Search

A continuous floc image analyser (C-FIA) was developed for tracking the dynamics of floc particle formation, growth and settling during conventional drinking water treatment processes, comprising coagulation, flocculation and settling. For this, a script was developed to (1) extract the video frames and sync these with reaction time (t), (2) transform the video frames to an equivalent matrix of pixel RGB data, (3) optically filter the video frames for background effects, (4) calculate the filtered (corrected for background) flocculation index (C-FIA FIt) for the frame belonging to each process time through RGB data and (5) correct the C-FIA FIt for baseline RGB signal (raw water frame, C-FIA FI0). The video frames collected by C-FIA have potential to provide direct information on floc size and concentration. The C-FIA FI data were acquired from jar tests using a range of alum doses performed on three natural surface water samples with highly contrasting water quality. The C-FIA FI data acquired, displayed lower variance in comparison with available data of photometric dispersive analysis (PDA). The indices previously developed for PDA analysis were utilized in this study for C-FIA FI data, including plateau index. In experiments conducted, this index showed an inverse relationship with residual turbidity, UVA(254) and colour following coagulation. This indicates a potential for C-FIA to be applied for coagulant dose control at conventional drinking water treatment plants. On the other hand, from the experimental work performed, impacts of light intensity and light radiation angle to the photography cell on the resulting FI value were found. These can impact on the pixels' red/green/blue (RGB) values of the video frames/images, and consequently can impact on the resultant C-FIA FI data. Refereed/Peer-reviewed

Traditional water quality–based processes of assessment using grab samples are simple to implement but far too retrospective and intermediate to adequately deal with water quality change situation. This case study demonstrated a customised software package using a web-based prototype portal with data integration, visualisation, prediction, and anomaly detection functions for complex real-time field monitoring data sets as a visualisation and decision support tool for treatment plant operators. The prototype was developed to analyse two-dimensional data obtained from a spectrophotometer (absorbance against wavelength) and data integrated from other sources (such as rainfall and temperature). It supports normal functions of time series data visualisation, such as, raw data plotting, zooming, smoothing, Boolean band etc. More importantly, it is specialised in supporting real-time monitoring of data quality, time series data comparison, anomaly detection, and future value prediction. The application of the prototype revealed that if this was placed in an operational environment, it has the potential to inform better operational decision by early detection of changes in water quality and impacts on the treatment process. This work demonstrated the potential usefulness of such real-time display and visualisation of online water quality data and the feasibility for prediction tools to provide an early warning system for process upsets.

Forecasts of wastewater inflow are considered as a significant component to support the development of a real-time control (RTC) system for a wastewater pumping network and to achieve optimal operations. This paper aims to investigate patterns of the wastewater inflow behaviour and develop a seasonal autoregressive integrated moving average (SARIMA) forecasting model at low temporal resolution (hourly) for a short-term period of 7 days for a real network in South Australia, the Murray Bridge wastewater network/wastewater treatment plant (WWTP). Historical wastewater inflow data collected for a 32-month period (May 2016 to December 2018) was pre-processed (transformed into an hourly dataset) and then separated into two parts for training (80%) and testing (20%). Results reveal that there is seasonality presence in the wastewater inflow time series data, as it is heavily dependent on time of the day and day of the week. Besides, the SARIMA (1,0,3)(2,1,2)24 was found as the best model to predict wastewater inflow and its forecasting accuracy was determined based on the evaluation criteria including the root mean square error (RMSE = 5.508), the mean absolute value percent error (MAPE = 20.78%) and the coefficient of determination (R2 = 0.773). From the results, this model can provide wastewater operators curial information that supports decision making more effectively for their daily tasks on operating their systems in real-time.

Development of an advanced pumping control scheme is one of the useful methods that can be applied in operational optimisation of wastewater pumps. Optimisation of pumping control can benefit the utility by overall cost saving using different electricity pricing schemes from the energy market. As electricity prices can be varied based on the spot market in some countries such as Australia, the consideration of operating the pumps at the most favourable electricity price, when managed correctly, can offer remarkable savings. This paper provides understanding on the electricity spot price behaviour of South Australia in the National Electricity Market (NEM). Half-hourly electricity spot price data of over 22 years from January 1999 to June 2021 were analysed to investigate the key characteristics of spot prices, including seasonality (intraday, intraweek and seasonal price patterns), spiky behaviour and occurrences of negative prices. In addition, the possible impacts of other factors on electricity spot prices such as electricity demand and weather conditions on pump control were examined. Results indicate a strong relationship between electricity demand and spot price with the Pearson correlation coefficient up to R = 0.95, and extreme high spot prices tended to occur on scorching days with the maximum temperature above 35 °C when air-conditioner usage was high. This paper also explains the importance of electricity spot prices in the wastewater pump on/off operations and analyses opportunities for cost savings by including electricity spot price forecasts as an input of the smart controller to enhance the efficiency of the real-time pumping control.

