Dr Peter Brady is an associate of the UTS Faculty of Engineering and IT, who received his PhD from UTS in 2011, in Computational Fluid Dynamics of turbulent free surface flows. In particular the work outlined in the thesis developed a new low order solver for the simulation of turbulent free surface flows. During the simulations and experimental investigations, in addition to the development of the code, a number of new physical phenomena were discovered, which are the subject of extended investigations.
Dr Brady received his Bachelor of Engineering in Civil Engineering in 2002 from UTS.
Dr Brady is currently a Senior Engineer with Pacific ESI and is actively collaborating with Associate Professor James Ball on a number of research projects and grants. These include:
- Computational Fluid Dynamics simulations
- Smoothed Particle Hydrodynamics simulations
- Empirical mode decomposition investigations of biological signals of Berowra Creek
- Australian Rainfall and Runoff Revision Project 3: Temporal Patterns
Prior to starting his PhD Dr Brady had worked across the civil engineering water engineering field in areas as diverse as a flood mitigation consultant and simulation specialist; a local government hydraulic engineer and a development consultant.
Journals that Dr Brady has reviewed papers for:
- Australian Journal of Water Resources
- Water Science and Technology
Dr Brady is actively involved in the Engineers Australia and has been a member of the organising committee of the Sydney Division Water Engineering Panel for nearly 10 years.
Fluid Mechanics and Computational Fluid Dynamics
- CFD simulations of turbulent free surface flows with and without surface penetrating objects.
- Fluid flow and heat transfer
- Micro CFD and nano-fluidics with molecular dynamics and meso-scale dynamics simulations
- Smoothed Particle Hydrodynamcis of free surface flows
Grid and HPC
- License management and optimisation
- Distributed data management and updates in live cluster and cloud environments
Dr Brady is currently teaching, or has taught in the following areas:
- Introduction to Programming for Civil and Mechatronic Engineers
- Fluid Mechanics
- Hydraulics and Hydrology
Post Graduate Level:
- Computational Fluid Dynamics
Burrowes, P & Brady, P 2006, 'Emisesion control', Water Environment and Technology, vol. 18, no. 3, pp. 40-41.
LaMontagne, P & Brady, P 2004, 'Dewatering made easy', Water Environment and Technology, vol. 16, no. 1, pp. 58-63.
The significance of automation of dewatering processes for wastewater treatment facilities is discussed. Dewatering solids require polymer and, if the feed solids and polymer entering the dewatering unit were constant, there would be little need for automatic control. Feed flowmeters and feed density meters helps to measure a change in solids loading and change the polymer rate to maintain polymer dosage, increasing the belt speed for a filter or increasing the differential speed for the centrifuge. Feed-back control determines the error in the output of the dewatering system and calculates a change in the system to correct the error.
Rowan, J, Heitz, M & Brady, P 2003, 'Thermal processing biosolids, bioenergy, or hot air?', Water Environment and Technology, vol. 15, no. 1, pp. 41-43.
Various advantages of using thermal processing technologies to treat digested wastewater solids are discussed. The processing use heat or elevated temperature to produce Class A biosolids, biofuel or bioenergy from wastewater solids. Thermal processing technologies has the ability to operate around the clock in limited space without concern for weather, storage requirements, or odors. The processing can also be used for biosolids that are easier to handle and use because of its better size, shape, dryness and other physical characteristics.
Pramanik, A, LaMontagne, P & Brady, P 2002, 'Automatic improvements', Water Environment and Technology, vol. 14, no. 10, pp. 46-50.
The installation of an integrated control system, which can improve sludge dewatering performance and cut costs, is discussed. The best candidates for fully automatic dewatering systems are treatment facilities whose sludge varies little from day to day. Fully automating a dewatering system involves controlling several process variables: feeds solids, polymer, centrifuge or belt press performance and effluent solids. Water Environment Research Foundation (WERF) researchers tested seven treatment plants and found that even limited automation reduced polymer consumption by an average of 16%.
Podger, S, Babister, M & Brady, P 2016, 'Deriving temporal patterns for areal rainfall bursts', 37th Hydrology and Water Resources Symposium 2016: Water, Infrastructure and the Environment, HWRS 2016.
© 2017 Engineers Australia. All Rights Reserved. Areal temporal patterns have been derived for the update of Australian Rainfall and Runoff (ARR) 2016 as part of Project 3: Temporal Patterns of Rainfall. These patterns have been developed for a range of Annual Exceedance Probabilities (AEP), durations and catchment areas. This paper outlines the method of extracting these patterns, including shapes and rotations of the catchment area to achieve the rarest areal pattern. The selection of areal patterns for recommended use is also discussed, including limitations and issues encountered. Testing of the patterns has been undertaken on the Hawkesbury-Nepean catchment and a set of hydrological models.
Brady, PDM & Ball, JE 2015, 'Parallel And Distributed Swmm For Individual Computation In A Genetic Algorithm', E-proceedings of the 36th IAHR World Congress, Congress of IAHR, the International Association of Hydro-Environment Engineering and Research, IAHR, The Hague, Netherlands.
Genetic Algorithms have already been successfully applied to the optimization of catchment parameters within hydrologic systems. However, as with all genetic algorithms significant computational effort is required to compute the fitness of the individuals within the population. We present a two stage computational scale out methodology to take the singly threaded Storm Water Management Model (version 4.4). Firstly, we develop an OpenMP based programme to run SWMM in parallel on a single, multi-core computer. With this wrapper we achieved linear speed up to three cores, which peaked at a 5.5 times speed up on 12 core machine. Secondly we implement a distributed methodology to deploy the multi-core programme across a cluster of shared workstations using the BOINC middleware. With this middleware in place were able scavenge 20-30% of the computational resources of a 100+ node cluster with over 1000 cores. These dual scale out methods allowed us to significantly reduce our computational runtimes and while simultaneously increasing both the parameter space to search and the size of the population of individuals.
