Process accident prediction using Bayesian network based on IT2Fs and Z-number: A case study of spherical tanks.

This study aimed to propose a novel method for dynamic risk assessment using a Bayesian network (BN) based on fuzzy data to decrease uncertainty compared to traditional methods by integrating Interval Type-2 Fuzzy Sets (IT2FS) and Z-numbers. A bow-tie diagram was constructed by employing the System Hazard Identification, Prediction, and Prevention (SHIPP) approach, the Top Event Fault Tree, and the Barriers Failure Fault Tree. The experts then provided their opinions and confidence levels on the prior probabilities of the basic events, which were then quantified utilizing the IT2FS and combined using the Z-number to reduce the uncertainty of the prior probability. The posterior probability of the critical basic events (CBEs) was obtained using the beta distribution based on recorded data on their requirements and failure rates over five years. This information was then fed into the BN. Updating the BN allowed calculating the posterior probability of barrier failure and consequences. Spherical tanks were used as a case study to demonstrate and confirm the significant benefits of the methodology. The results indicated that the overall posterior probability of Consequences after the failure probability of barriers displayed an upward trend over the 5-year period. This rise in IT2FS-Z calculation outcomes exhibited a shallower slope compared to the IT2FS mode, attributed to the impact of experts' confidence levels in the IT2FS-Z mode. These differences became more evident by considering the 10-4 variance compared to the 10-5. This study offers industry managers a more comprehensive and reliable understanding of achieving the most effective accident prevention performance.

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection.

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer's condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents.

A glance of coupled water and wastewater treatment systems based on microbial fuel cells.

Microbial fuel cell (MFC) is a variant of the bioelectrochemical system that uses microorganisms as biocatalysts to generate bioenergy by oxidizing organic matter. Due to its two-prong feature of simultaneously treating wastewater and generating electricity, it has drawn extensive interest by scientific communities around the world. However, the pollution purifying capacity and power production of MFC at the laboratory scale have tended to remain steady, and there have been no reports of a performance breakthrough. In recent years, research related to MFC has demonstrated a new trend, namely the coupling of MFC with other wastewater treatment technologies to create a 1 + 1 > 2 impact. MFC-based coupling/hybrid technologies such as sediment MFC (SMFC), constructed wetland MFC (CW-MFC), membrane bioreactor MFC (MBR-MFC), microbial desalination cell (MDC), and MFC coupled nutrient recovery technology, etc. have been increasingly studied. Therefore, this review aims to overview these already-emerging MFC coupling technologies and explores their development trends and challenges to serve as a guide for determining priority research topics in this area. Among these MFC-based coupling/hybrid technologies, literature seems to support that CW-MFC is a good example of integrated MFC technology where CWs are already employed at the field level for wastewater treatment application. MFC-Electroflocculation and MBR-MFCs are typical emerged hybrid systems to own promising potential. However, scalability and practical application potential of these integrated technologies are the challenge towards their reality except for ideal performance in small scale trials.

Materials discovery of ion-selective membranes using artificial intelligence.

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.

Interrelation between sulphur and conductive materials and its impact on ammonium and organic pollutants removal in electroactive wetlands.

This investigation is the first of its kind to evaluate the interrelation of sulphate (SO42-) with conductive materials as well as their individual and synergetic effects on the removal of ammonium and organic pollutants in electroactive wetlands, also known as constructed wetland (CW) - microbial fuel cell (MFC). The role of MFC components in CW was investigated to treat the sulphate containing wastewater under a long-term operation without any toxicity build-up in the system. A comparative study was also performed between CW-MFC and CW, where sulphate containing wastewater (S-replete) and without sulphate wastewater (S-deplete) was assessed. The S-replete showed high NH4+ removal than the S-deplete, and the requesnce of removal was: CW-MFC-replete>CW-MFC-deplete>CW-replete>CW-deplete. The chemical oxygen demand (COD) removal was high in the case of CW-MFC-replete, and the sequence of removal was CW-MFC-replete>CW-MFC-deplete>CW-deplete>CW-replete. X-ray photon spectroscopic study indicates 0.84% sulphur accumulation in CW-MFC-replete and 2.49% in CW-replete, indicating high sulphur precipitation in CW without the MFC component. The high relative abundance of class Deltaproteobacteria (7.3%) in CW-MFC-replete along with increased microbial diversity (Shannon index=3.5) rationalise the symbiosis of sulphate reducing/oxidising microbes and its impact on the treatment performance and electrochemical activity.

Influence of applied potential on treatment performance and clogging behaviour of hybrid constructed wetland-microbial electrochemical technologies.

