185: Evaluating Smart Sampling for Constructing Multidimensional Surrogate Models

ref: Technical Report 185, c4e-Preprint Series, Cambridge, 2017 by Sushant S. Garud, Iftekhar A. Karimi, George Brownbridge, and Markus Kraft

184: Machine learning approach for constructing surrogates of a biodiesel plant flow sheet model

ref: Technical Report 184, c4e-Preprint Series, Cambridge, 2017 by Xueheng Qiu, Janusz Sikorski, Sushant S. Garud, Ponnuthurai Nagaratnam Suganthan, and Markus Kraft

182: Design of Computer Experiments: A Review

ref: Technical Report 182, c4e-Preprint Series, Cambridge, 2017 by Sushant Garud, Iftekhar A. Karimi, and Markus Kraft

178: Blockchain technology in the chemical industry: machine-to-machine electricity market

ref: Technical Report 178, c4e-Preprint Series, Cambridge, 2016 by Janusz Sikorski, Joy Haughton, and Markus Kraft

174: J-Park Simulator: Roadmap to Smart Eco-Industrial Parks

ref: Technical Report 174, c4e-Preprint Series, Cambridge, 2016 by Martin J Kleinelanghorst, Li Zhou, Janusz Sikorski, Eddy Foo Yi Shyh, Kevin Aditya, Sebastian Mosbach, Iftekhar Karimi, Raymond Lau, Sushant Garud, Chuan Zhang, Ming Pan, Joymala Moirangthem, Yuhao Sun, Pulkit Chhabra, Khamila Nurul, Daryl Yong, Yi Ren Sng, Gehan Amaratunga, Jan Maciejowski, Hadinoto Ong, Sanjib Panda, and Markus Kraft

171: A Big Data Framework to Validate Thermodynamic Data for Chemical Species

ref: Technical Report 171, c4e-Preprint Series, Cambridge, 2016 by Philipp Buerger, Jethro Akroyd, Jacob W. Martin, and Markus Kraft

166: On the parameterisation of process flow sheet models

ref: Technical Report 166, c4e-Preprint Series, Cambridge, 2016 by Janusz Sikorski, George Brownbridge, Sushant S. Garud, Sebastian Mosbach, Iftekar A. Karimi, and Markus Kraft

164: Design technologies for eco-industrial parks: from unit operations to processes, plants and industrial networks

ref: Technical Report 164, c4e-Preprint Series, Cambridge, 2016 by Ming Pan, Janusz Sikorski, Jethro Akroyd, Sebastian Mosbach, R. Lau, and Markus Kraft

162: Outlier analysis for a silicon nanoparticle population balance model

ref: Technical Report 162, c4e-Preprint Series, Cambridge, 2015 by Sebastian Mosbach, William J. Menz, and Markus Kraft

150: Applying Industry 4.0 to the Jurong Island Eco-industrial Park

ref: Technical Report 150, c4e-Preprint Series, Cambridge, 2014 by Ming Pan, Janusz Sikorski, Catharine A Kastner, Jethro Akroyd, Sebastian Mosbach, R. Lau, and Markus Kraft

138: Influence of experimental observations on n-propylbenzene kinetic parameter estimates

ref: Technical Report 138, c4e-Preprint Series, Cambridge, 2013 by Sebastian Mosbach and Markus Kraft

133: Bayesian Error Propagation for a Kinetic Model of n-Propylbenzene Oxidation in a Shock Tube

ref: Technical Report 133, c4e-Preprint Series, Cambridge, 2013 by Sebastian Mosbach, Je Hyeong Hong, George Brownbridge, Markus Kraft, S. Gudiyella, and K. Brezinsky

117: The Semantics of Chemical Markup Language (CML) for Computational Chemistry: CompChem

ref: Technical Report 117, c4e-Preprint Series, Cambridge, 2012 by Weerapong Phadungsukanan, Markus Kraft, Joe Townsend, and Peter Murray-Rust

104: Iterative improvement of Bayesian parameter estimates for an engine model by means of experimental design

ref: Technical Report 104, c4e-Preprint Series, Cambridge, 2011 by Sebastian Mosbach, Andreas Braumann, Peter L.W. Man, Catharine A Kastner, George Brownbridge, and Markus Kraft

84: The future of computational modelling in reaction engineering

ref: Technical Report 84, c4e-Preprint Series, Cambridge, 2009 by Markus Kraft and Sebastian Mosbach

