ORCID Profile
0000-0002-9230-6175
Current Organisation
Macquarie University
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Manufacturing Engineering | Nonlinear Optics and Spectroscopy | Manufacturing Processes and Technologies (excl. Textiles) | Metals and Alloy Materials
Expanding Knowledge in the Physical Sciences | Expanding Knowledge in Engineering | Metals (e.g. Composites, Coatings, Bonding) |
Publisher: IOP Publishing
Date: 11-2021
DOI: 10.1088/1757-899X/1200/1/012009
Abstract: Due to modernization and urbanization, the number of vehicles on the road has been increased. Around 3 billion tires have been sold, and an equivalent number of tires have been discarded each year. Even though the lifetime of the tires has been increased but according to the Australian Bureau of Statistics, the number of end-of-life tires is going to rise approximately 5 billion in a year. Its complex composition, make it the most tricky and difficult waste in the world to handle. Because it creates significant health and environmental problem by emitting harmful chemicals in the environment, working as a birthplace for pests, and prone to fire hazards. Recycling waste tires can add economical value also creating a sustainable way to dispose of them. This paper presents different recycling strategies and civil engineering applications of end-of-life tires. Reduction, reuse, recovery, and recycling have been applied. Application of waste tire as reinforcing layers in landfill, road pavement, drainage system, fuel source in the kiln, playground surface makes it an ideal material for affordable, medium-density, low-rise buildings that are highly valued worldwide. Moreover, the sound insulation and absorption with enhanced seismic resilience properties of the end-of-life tire can provide novel and effective engineering solutions.
Publisher: Elsevier BV
Date: 03-2021
Publisher: Wiley
Date: 03-12-2019
DOI: 10.1002/PRS.12114
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 09-2023
Publisher: Thomas Telford Ltd.
Date: 03-2022
Abstract: The present study aims to investigate the impacts of oil sands development in Canada on the economy, society and the environment as the three pillars of sustainability. Factors such as aquatic ecosystems, land disturbance and reclamation, air quality, public health, safety, aboriginal and local communities, gross domestic product, employment rate and job creation, government revenues and demographic changes have been considered. Based on a review of the available literature, this study shows that the oil sands industry has so far fallen short in keeping a balance among the three pillars of sustainability, with the negative impacts on society (e.g. changing the lifestyle of Aboriginal people) and the environment (e.g. land disturbance) overweighing the relatively positive economic impacts. This, along with the current pace of remedies (e.g. land reclamation), makes it hard to conclude that the oil sands industry is sustainable.
Publisher: IOP Publishing
Date: 11-2021
DOI: 10.1088/1757-899X/1200/1/012003
Abstract: Due to the global urbanization, economic development, and increasing rate of the world’s population, the construction of new buildings and infrastructure is increasing. The manufacture of concrete has become an essential part of our life all over the world. Emitting 5-8% of carbon dioxide (CO 2 ), the production of concrete becomes the main obstacle to reach global climate action under the Paris 2050 Agreement. Reuse of waste or recycled waste materials in concrete as an environmentally friendly construction material has become highlighted as a feature of achieving sustainability, because of its potential environmental and economic benefits. The focus of this paper is to assess the application of alternative eco- friendly substitutes of cement for an innovative, economically attractive, and environmentally friendly alternative, and the transition towards of circular economy by reducing the number of natural resources consumed. Based on the existing studies, waste material (fly ash, bottom ash, coal ash, tire, steel slag, construction and demolition waste, glass, ceramic) incorporated with concrete accepted performance in the environment and economic perspective by reducing energy consumption, greenhouse gas emissions, costs, and other indicators.
