A CFD-based empirical model for hazardous area extent prediction including wind effects

Nascimento, Claudemi A.; Luiz, Aurélio M.; Barros, Paloma L.; Neto, Antônio Tavernard Pereira; Alves, José Jaílson Nicácio

doi:10.1016/j.jlp.2021.104497

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…Gusti, I. Irhamah, and H. Kuswanto [24] uses Support Vector Regression (SVR) to forecast TCP throughput by using multivariate regression. Using supervised learning techniques such as random forest, Nascimento et al [25] developed a loss prediction model to estimate the likelihood of packet loss due to congestion. Predicting and reducing packet loss incidents, reducing the frequency of transmitting rate reductions, and increasing throughput are all benefits of this technology.…”

Section: Network Ecosystemmentioning

confidence: 99%

Application of Machine Learning Technologies for Transport layer Congestion Control

Dong

Yortsos

2022

JCNS

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Due to the advent of technology, humans now live in the modern age of information and data. In this form of world, different objects are interlinked to data sources, and every aspect of human’s lives are recorded in a digital form. For example, the present electronic globe has an abundance of distinct forms of data e.g., health data, social media fata, smartphone data, business data, smart city data, cybersecurity data and Internet of Things (IoT) data, including Covid-19 data. Data can be unstructured, semi-structured and structured, and this is increasing on a daily basis. Machine Learning (ML) is significantly employed in different aspects of real-life e.g., Congestion Control (CC). This paper provides an evaluation of the aspect ML employed in CC. CC has emerged as a fundamental viewpoint in communications system infrastructure in the recent years, since network operations, and network capacity have enhanced at a rapid rate.

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Section: Network Ecosystemmentioning

confidence: 99%

Application of Machine Learning Technologies for Transport layer Congestion Control

Dong

Yortsos

2022

JCNS

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Application of Machine Learning and Bayesian Optimization Techniques in the Classification of Hazardous Atmosphere Zones Based on Fluid Dynamics Computer Simulations

Neto,

Lopes,

de Lima

et al. 2024

Preprint

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Wind Impact Assessment of a Sour Gas Release in an Offshore Platform

Moscatello

Ledda

Uggenti

et al. 2022

Safety

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Complex installations that involve dangerous substances, such as oil and gas or nuclear plants, must mandatorily undergo a quantitative risk assessment (QRA) according to current regulations. This requires, among others, the simulation of hundreds of accidental scenarios, which are typically carried out using empirical tools due to their fast response. Nonetheless, since they are not able to guarantee sufficient accuracy, especially when complex geometries are involved, computational fluid dynamics (CFD) tools are increasingly used. In this work, a high-pressure accidental release of a sour gas (CH4-H2S) in an offshore platform under several wind conditions is considered. A methodology used to perform a wind sensitivity analysis via CFD, while avoiding high computational costs, is presented. The wind intensity impact on some risk-related figures of merit, such as the high lethality or irreversible injuries areas, is discussed in relation to the flammability and toxicity limits of the released mixture. The results show that even a very low amount of H2S in the released mixture can strongly affect the threat zones. A progressive decrease in the toxic and flammable volumes in the platform is observed as the wind velocity increases; nonetheless, a saturation effect appears in high wind speed scenarios.

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A CFD-based empirical model for hazardous area extent prediction including wind effects

Cited by 4 publications

References 19 publications

Application of Machine Learning Technologies for Transport layer Congestion Control

Application of Machine Learning Technologies for Transport layer Congestion Control

Application of Machine Learning and Bayesian Optimization Techniques in the Classification of Hazardous Atmosphere Zones Based on Fluid Dynamics Computer Simulations

Wind Impact Assessment of a Sour Gas Release in an Offshore Platform

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