Brady, PDM & Ball, JE 2015, 'Parallel and distributed computation in design flood estimation', The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015, Hydrology and Water Resources Symposium and the International Conference on Water Resources and Environment Research, Engineers Australia, Hobart, Australia, pp. 1538-1544.
© 2015, Engineers Australia. All rights reserved.Reliable and efficient design flood estimation remains a concern for many catchment managers. The search for reliable and efficient approaches to design flood estimation together with the increased computational capacity available to analysts has resulted in the development of computationally intensive methods for design flood estimation; for example, the application of a Genetic Algorithm for calibration of a catchment modeling system and the use of a Monte Carlo technique for generation of a POT series requires multiple executions of the catchment modeling system. As the execution of a given simulation is entirely separate from others, the computation step in the method is embarrassingly parallel. The key step to reduce computational run times, therefore, is to efficiently distribute, compute and gather the results amongst a cluster of computers or processing cores. Within this paper we present two methods of efficiently distributing the individuals such that they are computed in parallel. The example application is the use of a Genetic Algorithm for calibration of SWMM applied to an urban catchment. The first method is based on the recognition that SWMM 4.4 is a single threaded application. We can, therefore, place a wrapper that is multi-threaded in front of the SWMM execution step and compute the population in parallel on a multi-core machine. With this wrapper we achieved linear speed up to three cores, which peaked at a 5.5 times speed up on 12 core machine. The second method builds on the first and is based on the BOINC framework. Implementing a distributed methodology to deploy the multi-core programme across a cluster of shared workstations using the BOINC middleware, we were able scavenge 20-30% of the computational resources of a 100+ node cluster with over 1000 cores.
Babister, M, Brady, PDM, Retallick, M & Ball, J 2015, 'Is ARR 2015 a watershed moment for how we manage hydrologic data?', The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015, pp. 17-23.
© 2015, Engineers Australia. All rights reserved. As network speeds have increased, online delivery of data has the potential to revolutionise the hydrologic industry not only in Australia but worldwide, for example the recent ARR Revision Projects on regional flood frequency estimation and the interaction of coastal and riverine flooding. There are a number of distinct advantages to centralising data stores, namely: quality control that can ensure practitioners are all using the same consistent data set as well as revision control in case changes are required in the future. These, and other, ARR projects, although small scale, have proved that the limitations are not technical but rather cultural, namely they fear of confidentiality when accessing services from remote third party servers as well as the institutionalised culture of downloading and archiving copies of data and software. Centralised data management confronts the established dogma of software licensing in that the concept of paying a single license fee for a particular version or data snapshot is, essentially, eliminated. We believe that this will be replaced with an alternate hybrid organisational structure similar to an open source software project combined with a not-for-profit business that would be run by the industry for the industry. This paper presents a brief overview of the already eliminated technical issues and, more importantly, challenges the hydrologic community to critically evaluate their view of data and software ownership, hydrologic engineering workflows and the direction of collaboration in a data centric workplace.
Brady, PD 2014, 'A High-Level API to Access Centralised Australian Rainfall and Runoff Data', Hydrology & Water Resources Symposium 2014 Conference Proceedings, Hydrology & Water Resources Symposium, HWRS, Perth, Australia, pp. 653-660.View/Download from: UTS OPUS
Brady, PD 2011, 'A Novel ILES/VOF Solver for the Simulation of Turbulent Free Surface Flows', 34th IAHR Congress, Balance and Uncertainty - Water in a Changing World, Engineers Australia, Brisbane, pp. 4344-4351.
A new Implicit Large Eddy Simulation Computational Fluid Dynamics algorithm for the simulation of turbulent flows in the presence of a free surface was developed and validated. The unsteady solver computes the motion of the free surface and surrounding fluid with sufficient accuracy yet without the exorbitant requirements of a Direct Numerical Simulation. The validation study was the simulation of the flow around a right circular cylinder that pierced a free surface. The Reynolds number investigated was 27x103, with a corresponding Froude number, based on the cylinder diameter, of 0.75. In clear contrast to a recently published LES simulation, the shape of the free surface was correctly simulated while a spectral analysis indicated, somewhat surprisingly, that the turbulent cascade was being correctly simulated beyond the grid scale, which is a confirmation that the ILES solver is computing the subgrid-scale turbulence.
Brady, PD, Gaston, MJ & Reizes, J 2007, 'An application of a second order upwinding scheme for an implicit LES CFD Solver', Proceedings of the 16th Australasian Fluid Mechanics Conference, Australasian Fluid Mechanics Conference, School of Engineering, The University of Queensland, Surfers Paradise, Queensland, Australia, pp. 1071-1078.View/Download from: UTS OPUS
Amur, GQ, Milton, BE, Reizes, J, Madadnia, J, Beecham, SC, Brady, PD & Koosha, H 2004, 'Role of Plant Buildings in a Power Station Acting as a Barrier to the Wind Affecting the Natural Draft Cooling Tower Performance', Proceedings of the Fifteenth Australasian Fluid Mechanics Conference, Australasian Fluid Mechanics Conference, University of Sydney, Sydney, Australia, pp. 1-8.View/Download from: UTS OPUS