Publisher: Springer Science and Business Media LLC
Date: 22-01-2009
Publisher: Springer Science and Business Media LLC
Date: 25-07-2013
Publisher: Wiley
Date: 05-12-2019
DOI: 10.1002/PRS.12118
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 02-2017
Publisher: Elsevier BV
Date: 08-2018
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 05-2020
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier
Date: 2018
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier
Date: 2020
Publisher: The Society of Naval Architects and Marine Engineers
Date: 11-2016
Publisher: Elsevier BV
Date: 05-2022
Publisher: Elsevier BV
Date: 07-2022
Publisher: The Society of Naval Architects and Marine Engineers
Date: 2016
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 09-2015
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 03-2020
Publisher: Springer Science and Business Media LLC
Date: 20-09-2022
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 09-2011
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 11-2016
Publisher: Elsevier BV
Date: 07-2017
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 03-2013
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier BV
Date: 11-2017
DOI: 10.1016/J.BIORTECH.2017.08.026
Abstract: The present study explores low-cost cathode development possibility using radial oxygen loss (ROL) of Canna indica plants and intermittent aeration (IA) for wastewater treatment and electricity generation in constructed wetland-microbial fuel cell (CW-MFC) system. Two CW-MFC microcosms were developed. Amongst them, one microcosm was planted with Canna indica plants for evaluating the ROL dependent cathode reaction (CW-MFC dependent on ROL) and another microcosm was equipped with intermittent aeration for evaluating the intermittent aeration dependent cathode reaction (CW-MFC with additional IA). The CW-MFC with additional IA has achieved 78.71% and 53.23%, and CW-MFC dependent on ROL has achieved 72.17% and 46.77% COD removal from synthetic wastewater containing glucose loads of 0.7gL
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.JENVMAN.2014.03.013
Abstract: The possibility of using membrane bioreactors (MBRs) in simultaneous nitrification-anammox-denitrification (SNAD) by considering periodic aeration cycles was investigated. Two separate reactors were operated to investigate the effect of different anammox biomass in the presence of nitrifying and denitrifying biomass on the final nitrogen removal efficiency. The results illustrated that the reactor with higher anammox biomass was more robust to oxygen cycling. Around 98% Total Nitrogen (TN) and 83% Total Organic Carbon (TOC) removal efficiencies were observed by applying one hour aeration over a four-hour cycle. Decreasing the aeration time to 30, 15, and 2 min during a four-hour cycle affected the final TN removal efficiencies. However, the effect of decreasing aeration on the TN removal efficiencies in the reactor with higher anammox biomass was much lower compared to the regular reactor. The nitrous oxide (N2O) emission was a function of aeration as well, and was lower in the reactor with higher anammox biomass. The results of q-PCR analysis confirmed the simultaneous co-existence of nitrifiers, anammox, and denitrifiers in both of the reactors. To simulate the TN removal in these reactors as a function of the aeration time, a new model, based on first order reaction kinetics for both denitrification and anammox was developed and yielded a good agreement with the experimental observations.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier
Date: 2022
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 02-2022
Publisher: Springer Science and Business Media LLC
Date: 09-06-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 12-2021
Publisher: Springer Science and Business Media LLC
Date: 07-2021
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 07-2020
Publisher: Springer Science and Business Media LLC
Date: 20-10-2022
DOI: 10.1038/S42004-022-00744-X
Abstract: Significant attempts have been made to improve the production of ion-selective membranes (ISMs) with higher efficiency and lower prices, while the traditional methods have drawbacks of limitations, high cost of experiments, and time-consuming computations. One of the best approaches to remove the experimental limitations is artificial intelligence (AI). This review discusses the role of AI in materials discovery and ISMs engineering. The AI can minimize the need for experimental tests by data analysis to accelerate computational methods based on models using the results of ISMs simulations. The coupling with computational chemistry makes it possible for the AI to consider atomic features in the output models since AI acts as a bridge between the experimental data and computational chemistry to develop models that can use experimental data and atomic properties. This hybrid method can be used in materials discovery of the membranes for ion extraction to investigate capabilities, challenges, and future perspectives of the AI-based materials discovery, which can pave the path for ISMs engineering.
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier
Date: 2020
Publisher: Elsevier BV
Date: 03-2015
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.1016/J.ENVPOL.2017.11.008
Abstract: This study investigated particle and gaseous emission factors from a large cargo vessel for her whole voyage including at berth, manoeuvring and cruising. Quantification of these factors assists in minimising the uncertainty in the current methods of exhaust gas emission factor estimation. Engine performance and emissions from the main marine engine were measured on-board while the ship was manoeuvring and cruising at sea. Emissions of an auxiliary engine working at 55% of maximum continuous rating (MCR) were measured when the ship was at actual harbour stopovers. Gaseous and particle emission factors in this study are presented in g kWh
Publisher: Elsevier BV
Date: 06-2022
Publisher: Springer Singapore
Date: 2020
Publisher: Elsevier BV
Date: 11-2012
Publisher: IOP Publishing
Date: 07-2017
Publisher: Wiley
Date: 04-2022
DOI: 10.1002/PRS.12361
Abstract: Daily operations onboard ships are very challenging due to man–machine interactions. To improve daily operational safety and to prevent losses due to machinery breakdown, effective risk management techniques need to be developed, considering various operational and environmental factors affecting the seafarers' performance. The current study explains the comparison between simulation and conventional classroom training to enhance safety in maritime operations in compromised environments. The contribution of this study lies in introducing the concept of social fidelity in simulator‐based training. This study bridges the gap between computer technology and collaborative learning activities in simulator‐based training. The result obtained through the simulation improves marine engineers' training and enhances the reliability of marine engines. This paper concludes by proposing a set of recommendations for the future design of simulator‐based training for marine engineers.