Calcium aluminate cement (CAC)—based strain hardening cementitious composites (SHCC) has been developed and used for the rehabilitation of sewerage pipelines. In addition to well-known microbiologically induced corrosion, CO2 concentration in the sewerage environment is high, which may cause significant carbonation of pipelines. Thus, this paper aims to investigate the effects of carbonation on the mechanical performance of CAC-based SHCC. Two types of CAC-based SHCC with different strength grades and a referenced OPC-based SHCC were prepared. The accelerated carbonation test was conducted in a carbonation chamber with a 5% CO2 concentration. The compressive and tensile behaviour of SHCC was tested first, and microstructure analysis, e.g., X-ray diffraction and scanning electron microscopy, was then performed. The results showed that CAC-based SHCC specimens exhibited robust strain-hardening performance as well as large deformation capacity in tension due to the fiber-bridging effect. Also, the compressive and tensile strength was significantly improved as well as achieving a higher tensile strain capacity after carbonation when compared with OPC-based SHCC. Microstructure analysis revealed that the metastable phases in carbonated CAC-based SHCC were converted into stable phases and calcium carbonate polymorphs, densifying the binder matrix. The obtained results of this paper may provide new insight into utilizing carbonation to avoid the unstable conversion of hydrates in calcium aluminate cement.

Monochloramine, commonly referred to as chloramine, is a popular disinfectant used in drinking water distribution systems (DWDS) where high water age is encountered. Chloramine, being more stable than chlorine, is suited to such DWDS to ensure water is microbiologically safe at customer taps. It decays with time, so a certain level of chloramine residual needs to be maintained throughout the distribution system to prevent bacterial regrowth. Dependent on water quality, chloramine decay will occur through several pathways. The major pathways of chloramine decay and the kinetics involved are reviewed in this paper. Several chemical and microbiological factors including pH, temperature, hydraulic residence time, concentration/character of natural organic matter, chlorine to ammonia ratio and concentration of bacterial cells are known to have significant impact on chloramine decay. Under favourable conditions, microbiologically mediated decay can dominate over the other decay pathways by an order of magnitude. Examples include rapid chloramine decay and nitrification where a complete loss of chloramine residual occurs within a short time. From extensive research, a number of empirical and theoretical models have been developed to determine the chloramine decay. However, their application is still challenging as they generally rely on physical and chemical principles and suitable under specific conditions, although the environmental conditions throughout each DWDS vary. One way to improve the estimate of chloramine measurement, hence, better management of chloramine residual, is by developing a site-specific water quality model, incorporating the parameters representing chloramine decays in different pathways, with the unknown parameter obtained through an optimisation process. Refereed/Peer-reviewed

Refereed/Peer-reviewed In this study, the dredged river sediment, soft texture and fine particles, is mixed with other materials and transformed into eco-friendly autoclaved aerated concrete (hereinafter referred to as AAC) blocks. The results indicated the bricks produced under the conditions of 30%–34% dredged river sediment, 24% cement, 10% quick lime, 30% fly ash, 2% gypsum and 0.09% aluminum powder with 0.5 water to material ratio, 2.2 MPa autoclave pressure and 6 h autoclave time, the average compressive strength of 4.5 MPa and average dry density of 716.56 kg/m³ were obtained, the two parameters (strength & density) both met the requirement of national industry standard. At the same time, the contents of dredged river sediment, cement, lime, fly ash, gypsum and aluminum powder were 15%, 48%, 20%, 15%, 2% and 0.09%, respectively, and the non-AAC block made of 0.5 water to material ratio, the average compressive strength of 3.1 MPa and average dry density of 924.19 kg/m³ were obtained, the two parameters (strength & density) also met the requirement of national industry standard. In addition, the AAC block’s phase composition and morphology were micro-analyzed by SEM and XRD, the main substances in AAC block were found to be tobermorite and CSH, Among them, the chemical bond between Si-O-Si and Al-O-Al is broken, Al-O-Si is regenerated, Al substituted tobermorite with better strength is formed, and the compressive strength of AAC is further improved.

Nitrification is a major challenge in chloraminated drinking water systems, resulting in undesirable loss of disinfectant residual. Consequently, heterotrophic bacteria growth is increased, which adversely affects the water quality, causing taste, odour, and health issues. Regular monitoring of various water quality parameters at susceptible areas of the water distribution system (WDS) helps to detect nitrification at an earlier stage and allows sufficient time to take corrective actions to control it. Strategies to monitor nitrification in a WDS require conducting various microbiological tests or assessing surrogate parameters that are affected by microbiological activities. Additionally, microbial decay factor (Fm) is used by water utilities to monitor the status of nitrification. In contrast, approaches to manage nitrification in a WDS include controlling various factors that affect monochloramine decay rate and ammonium substrate availability, and that can inhibit nitrification. However, some of these control strategies may increase the regulated disinfection-by-products level, which may be a potential health concern. In this paper, various strategies to monitor and control nitrification in a WDS are critically examined. The key findings are: (i) the applicability of some methods require further validation using real WDS, as the original studies were conducted on laboratory or pilot systems; (ii) there is no linkage/formula found to relate the surrogate parameters to the concentration of nitrifying bacteria, which possibly improve nitrification monitoring performance; (iii) improved methods/monitoring tools are required to detect nitrification at an earlier stage; (iv) further studies are required to understand the effect of soluble microbial products on the change of surrogate parameters. Based on the current review, we recommend that the successful outcome using many of these methods is often site-specific, hence, water utilities should decide based on their regular experiences when considering economic and sustainability aspects. Refereed/Peer-reviewed

