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Microwave-based reactions have gained traction in recent years due to their ability to enhance reaction rates and yield while reducing energy consumption. Also, according to the conception of ‘waste to materials’, various waste feeds are intensively sought to be tested. The experimental setup of this study involved varying pH levels, oxidation agents, and precipitation agents to optimize the synthesis process of iron red based on waste iron sulfate. The selection of oxidation and precipitation agents was found to significantly influence the pigment synthesis process. Various oxidizing agents, including hydrogen peroxide and atmospheric air, were evaluated for their effectiveness in promoting the oxidation of ferrous ions to ferric ions, essential for pigment formation. Additionally, different precipitation agents such as sodium hydroxide and ammonia solution were assessed for their ability to precipitate iron hydroxides and facilitate pigment particle formation. The characterization of synthesized pigments revealed promising results in terms of quality and color properties. Helium Ion Microscopy (HIM) analysis confirmed the formation of well-defined pigment particles with controlled morphology. X-ray diffraction (XRD) studies provided insights into the crystalline structure of the pigments, indicating the presence of characteristic iron oxide phases. By improving this technology, waste iron sulfate can be efficiently transformed into valuable iron pigments, offering a sustainable solution for waste management while meeting the growing demand for high-quality pigments.

Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications., Coastal Engineering

The sensitivity of a one-line longshore shoreline change model to the incident wave direction is evaluated at Narrabeen Beach (Australia). As previously observed, the application of the one-line model using wave conditions generated along the 10-m depth contour produces a long-term reorientation of the coastline, with an initial transition period and then a new stable equilibrium during the 10-year period from 2005 to 2015. However, this coastline change in shoreline planform shape is not observed in the shoreline position measurements. The source of this error is investigated by assuming that it is caused by biases in the incident wave direction and by using a Monte Carlo approach to search for the optimal set of wave angle bias corrections to apply at each cross-shore transect. The obtained optimal values enable the one-line model to reproduce accurately the shoreline planform, and they are coherent with estimates of the wave breaking angle obtained independently using a nearshore wave propagation model. Then, using the corrected wave angle time series as a reference, a second Monte Carlo analysis is completed to investigate the sensitivity of the model to errors in the mean wave direction drawn from Gaussian distributions with varying standard deviations. The analysis shows the range of expected errors in shoreline position for an estimated range of errors in the mean wave direction at Narrabeen beach. This work highlights the importance of considering the sensitivity of one-line longshore model simulations to errors in the incident wave angle, which can be relatively large given the uncertainties in spectral wave model estimates of wave direction, in wave buoy observations, and in wave propagation methods or input bathymetry used to estimate wave breaking conditions.

Energy dissipation is an important aspect in the design of hydraulic structures. Stilling basins are a common type of energy dissipator in which a hydraulic jump dissipates large amounts of the flow energy. The energetic processes in hydraulic jumps are closely linked with air entrainment and non-stationary interactions of roller and free-surface motions. Free-surface motions may provide information on the overall performance of a stilling basin. Recently LIDAR technology was pioneered as a method to measure highly aerated hydraulic jumps providing continuous non-intrusive free-surface measurements with high temporal and spatial resolution. In the present study, the LIDAR technology was applied to a hydraulic jump in a laboratory-scale stilling basin. A LIDAR measured the time-varying free-surface features at seven longitudinal and six transverse cross-sections across the stilling basin. A three-dimensional free-surface map was created providing a detailed and integrated free-surface image. Three dimensionalities of free-surface profiles and fluctuations are presented and opportunities of free-surface mapping discussed.

This chapter introduces the reader to the basic concepts of machine learning (ML). Popular ML methods, such as neural networks, support vector machines, Bayesian networks, decision trees and the k-nearest neighbours algorithm are described along with simple examples applied to coastal processes. The reader is then guided through the steps required to develop ML algorithms from the first steps of data selection and preparation, to model selection, development and evaluation. A case study worked example is also included for the reader as a step-by-step guide to setting up a simple ML model and is provided as a supplementary online workbook for this chapter. The chapter concludes with a brief discussion on the future of ML in coastal processes research.

Increasing Navy Fleet size requires an increase and diversity of maritime facilities. By 2035, around half of the world’s submarines will be operating in the IndoPacifc region (Defence 2016). Submarines offer a unique defence capability and play an essential role in supporting Australia’s maritime security. When berthed, submarines sit lower in the water than other large military vessels and experience more excessive motions in operational wave conditions. As such, shore connected floating pontoons are an important option for developing and operating submarine facilities and are particularly appropriate for both the docking and loading of submarines. The safety of Navy personnel during loading of munitions and general operational tasks require that safe working limits be placed on the motions of these piled floating pontoons. At present, there are no standards assigning suitable limits of motion for floating pontoons in order to maintain the safety/comfort of users undertaking operational activities. This research proposes a set of operational safe motion limits in the form of accelerations to ensure the comfort and safety of floating pontoon users. Experimental work has been undertaken and data collected on the motions of a piled floating pontoon subjected to regular waves, representative of a harbour environment. Pontoon widths, drafts and skirts have been examined under varying wave conditions. The research has found that in many circumstances, the pontoon motions exceed proposed safe working limits and that the application of different pontoon design features can be used to reduce the accelerations of motion to within operational safe motion limits.

