Port of Brisbane stormwater quality : stage 1 rainfall simulation to evaluate pollutant build-up and wash-off from selected land uses

Background: The quality of stormwater runoff from ports is significant as it can be an important source of pollution to the marine environment. This is also a significant issue for the Port of Brisbane as it is located in an area of high environmental values. Therefore, it is imperative to develop an in-depth understanding of stormwater runoff quality to ensure that appropriate strategies are in place for quality improvement. ---------------- The Port currently has a network of stormwater sample collection points where event based samples together with grab samples are tested for a range of water quality parameters. Whilst this information provides a ‘snapshot’ of the pollutants being washed from the catchment/s, it does not allow for a quantifiable assessment of total contaminant loads being discharged to the waters of Moreton Bay. It also does not represent pollutant build-up and wash-off from the different land uses across a broader range of rainfall events which might be expected. As such, it is difficult to relate stormwater quality to different pollutant sources within the Port environment. ----------------- Consequently, this would make the source tracking of pollutants to receiving waters extremely difficult and in turn the ability to implement appropriate mitigation measures. Also, without this detailed understanding, the efficacy of the various stormwater quality mitigation measures implemented cannot be determined with certainty. --------------- Current knowledge on port stormwater runoff quality Currently, little knowledge exists with regards to the pollutant generation capacity specific to port land uses as these do not necessarily compare well with conventional urban industrial or commercial land use due to the specific nature of port activities such as inter-modal operations and cargo management. Furthermore, traffic characteristics in a port area are different to a conventional urban area. Consequently, as data inputs based on an industrial and commercial land uses for modelling purposes is questionable. ------------------ A comprehensive review of published research failed to locate any investigations undertaken with regards to pollutant build-up and wash-off for port specific land uses. Furthermore, there is very limited information made available by various ports worldwide about the pollution generation potential of their facilities. Published work in this area has essentially focussed on the water quality or environmental values in the receiving waters such as the downstream bay or estuary. ----------------- The Project: The research project is an outcome of the collaborative Partnership between the Port of Brisbane Corporation (POBC) and Queensland University of Technology (QUT). A key feature of this Partnership is the undertaking of ‘cutting edge’ research to strengthen the environmental custodianship of the Port area. This project aims to develop a port specific stormwater quality model to allow informed decision making in relation to stormwater quality improvement in the context of the increased growth of the Port. --------------- Stage 1 of the research project focussed on the assessment of pollutant build-up and wash-off using rainfall simulation from the current Port of Brisbane facilities with the longer-term objective of contributing to the development of ecological risk mitigation strategies for future expansion scenarios. Investigation of complex processes such as pollutant wash-off using naturally occurring rainfall events has inherent difficulties. These can be overcome using simulated rainfall for the investigations. ----------------- The deliverables for Stage 1 included the following: * Pollutant build-up and wash-off profiles for six primary land uses within the Port of Brisbane to be used for water quality model development. * Recommendations with regards to future stormwater quality monitoring and pollution mitigation measures. The outcomes are expected to deliver the following benefits to the Port of Brisbane: * The availability of Port specific pollutant build-up and wash-off data will enable the implementation of customised stormwater pollution mitigation strategies. * The water quality data collected would form the baseline data for a Port specific water quality model for mitigation and predictive purposes. * To be at the cutting-edge in terms of water quality management and environmental best practice in the context of port infrastructure. ---------------- Conclusions: The important conclusions from the study are: * It confirmed that the Port environment is unique in terms of pollutant characteristics and is not comparable to typical urban land uses. * For most pollutant types, the Port land uses exhibited lower pollutant concentrations when compared to typical urban land uses. * The pollutant characteristics varied across the different land uses and were not consistent in terms of the land use. Hence, the implementation of stereotypical structural water quality improvement devices could be of limited value. * The <150m particle size range was predominant in suspended solids for pollutant build-up as well as wash-off. Therefore, if suspended solids are targeted as the surrogate parameter for water quality improvement, this specific particle size range needs to be removed. ------------------- Recommendations: Based on the study results the following preliminary recommendations are made: * Due to the appreciable variation in pollutant characteristics for different port land uses, any water quality monitoring stations should preferably be located such that source areas can be easily identified. * The study results having identified significant pollutants for the different land uses should enable the development of a more customised water quality monitoring and testing regime targeting the critical pollutants. * A ‘one size fits all’ approach may not be appropriate for the different port land uses due to the varying pollutant characteristics. As such, pollution mitigation will need to be specifically tailored to suit the specific land use. * Any structural measures implemented for pollution mitigation to be effective should have the capability to remove suspended solids of size <150m. * Based on the results presented and the particularly the fact that the Port land uses cannot be compared to conventional urban land uses in relation to pollutant generation, consideration should be given to the development of a port specific water quality model.