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 11-2013
Publisher: Elsevier BV
Date: 09-2020
Publisher: SAGE Publications
Date: 06-12-2011
Abstract: There has been an increasing concern on indoor air quality in recent years due to the possible harmful effects to human health. Indoor air pollution as a result of using natural gas for cooking and heating is a common health threat, particularly for women and young children. Therefore, quantification of the type and emission levels of these pollutants is necessary in order to mitigate and monitor the emissions. Computational fluid dynamics (CFDs) can be used to model airflow and dispersion within buildings of complex geometry and layout. In the present paper, a CFD analysis is performed to determine the concentration of indoor air quality for a typical one-floor building in order to determine the optimal locations of monitoring sensors. According to this study, placing the monitoring sensors based on the maximum concentrations of the in idual contaminant does not entirely overcome the problems, as the concentrations of different hazardous pollutants cannot be added. Moreover, high concentration with low duration of exposure is not a good candidate for placing the monitoring system. A risk-based methodology is proposed to determine the optimal location for the monitoring systems. Different risk management strategies are also considered as a part of the methodology to reduce the exposure risk of indoor contaminants.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 08-2013
Publisher: Elsevier BV
Date: 05-2016
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 06-2023
Publisher: Wiley
Date: 06-05-2016
DOI: 10.1002/PRS.11829
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 2020
DOI: 10.1016/J.SCITOTENV.2019.134248
Abstract: This study provides a new approach of electrode dependent anaerobic ammonium oxidation (electroanammox) in microbial fuel cell (MFC) integrated hybrid constructed wetlands (CWs). The study was carried out in three CWs, each with a horizontal flow (HF) followed by a vertical upflow (VUF). Two of the CWs were integrated with MFC, one was operated in closed circuit (CL) mode and the other in open circuit (OP) mode to determine the influence of electron transfer through an external electrical circuit. The initial nitrogen and carbon concentration were 40 mg/l and 880 mg/l respectively. The total nitrogen (TN), NH
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 09-2023
Publisher: SAGE Publications
Date: 21-04-2016
Abstract: Spray modelling is one of the most useful techniques to characterize engine performance, efficiency and emissions. The size of droplets is one of the key variables that govern the efficiency of combustion of the liquid fuel. This study aims to develop an interactive tool using MATLAB codes that identifies the droplets and their sizes from the image taken with the long distance microscope in the spray chamber setup. In this developed method, firstly the background of the image was removed and then image processing techniques, dilation and erosion, were applied to the image file to refine the image files. Subsequently, circle detection method based on the Hough Transform algorithm with the function of imfindcircles was implemented. This function of the program allows the user to identify size droplets from the image files. A statistical study was conducted with the results automated from the MATLAB program using a different set of threshold values of black and white contrast. The results showed an optimal range for the threshold (black and white) values between 40 and 70. This optimal threshold range was established based on consideration of the correct and incorrect identification of the droplets. The results indicated that the program has the ability to identify the droplet providing size and numbers. The MATLAB program was developed using MATLAB compiler and can be used at different workstations.