82: Resolving conflicting parameter estimates in multivariate population balance models

ref: Technical Report 82, c4e-Preprint Series, Cambridge, 2009 by Peter L.W. Man, Andreas Braumann, and Markus Kraft

66: Incorporating experimental uncertainties into multivariate granulation modelling

ref: Technical Report 66, c4e-Preprint Series, Cambridge, 2009 by Andreas Braumann and Markus Kraft

56: Applying response surface methodology to multidimensional granulation modelling

ref: Technical Report 56, c4e-Preprint Series, Cambridge, 2008 by Andreas Braumann, Markus Kraft, and Paul R. Mort

Associated Publications

Incorporating seller/buyer reputation-based system in blockchain-enabled emission trading application,

Khamila Nurul Khaqqi, Janusz Sikorski, Kunn Hadinoto, and Markus Kraft, Applied Energy 209, 8-19, (2018)

Evaluating smart sampling for constructing multidimensional surrogate models,

Sushant S. Garud, Iftekhar A. Karimi, George Brownbridge, and Markus Kraft, Computers and Chemical Engineering 108, 276-288, (2018)

Design of Computer Experiments: A Review,

Sushant Garud, Iftekhar A. Karimi, and Markus Kraft, Computers and Chemical Engineering 106, 71-95, (2017)

Blockchain technology in the chemical industry: Machine-to-machine electricity market,

Janusz Sikorski, Joy Haughton, and Markus Kraft, Applied Energy 195, 234-246, (2017)

A big data framework to validate thermodynamic data for chemical species,

Philipp Buerger, Jethro Akroyd, Jacob W. Martin, and Markus Kraft, Combustion and Flame 176, 584-591, (2017)

Parameterisation of a biodiesel plant process flow sheet model,

Janusz Sikorski, George Brownbridge, Sushant S. Garud, Sebastian Mosbach, Iftekar A. Karimi, and Markus Kraft, Computers and Chemical Engineering 95, 108-122, (2016)

Design technologies for eco-industrial parks: from unit operations to processes, plants and industrial networks,

Ming Pan, Janusz Sikorski, Jethro Akroyd, Sebastian Mosbach, R. Lau, and Markus Kraft, Applied Energy 175, 305-323, (2016)

Outlier analysis for a silicon nanoparticle population balance model,

Sebastian Mosbach, William J. Menz, and Markus Kraft, Combustion and Flame 177, 89-97, (2017)

Applying Industry 4.0 to the Jurong Island Eco-industrial Park,

Ming Pan, Janusz Sikorski, Catharine A Kastner, Jethro Akroyd, Sebastian Mosbach, Raymond Lau, and Markus Kraft, Energy Procedia 75, 1536-1541, (2015)

Influence of experimental observations on n-propylbenzene kinetic parameter estimates,

Sebastian Mosbach and Markus Kraft, Proceedings of the Combustion Institute 35, 357-365, (2015)

Bayesian Error Propagation for a Kinetic Model of n-Propylbenzene Oxidation in a Shock Tube,

Sebastian Mosbach, Je Hyeong Hong, George Brownbridge, Markus Kraft, S. Gudiyella, and K. Brezinsky, International Journal of Chemical Kinetics 46, (7), 389-404, (2014)

The semantics of Chemical Markup Language (CML) for computational chemistry: CompChem,

Weerapong Phadungsukanan, Markus Kraft, Joe Townsend, and Peter Murray-Rust, Journal of Cheminformatics 4, 15, (2012)

Iterative improvement of Bayesian parameter estimates for an engine model by means of experimental design,

Sebastian Mosbach, Andreas Braumann, Peter L.W. Man, Catharine A Kastner, George Brownbridge, and Markus Kraft, Combustion and Flame 159, 1303-1313, (2012)

The future of computational modelling in reaction engineering,

Markus Kraft and Sebastian Mosbach, Philosophical Transactions 368, 3633-3644, (2010)

Resolving conflicting parameter estimates in multivariate population balance models,

Peter L.W. Man, Andreas Braumann, and Markus Kraft, Chemical Engineering Science 65, 4038-4045, (2010)

Incorporating experimental uncertainties into multivariate granulation modelling,

Andreas Braumann and Markus Kraft, Chemical Engineering Science 65, 1088-1100, (2010)

Parameter estimation in a multidimensional granulation model,

Andreas Braumann, Markus Kraft, and Paul Mort, Powder Technology 197, 196-210, (2010)

Funding

This research is supported by the National Research Foundation (NRF), Prime Minister's Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.