Faster group operations on elliptic curves

This paper improves implementation techniques of Elliptic Curve Cryptography. We introduce new formulae and algorithms for the group law on Jacobi quartic, Jacobi intersection, Edwards, and Hessian curves. The proposed formulae and algorithms can save time in suitable point representations. To support our claims, a cost comparison is made with classic scalar multiplication algorithms using previous and current operation counts. Most notably, the best speeds are obtained from Jacobi quartic curves which provide the fastest timings for most scalar multiplication strategies benefiting from the proposed 12M + 5S + 1D point doubling and 7M + 3S + 1D point addition algorithms. Furthermore, the new addition algorithm provides an efficient way to protect against side channel attacks which are based on simple power analysis (SPA). Keywords: Efficient elliptic curve arithmetic,unified addition, side channel attack.

Port decoupling for small arrays by means of an eigenmode feed network

An alternative approach to port decoupling and matching of arrays with tightly coupled elements is proposed. The method is based on the inherent decoupling effect obtained by feeding the orthogonal eigenmodes of the array. For this purpose, a modal feed network is connected to the array. The decoupled external ports of the feed network may then be matched independently by using conventional matching circuits. Such a system may be used in digital beam forming applications with good signal-to-noise performance. The theory is applicable to arrays with an arbitrary number of elements, but implementation is only practical for smaller arrays. The principle is illustrated by means of two examples.

Port of Brisbane stormwater quality : stage 2 development of a port specific water quality model

Background: The quality of stormwater runoff from ports is significant as it can be an important source of pollution to the marine environment. This is also a significant issue for the Port of Brisbane as it is located in an area of high environmental values. Therefore, it is imperative to develop an in-depth understanding of stormwater runoff quality to ensure that appropriate strategies are in place for quality improvement, where necessary. To this end, the Port of Brisbane Corporation aimed to develop a port specific stormwater model for the Fisherman Islands facility. The need has to be considered in the context of the proposed future developments of the Port area. ----------------- The Project: The research project is an outcome of the collaborative Partnership between the Port of Brisbane Corporation (POBC) and Queensland University of Technology (QUT). A key feature of this Partnership is that it seeks to undertake research to assist the Port in strengthening the environmental custodianship of the Port area through ‘cutting edge’ research and its translation into practical application. ------------------ The project was separated into two stages. The first stage developed a quantitative understanding of the generation potential of pollutant loads in the existing land uses. This knowledge was then used as input for the stormwater quality model developed in the subsequent stage. The aim is to expand this model across the yet to be developed port expansion area. This is in order to predict pollutant loads associated with stormwater flows from this area with the longer term objective of contributing to the development of ecological risk mitigation strategies for future expansion scenarios. ----------------- Study approach: Stage 1 of the overall study confirmed that Port land uses are unique in terms of the anthropogenic activities occurring on them. This uniqueness in land use results in distinctive stormwater quality characteristics different to other conventional urban land uses. Therefore, it was not scientifically valid to consider the Port as belonging to a single land use category or to consider as being similar to any typical urban land use. The approach adopted in this study was very different to conventional modelling studies where modelling parameters are developed using calibration. The field investigations undertaken in Stage 1 of the overall study helped to create fundamental knowledge on pollutant build-up and wash-off in different Port land uses. This knowledge was then used in computer modelling so that the specific characteristics of pollutant build-up and wash-off can be replicated. This meant that no calibration processes were involved due to the use of measured parameters for build-up and wash-off. ---------------- Conclusions: Stage 2 of the study was primarily undertaken using the SWMM stormwater quality model. It is a physically based model which replicates natural processes as closely as possible. The time step used and catchment variability considered was adequate to accommodate the temporal and spatial variability of input parameters and the parameters used in the modelling reflect the true nature of rainfall-runoff and pollutant processes to the best of currently available knowledge. In this study, the initial loss values adopted for the impervious surfaces are relatively high compared to values noted in research literature. However, given the scientifically valid approach used for the field investigations, it is appropriate to adopt the initial losses derived from this study for future modelling of Port land uses. The relatively high initial losses will reduce the runoff volume generated as well as the frequency of runoff events significantly. Apart from initial losses, most of the other parameters used in SWMM modelling are generic to most modelling studies. Development of parameters for MUSIC model source nodes was one of the primary objectives of this study. MUSIC, uses the mean and standard deviation of pollutant parameters based on a normal distribution. However, based on the values generated in this study, the variation of Event Mean Concentrations (EMCs) for Port land uses within the given investigation period does not fit a normal distribution. This is possibly due to the fact that only one specific location was considered, namely the Port of Brisbane unlike in the case of the MUSIC model where a range of areas with different geographic and climatic conditions were investigated. Consequently, the assumptions used in MUSIC are not totally applicable for the analysis of water quality in Port land uses. Therefore, in using the parameters included in this report for MUSIC modelling, it is important to note that it may result in under or over estimations of annual pollutant loads. It is recommended that the annual pollutant load values given in the report should be used as a guide to assess the accuracy of the modelling outcomes. A step by step guide for using the knowledge generated from this study for MUSIC modelling is given in Table 4.6. ------------------ Recommendations: The following recommendations are provided to further strengthen the cutting edge nature of the work undertaken: * It is important to further validate the approach recommended for stormwater quality modelling at the Port. Validation will require data collection in relation to rainfall, runoff and water quality from the selected Port land uses. Additionally, the recommended modelling approach could be applied to a soon-to-be-developed area to assess ‘before’ and ‘after’ scenarios. * In the modelling study, TSS was adopted as the surrogate parameter for other pollutants. This approach was based on other urban water quality research undertaken at QUT. The validity of this approach should be further assessed for Port land uses. * The adoption of TSS as a surrogate parameter for other pollutants and the confirmation that the <150 m particle size range was predominant in suspended solids for pollutant wash-off gives rise to a number of important considerations. The ability of the existing structural stormwater mitigation measures to remove the <150 m particle size range need to be assessed. The feasibility of introducing source control measures as opposed to end-of-pipe measures for stormwater quality improvement may also need to be considered.