Publisher: Springer Science and Business Media LLC
Date: 03-03-2022
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 04-2021
Publisher: SAGE Publications
Date: 26-11-2013
Abstract: This paper proposes a new methodology that focuses on the effects of cold and harsh environments on the reliability of human performance. As maritime operations move into Arctic and Antarctic environments, decision makers must be able to recognize how cold weather affects human performance and subsequently adjusts management and operational tools and strategies. In the present work, a revised version of the Human Error Assessment and Reduction Technique (HEART) methodology has been developed to assess the effects of cold on the likelihood of human error in offshore oil and gas facilities. This methodology has been applied to post-maintenance tasks of offshore oil and gas facility pumps to investigate how management, operational, and equipment issues must be considered in risk analysis and prediction of human error in cold environments. This paper provides a proof of concept indicating that the risk associated with operations in cold environments is greater than the risk associated with the same operations performed in temperate climates. It also develops guidelines regarding how this risk can be assessed. The results illustrate that in post-maintenance procedures of a pump, the risk value related to the effect of cold and harsh environments on operator cognitive performance is twice as high as the risk value when performed in normal conditions. The present work demonstrates significant differences between human error probabilities (HEPs) and associated risks in normal conditions as opposed to cold and harsh environments. This study also highlights that the cognitive performance of the human operator is the most important factor affected by the cold and harsh conditions. The methodology developed in this paper can be used for reevaluating the HEPs for particular scenarios that occur in harsh environments since these HEPs may not be comparable to similar scenarios in normal conditions.
Publisher: Elsevier BV
Date: 08-2018
Publisher: Elsevier BV
Date: 11-2017
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 02-2018
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 05-2017
Publisher: Elsevier BV
Date: 09-2019
Publisher: Springer Science and Business Media LLC
Date: 02-2019
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier
Date: 2022
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 2019
DOI: 10.1016/J.JHAZMAT.2018.09.044
Abstract: In this paper, a risk-based optimization methodology for a maintenance schedule considering Process Variables (PVs), is developed within the framework of asset integrity assessment. To this end, an integration of Dynamic Bayesian Network, Damage Modelling and sensitivity analysis are implemented to clarify the behaviour of failure probability, considering the exogenous undisciplinable perturbations. Discrete time case is considered through measuring or observing the PVs. Decision configurations and utility nodes are defined inside the network to represent maintenance activities and their associated costs. The regression analysis is considered to model the impact of perturbations on PVs for future applications. The developed methodology is applied to a case study of Chemical Plant (Natural Gas Regulating and Metering Stations). To demonstrate the applicability of the methodology, three cases of seasonal observations of specific PV (pressure) are considered. The proposed methodology could either analyse the failure based on precursor data of PVs or obtain the optimum maintenance schedule based on actual condition of the systems.
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 02-2023
Publisher: Wiley
Date: 28-09-2016
DOI: 10.1002/PRS.11854
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 10-2016
Publisher: Elsevier BV
Date: 06-2021
Publisher: Royal Institution of Naval Architects
Date: 12-2018
DOI: 10.3940/RINA.IJME.2018.A4.500
Abstract: The objective of this study is to develop a shipping emission inventory model incorporating Machine Learning (ML) tools to estimate gaseous emissions. The tools enhance the emission inventories which currently rely on emission factors. The current inventories apply varied methodologies to estimate emissions with mixed accuracy. Comprehensive Bottom-up approach have the potential to provide very accurate results but require quality input. ML models have proven to be an accurate method of predicting responses for a set of data, with emission inventories an area unexplored with ML algorithms. Five ML models were applied to the emission data with the best-fit model judged based on comparing the real mean square errors and the R-values of each model. The primary gases studied are from a vessel measurement c aign in three modes of operation berthing, manoeuvring, and cruising. The manoeuvring phase was identified as key for model selection for which two models performed best.
Publisher: Elsevier
Date: 2020
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 08-2023
Publisher: Elsevier BV
Date: 10-2012
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 08-2021
Publisher: American Chemical Society (ACS)
Date: 03-2018
Publisher: Elsevier BV
Date: 03-2018
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 07-2020
Publisher: Elsevier BV
Date: 11-2019
Publisher: Informa UK Limited
Date: 03-07-2022
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 10-2018
DOI: 10.1016/J.MARPOLBUL.2018.08.030
Abstract: There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC
Publisher: Elsevier BV
Date: 02-2019
Publisher: Elsevier BV
Date: 11-2017
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier
Date: 2019
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 12-2023
Publisher: Elsevier BV
Date: 05-2020
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 02-2019
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 07-2021
Publisher: Springer Science and Business Media LLC
Date: 09-11-2018
Publisher: Elsevier BV
Date: 02-2018
Publisher: Elsevier BV
Date: 04-2020
DOI: 10.1016/J.JHAZMAT.2019.121722
Abstract: A constructed wetland (CW) microcosm based on conductive graphite gravel was investigated for hexavalent chromium (Cr(VI)) treatment from synthetic wastewater. Its performance was evaluated and compared with a traditional gravel-based CW microcosm. The microcosms were operated at varying initial Cr(VI) concentrations (5-20 mg/L) and hydraulic retention times (HRT) (3-7.5 h). Near complete treatment (99.9 ± 0.06 %) was achieved in the graphite-based microcosm throughout the experiment. The performance was consistently high throughout with 42.9 % improvement in Cr (VI) treatment compared to a traditional gravel microcosm. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) analysis indicated that chromium was adsorbed to microbial biofilms. Moreover, microbial ersity profiling suggested that the microbial population in both microcosms differed in ersity and communities. The results suggest that the use of conductive materials in CW significantly enhances the treatment of Cr(VI) and more importantly, allows microbial activity even at high levels of Cr(VI) in the CW.