Refereed/Peer-reviewed The textile industry uses a variety of synthetic dyes for dyeing and discharges a large amount of colored wastewater. It is difficult to achieve good decolorization effect for textile wastewater by conventional biological treatment methods, because it contains various synthetic dyes with complex structures. At present, coagulation is an economical and effective treatment method. However, in dye removal by coagulation research, the adaptability and mechanisms of coagulation removal of many dyes are still unknown due to the wide variety of dyes in use. In this study, ferric chloride (FeCl₃), aluminum chloride (AlCl₃) and magnesium chloride (MgCl₂) were selected as coagulants, and direct orange 26 (DO), direct yellow 11 (DY) and direct black 19 (DB) were used as the dye samples to conduct a series of coagulation experiments; in order to understand the coagulation adaptability and mechanism for high removal efficiency of direct dyes. In this system without particles, the direct dyes were dissolved directly in pure water and maintained in molecular state. The results showed that 1) AlCl₃, FeCl₃ and MgCl₂ exhibited superior coagulation efficiency on the three dyes. Direct dyes which contain more amino functional groups are more easily removed by coagulation. 2) The influence of hydraulic conditions on the residual turbidity was more significant compared with the color removal. 3) Zeta potential increased with the increase of the coagulant dosage, but the colloidal particles did not re-stabilize. This proved that charge neutralization is not the dominant mechanism of coagulation. The FT-IR and XRD patterns indicated that the direct dyes were removed by the chemical combination of the -SO₃H on the dye molecule and the hydrolysate of the coagulant.

Failure prognostics and health management are central to the Remaining Useful Life (RUL) estimation of critical engineering assets, particularly to improve safety, reduce downtimes and maintenance expenditures. Over recent years, several prognostic approaches have been developed to predict remaining asset lifetime, optimise maintenance schedules, and enhance equipment availability and reliability. While academic research in this area has grown rapidly, implementations of these methods by industry’s asset managers and reliability experts have only had limited success. Yet asset lifetime and reliability analysis are only restricted to the conventional reliability-centred maintenance and total productive maintenance approaches in industries. The purpose of this paper is to emphasise a need for a paradigm shift in industrial asset health management from the conventional to modern approaches that would benefit industries. At first, this paper classifies existing prognostic techniques into the traditional reliability, model-based, and data-driven approaches. Each prognostic approach is then analytically discussed with emphasis on models and algorithms. Consequently, this paper explores the strengths and weaknesses of main models in these groups to assist industry practitioners to select an appropriate prognostic model for RUL prediction within their specific business environment. Finally, the paper concludes with a brief discussion on possible future trends and further research directions in this field. Refereed/Peer-reviewed

Refereed/Peer-reviewed Cement-based sensors include conductive fillers to achieve a sensing capability based on the piezoresistivity phenomenon, in which the electrical resistivity changes with strain. The microstructural characterisation of cement-based sensors can be obtained using a promising non-destructive technique, such as AC impedance spectroscopy (ACIS), which has been recently used by many researchers. This paper reviews the fundamental concepts of piezoresistivity and ACIS in addition to the comparison of equivalent circuit models of cement-based sensors found in the literature. These concepts include piezoresistivity theory, factors affecting piezoresistivity measurement, resistance measurement methodology, strain/damage sensing, causes of piezoresistivity, theories of conduction, AC impedance spectroscopy theory, and the equivalent circuit model. This review aims to provide a comprehensive guide for researchers and practitioners interested in exploring and applying different techniques to self-sensing concrete.

There is an increasing need to use online instrumentation for continuous monitoring of water quality. However, industrial applications using online instruments, such as submersible UV-Vis spectrophotometers, may require the use of alternative techniques to remove particle effect rather than performing a physical filtration step. Some submersible UV-Vis spectrophotometers have built-in generic particle compensation algorithms to remove the filtration step. This work studied the influence of suspended particles on the measurements of a submersible UV-Vis spectrophotometer as well as the performance of the built-in particle compensation technique under laboratory-controlled conditions. Simulated water samples were used in the combinations of standard particles from laboratory chemical and natural particles extracted from water systems with ultrapure water and treated water from a drinking water treatment plant. Particle contributions to the UV absorbance at 254 nm (UV

Drinking water treatment sludge (DWTS) can be recycled into low-strength concrete blocks for construction use. The sodium sulfate resistance and leaching behaviours of the DWTS-derived blocks are investigated in this study. The experimental results show that the addition of DWTS degrades the sodium sulfate resistance of the concrete blocks, however CO