Accepting PhD Students

20112019
If you made any changes in Pure these will be visible here soon.

Personal profile

Research interests

Measurements and Analytics for Petroleum and Chemical Industries

Oil and gas and other chemical process industries are constantly under pressure to minimise costs and environmental footprint. To achieve these objectives effective control and optimisation of the processes are required. Two key enabling technologies are needed to achieve effective control and optimisation. One is online measurement systems that provide continuous information on key physical and chemical attributes of the process streams. The second enabling technology is for the extraction of critical information from process measurements through the application of big data analytics and process modelling. These technologies are essential to develop reliable predictive models that effectively utilise the large amount of data that are typically collected in petroleum and chemical plants. Combining this databased approach with first-principles-based knowledge of process systems can potentially provide significantly improved predictive models.

The technologies we are developing have broad applications across the chemical and agricultural sectors.  We welcome enquiries from prospective industry and academic collaborators as well as from researchers interested in pursuing a Ph.D. within the following project areas.

 

Data Driven Process Analysis – Big Data Analytics

In many areas of engineering, the commercial availability of variety sensors based on different measurement techniques has increased due to them becoming progressively cheap and thus affordable. This has led to the collection of vast amounts of data. Most of these data are of disparate types. For example, in a chemical process data collected consists of a large number of qualitative and quantitative measurements taken at different time intervals. 

 

We are investigating cutting edge machine learning techniques for building process models to provide information on the current status of the process in terms of critical product attributes and also to predict the end point conditions so that timely corrective actions can be taken. The handling of disparate data types is also an active area of investigation in our group. We are investigating approaches based on Bayesian principles for combining data from different sources. The goal is to develop data and model fusion techniques that can be applied to upstream and downstream oil and gas processes.

 

Online monitoring of critical attributes of a process stream

We are engaged in the development of a measurement platform that can measure multiple chemical and physical properties of a process stream. Optical spectroscopy has been our main focus. We are developing a novel fibre-optic probe system that utilises Ultraviolet-Visible-Near Infrared spectroscopy. We are investigating a number of measurement configurations based on spatially and angularly resolved measurements that will enable the simultaneous determination of particle/droplet size and composition of process streams that are slurries or emulsions. The challenge of extracting the required information from these measurements is being investigated through a combination of machine learning techniques and fundamental light propagation models.

Fingerprint Dive into the research topics where Suresh Thennadil is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Particle size Chemical Compounds
Suspensions Chemical Compounds
Radiative transfer Chemical Compounds
Infrared radiation Chemical Compounds
optical properties Physics & Astronomy
Optical properties Chemical Compounds
Calibration Engineering & Materials Science
Reflectometers Chemical Compounds

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2011 2019

  • 10 Article
  • 7 Conference Paper published in Proceedings
  • 1 Abstract

Constrained kalman filtering: Improving fused information retention during constraining

Baker, F. & Thennadil, S., 1 Aug 2019, 2019 24th International Conference on Methods and Models in Automation and Robotics, MMAR 2019. IEEE, Institute of Electrical and Electronics Engineers, p. 434-437 4 p. 8864655. (2019 24th International Conference on Methods and Models in Automation and Robotics, MMAR 2019).

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in ProceedingsResearchpeer-review

Kalman Filtering
Extended Kalman filters
Pressure measurement
Estimate
Kalman Filter

Effect of Nickel on the Adhesion and Corrosion Ability of Pseudomonas aeruginosa on Stainless Steel

Tran Thi Thuy, T., Kannoorpatti, K., Padovan, A., Thennadil, S. & Nguyen Dang, N., Sep 2019, In : Journal of Materials Engineering and Performance. 28, 9, p. 5797-5805 9 p.

Research output: Contribution to journalArticleResearchpeer-review

Stainless Steel
Nickel
Bacteria
Adhesion
Stainless steel

Automated weighted outlier detection technique for multivariate data

Thennadil, S. N., Dewar, M., Herdsman, C., Nordon, A. & Becker, E., Jan 2018, In : Control Engineering Practice. 70, p. 40-49 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Outlier Detection
Multivariate Data
Multivariate Outliers
Mahalanobis Distance
Process Monitoring

Estimation of cattle age using visible-near-infrared scans of hides

Alvarenga, T. I. R. C., Palendeng, M., Hopkins, D., Fowler, S., McGilchrist, P. & Thennadil, S., 2018, International Congress of Meat Science and Technology. 2 p.

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in ProceedingsResearchpeer-review

Open Access
Infrared radiation

Estimation of meat tenderness using visible-near-infrared spectroscopy

Alvarenga, T. I. R. C., Palendeng, M., Hopkins, D., Fowler, S., McGilchrist, P. & Thennadil, S., 2018, International Conference on Meat Science and Technology. 2 p.

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in ProceedingsResearchpeer-review

Open Access
Near infrared spectroscopy
Meats

Thesis

Corrosion behaviour of high chromium white iron hardfacing alloys based on chromium carbides

Author: Marimuthu, V., 2016

Supervisor: Krishnan, K. (Supervisor), Thennadil, S. (Supervisor) & Singh, J. (Supervisor)

Student thesis: Masters by Research - CDU

File