This paper describes the process and outcomes of a collaborative process across different Australian stakeholder groups to identify the highest priorities in wind-wave research.The Australian marine research, industry and stakeholder community has recently undertaken an extensive collaborative process to identify the highest national priorities for wind-waves research. This was undertaken under the auspices of the Forum for Operational Oceanography Surface Wave’s Working Group. The main steps in the process were firstly, soliciting possible research questions from the community via an online survey; secondly, reviewing the questions at a face-to-face workshop; and thirdly, online ranking of the research questions by individuals. This process resulted in 15 identified priorities, covering research activities and the development of infrastructure. The top 5 priorities are 1) Enhanced and updated nearshore and coastal bathymetry; 2) Improved understanding of extreme sea-states; 3) Maintain and enhance in situ buoy network; 4) Improved data access and sharing; and 5) Ensemble and probabilistic wave modelling and forecasting. In this paper, each of the 15 priorities is discussed in detail, providing insight into why each priority is important, and the current state-of-the-art, both nationally and internationally, where relevant. While this process has been driven by Australian needs, it is likely that the results will be relevant to other marine-focussed nations.

Long-term high-resolution measurements of coastal variability are extremely rare and provide unique insight to beach fluctuations and change at a variety of different scales. Crucially, they also provide an invaluable dataset that researchers can use to test and develop new coastal modelling tools and statistical techniques. This paper describes one such coastal monitoring program that has been continuously underway at Narrabeen-Collaroy Beach in SE Australia at monthly or greater survey frequencies for the past 39 years. The history of this unique program can be divided into two periods: (1) the initial three decades (1976-2006) characterised by the use of traditional survey methods; and (2) the past decade during which the monitoring program has been expanded and modernised using new survey technologies such as RTK-GPS, coastal imaging, LiDAR and UAV technology. A summary and timeline as to the introduction of the various technologies is presented, followed by some standard data products (e.g. the Subaerial Volume and Beach Orientation Indices) produced from the raw historical data to facilitate easy data interpretation. With the forty-year anniversary of this dataset approaching in April 2016, efforts are being made to make this dataset openly accessible for download via a public web interface, thereby extending the reach of this valuable dataset to coastal researchers and practitioners worldwide.

Sophisticated numerical models play an important role in forecasting beach erosion at high risk sites along NSW coastlines. These models contain free parameters that require calibration to available field data and little guidance (beyond the adoption of the default values provided) is presently available to inform the selection of best-fit parameter values. In practice, the means of calibrating erosion models through the optimisation of these parameters often lacks a sufficient consideration of parameter compensation for model error, the impacts of parameter interdependence and parameter-induced model uncertainty. The Generalised Likelihood Uncertainty Estimation (GLUE) method has been previously employed in the field of hydrology and has proven to be a conceptually simple and efficient method to evaluate model sensitivity to parameters, optimum calibrated parameter values and parameter uncertainty. This paper describes the application of the GLUE method to the XBeach storm erosion model, using data from a site in Italy where the XBeach model has been previously applied without such a rigorous calibration method. The results presented demonstrate the more generic effectiveness of GLUE in enhancing the performance of coastal numerical models. The sensitivity of XBeach to each trailed free parameter is determined in a rigorous and transparent manner, and parameter-induced uncertainty bounds are obtained. This enables the modeller to better quantify model skill in predicting observed and potential future erosion.

Robust data are the base of effective gender diversity policy. Evidence shows that gender inequality is still pervasive in science, technology, engineering and mathematics (STEM). Coastal geoscience and engineering (CGE) encompasses professionals working on coastal processes, integrating expertise across physics, geomorphology, engineering, planning and management. The article presents novel results of gender inequality and experiences of gender bias in CGE, and proposes practical steps to address it. It analyses the gender representation in 9 societies, 25 journals, and 10 conferences in CGE and establishes that women represent 30% of the international CGE community, yet there is under-representation in prestige roles such as journal editorial board members (15% women) and conference organisers (18% women). The data show that female underrepresentation is less prominent when the path to prestige roles is clearly outlined and candidates can self-nominate or volunteer instead of the traditional invitation-only pathway. By analysing the views of 314 survey respondents (34% male, 65% female, and 1% ‘‘other’’), we show that 81% perceive the lack of female role models as a key hurdle for gender equity, and a significantly larger proportion of females (47%) felt held back in their careers due to their gender in comparison with males (9%). The lack of women in prestige roles and senior positions contributes to 81% of survey respondents perceiving the lack of female role models in CGE as a key hurdle for gender equality. While it is clear that having more women as role models is important, this is not enough to effect change. Here seven practical steps towards achieving gender equity in CGE are presented: (1) Advocate for more women in prestige roles; (2) Promote high-achieving females; (3) Create awareness of gender bias; (4) Speak up; (5) Get better support for return to work; (6) Redefine success; and, (7) Encourage more women to enter the discipline at a young age. Some