Publisher: MDPI AG
Date: 12-01-2023
DOI: 10.3390/FIRE6010029
Abstract: Hydrogen fuel cell vehicle (HFCV) technology poses great promise as an alternative to significantly reduce the environmental impact of the transport sector’s emissions. However, hydrogen fuel cell technology is relatively new, therefore, confirmation of the reliability and safety analysis is still required, particularly for fire scenarios within confined spaces such as tunnels. This study applied the computational fluid dynamics (CFD) simulations in conjunction with probabilistic calculation methods to determine the associated thermal risk of a hydrogen jet fire in a tunnel and its dependency on scenarios with different tunnel slopes, longitudinal and transverse ventilation velocities, and fire positions. A large-scale model of 102 m in which the effects of outlined parameter variations on the severity of the fire incident were analysed. It is found that both tunnel ventilation techniques and slope were critical for the effective ejection of accumulated heat. With ventilation playing a primary role in the ejection of heat and gas and slope ensuring the stability of the ejected heat, probabilities of thermal burns were found to be reduced by up to approximately 35% with a strong suggestion of critical combinations to further reduce the dangers of hydrogen tunnel fires.
Publisher: ASME International
Date: 09-06-2017
DOI: 10.1115/1.4036832
Abstract: Modeling depth of long-term pitting corrosion is of interest for engineers in predicting the structural longevity of ocean infrastructures. Conventional models demonstrate poor quality in predicting the long-term pitting corrosion depth. Recently developed phenomenological models provide a strong understanding of the pitting process however, they have limited engineering applications. In this study, a novel probabilistic model is developed for predicting the long-term pitting corrosion depth of steel structures in marine environment using Bayesian network (BN). The proposed BN model combines an understanding of corrosion phenomenological model and empirical model calibrated using real-world data. A case study, which exemplifies the application of methodology to predict the pit depth of structural steel in long-term marine environment, is presented. The result shows that the proposed methodology succeeds in predicting the time-dependent, long-term anaerobic pitting corrosion depth of structural steel in different environmental and operational conditions.
Publisher: Elsevier BV
Date: 2020
Publisher: Elsevier BV
Date: 08-2018
Publisher: Elsevier BV
Date: 07-2020
Publisher: Springer Science and Business Media LLC
Date: 07-2021
Publisher: Wiley
Date: 24-01-2021
DOI: 10.1002/CJCE.23920
Publisher: Springer Science and Business Media LLC
Date: 07-01-2021
Publisher: Elsevier BV
Date: 08-2021
Publisher: Royal Institution of Naval Architects
Date: 09-2017
DOI: 10.3940/RINA.IJME.2017.A3.351
Abstract: A methodology for risk analysis applicable to shipping in arctic waters is introduced. This methodology uses the Bowtie relationship to represent an accident causes and consequences. It is further used to quantify the probability of a ship accident and also the related accident consequences during navigation in arctic waters. Detailed fault trees for three possible ship accident scenarios in arctic transits are developed and represented as bowties. Factors related to cold and harsh conditions and their effects on grounding, foundering, and collision are considered as part of this study. To illustrate the application of the methodology, it is applied to a case of an oil-tanker navigating on the Northern Sea Route (NSR). The methodology is implemented in a Markov Chain Monte Carlo framework to assess the uncertainties arisen from historical data and expert judgments involved in the risk analysis.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 2023
Start Date: 08-2022
End Date: 07-2023
Amount: $320,000.00
Funder: Australian Research Council
View Funded Activity