Room for improvement : hotel giant resorts to Six Sigma to improve operations

Six Sigma provides a framework for quality improvement and business excellence. Introduced in the 1980s in manufacturing, the concept of Six Sigma has gained popularity in service organizations. After initial success in healthcare and banking, Six Sigma has gradually gained traction in other types of service industries, including hotels and lodging. Starwood Hotels and Resorts was the first hospitality giant to embrace Six Sigma. In 2001, Starwood adopted the method to develop innovative, customer-focused solutions and to transfer these solutions throughout the global organization. To analyze Starwood's use of Six Sigma, the authors collected data from articles, interviews, presentations and speeches published in magazines, newspapers and Web sites. This provided details to corroborate information, and they also made inferences from these sources. Financial metrics can explain the success of Six Sigma in any organization. There was no shortage of examples of Starwood's success resulting from Six Sigma project metrics uncovered during the research.

An innovative modelling approach to assess stormwater pollutant loads from the Port of Brisbane, Australia

Port land uses are subjected to unique anthropogenic activities compared to typical urban land uses. This uniqueness results in distinctive stormwater quality characteristics. Such distinction in stormwater quality has made conventional approaches used for pollutant load estimations inaccurate. This is also the case for the Port of Brisbane (PoB). The study discussed in the paper was conducted to estimate the pollutant contributions from Port specific land uses at PoB. For estimation, software modules embedded in Mike URBAN were used. An innovative approach was adopted in modelling where the conventional model calibration step was not needed to be performed to generate suitable site specific parameters. Instead, equations and site specific parameters that replicate pollutant build-up and wash-off were generated from an extensive field investigation. Models were simulated incorporating site specific parameters from six different Port specific land uses and rainfall events from three representative years. Outcomes of the modelling exercise were used to identify the distinct pollutant contributions from different Port land uses.

A general-purpose simulator for train operations

Computer simulation has been widely accepted as an essential tool for the analysis of many engineering systems. It is nowadays perceived to be the most readily available and feasible means of evaluating operations in real railway systems. Based on practical experience and theoretical models developed in various applications, this paper describes the design of a general-purpose simulation system for train operations. Its prime objective is to provide a single comprehensive computer-aided engineering tool for most studies on railway operations so that various aspects of the railway systems with different operation characteristics can be investigated and analysed in depth. This system consists of three levels of simulation. The first is a single-train simulator calculating the running time of a train between specific points under different track geometry and traction conditions. The second is a dual-train simulator which is to find the minimum headway between two trains under different movement constraints, such as signalling systems. The third is a whole-system multi-train simulator which carries out process simulation of the real operation of a railway system according to a practical or planned train schedule or headway; and produces an overall evaluation of system performance.

Engaging operations management students by designing the unit with industry focus

Operations management is an area concerned with the production of goods and services ensuring that business operations are efficient in utilizing resource and effective to meet customer requirements. It deals with the design and management of products, processes, services and supply chains and considers the acquisition, development, and effective and efficient utilization of resources. Unlike other engineering subjects, content of these units could be very wide and vast. It is therefore necessary to cover the content that is most related to the contemporary industries. It is also necessary to understand what engineering management skills are critical for engineers working in the contemporary organisations. Most of the operations management books contain traditional Operations Management techniques. For example ‘inventory management’ is an important topic in operations management. All OM books deal with effective method of inventory management. However, new trend in OM is Just in time (JIT) delivery or minimization of inventory. It is therefore important to decide whether to emphasise on keeping inventory (as suggested by most books) or minimization of inventory. Similarly, for OM decisions like forecasting, optimization and linear programming most organisations now a day’s use software. Now it is important for us to determine whether some of these software need to be introduced in tutorial/ lab classes. If so, what software? It is established in the Teaching and Learning literature that there must be a strong alignment between unit objectives, assessment and learning activities to engage students in learning. Literature also established that engaging students is vital for learning. However, engineering units (more specifically Operations management) is quite different from other majors. Only alignment between objectives, assessment and learning activities cannot guarantee student engagement. Unit content must be practical oriented and skills to be developed should be those demanded by the industry. Present active learning research, using a multi-method research approach, redesigned the operations management content based on latest developments in Engineering Management area and the necessity of Australian industries. The redesigned unit has significantly helped better student engagement and better learning. It was found that students are engaged in the learning if they find the contents are helpful in developing skills that are necessary in their practical life.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.