A two-stage hybrid Constructed Wetland (CW) integrated with a microbial fuel cell (MFC), and microbial electrolysis cell (MEC) has been assessed for treatment performance and clogging assessment and further compared with CW. The CW-MEC was operated with applied potential to the working electrode and compared with the performance of naturally adapted redox potential of the CW-MFC system. A complex synthetic municipal wastewater was used during the study, which was composed of trace metals, organics, inorganics, and dye. The study demonstrated that providing a constant potential to the working electrode in CW-MEC has resulted in high treatment performance and reduced sludge generation. The maximum chemical oxygen demand (COD), ammonium (NH4+), and phosphate (PO43-) removal achieved during treatment by CW-MEC at 24 h hydraulic retention time was 89 ± 6%, 72 ± 6% and 93 ± 2%, respectively. ICP-MS results indicated that trace metal removals were also higher in CW-MEC than in CW alone (p < 0.05). At the end of the experiment, significant volumetric change (total volume of the microcosm) occurred in CW (1.3 L), which indicates high sludge generation, whereas it was lesser in CW-MEC (0.3 L) and in CW-MFC (0.5 L). Further, Energy Dispersive X-ray (EDX) spectroscopy results indicated low levels of metal precipitation in the CW-MEC system. Based on the Shannon diversity index, the CW-MEC was assessed to be characterised by high species richness and diversity. The observations from this study indicate that the applied potential at the working electrode has a significant impact on treatment performance and clogging behaviour of the system.

A review on the contribution of electron flow in electroactive wetlands: Electricity generation and enhanced wastewater treatment.

In less than a decade, bioelectrochemical systems/microbial fuel cell integrated constructed wetlands (electroactive wetlands) have gained a considerable amount of attention due to enhanced wastewater treatment and electricity generation. The enhancement in treatment has majorly emanated from the electron transfer or flow, particularly in anaerobic regions. However, the chemistry associated with electron transfer is complex to understand in electroactive wetlands. The electroactive wetlands accommodate diverse microbial community in which each microbe set their own potential to further participate in electron transfer. The conductive materials/electrodes in electroactive wetlands also contain some potential, due to which, several conflicts occur between microbes and electrode, and results in inadequate electron transfer or involvement of some other reaction mechanisms. Still, there is a considerable research gap in understanding of electron transfer between electrode-anode and cathode in electroactive wetlands. Additionally, the interaction of microbes with the electrodes and understanding of mass transfer is also essential to further understand the electron recovery. This review mainly deals with the electron transfer mechanism and its role in pollutant removal and electricity generation in electroactive wetlands.

Enhanced chromium(VI) treatment in electroactive constructed wetlands: Influence of conductive material.

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 ±â€¯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 diversity profiling suggested that the microbial population in both microcosms differed in diversity 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.

Electrode dependent anaerobic ammonium oxidation in microbial fuel cell integrated hybrid constructed wetlands: A new process.

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), NH4+-N, TOC and COD removal achieved in CW-MFC-CL were 90.0 ±â€¯1.15%, 94.4 ±â€¯0.75%, 64.8 ±â€¯3.0% and up to 99.5 ±â€¯3.4%, respectively. The TN and NH4+-N removal in CW-MFC-CL was 20.0% and 13.6% higher than normal CW. Maximum current density achieved in CW-MFC-HF was of 75 mA/m3 and in CW-MFC-VUF was 156 mA/m3. Furthermore, the study revealed that even at low microbiological biomass, an MFC integrated CW operating in closed circuit gave higher removal of NH4+-N and COD than the normal CW and open circuit CW-MFC. Microbiological analysis shows the presence of already known nitrifier and denitrifer which indicates their role in electrode dependent nitrogen removal.

Multi-level optimization of maintenance plan for natural gas system exposed to deterioration process.

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.

Human Error Probability Assessment During Maintenance Activities of Marine Systems.

BACKGROUND: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man-machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. METHODS: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. RESULTS: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. CONCLUSION: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue) or external (i.e., environmental and operational conditions such as weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress) factors.

An ecological risk assessment model for Arctic oil spills from a subsea pipeline.

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 (PEC95%) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC5%) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level.

On-board measurements of particle and gaseous emissions from a large cargo vessel at different operating conditions.

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-1 or # kWh-1, and compared with previous studies. Results showed that the SO2 emission factor is higher than that of previous studies due to the high sulphur content of the fuel used. The particle number size distributions showed only one mode for different operating conditions of the ship, with a peak at around 40-50 nm, which was dominated by ultrafine particles. Emission factors of CO, HC, PM and PN observed during ship manoeuvring were much higher than that of those recorded at cruising condition. These findings highlight the importance of quantification and monitoring ship emissions in close proximity to port areas, as they can have the highest impact on population exposure.

Performance assessment of aeration and radial oxygen loss assisted cathode based integrated constructed wetland-microbial fuel cell systems.

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-1and 2.0gL-1, respectively. The maximum power density of 31.04mWm-3 and 19.60mWm-3 was achieved in CW-MFC with additional IA and CW-MFC dependent on ROL, respectively.

Effects of cold environments on human reliability assessment in offshore oil and gas facilities.

OBJECTIVE: This paper proposes a new methodology that focuses on the effects of cold and harsh environments on the reliability of human performance. BACKGROUND: 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. METHOD: 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. RESULTS: 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. CONCLUSION: 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. APPLICATION: 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.

Laboratory study of nitrification, denitrification and anammox processes in membrane bioreactors considering periodic aeration.

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.