CHE6020N02: Quantitative Risk Analysis

Training Provider: SINGAPORE INSTITUTE OF TECHNOLOGY
Course Reference: TGS-2023022011
S$720
Original: S$2,400
Save S$1,680

About This Course

- Overview of consequence modelling
- Introduction to consequence modelling software using ALOHA®
- Using the software to set up the study, scenario, meteorology and isopleth limits
- Event tree analysis
- Inputs required for QRA studies: Information relating to the installation; release of source information; hazardous substance information; industrial hygiene and toxic data; equipment reliability data; meteorological data and receptor information
- Event tree analyses to estimate frequencies and/or likelihoods of accidents. Applies plant-specific experience, industry data, and appropriate calculation methods to estimate the frequency and/or likelihood of those accidents
- Acceptability of risks (criteria for Europe, Hong Kong, Singapore and Malaysia)

What You'll Learn

Quantitative Risk Analysis (QRA) is a formalised specialist method for calculating numerical individual, societal, (employee and public) risk level values for comparison with regulatory risk criteria.

Satisfactory demonstration of acceptable risk levels is often a requirement for approval of major hazard plant construction plans, including transmission pipelines, offshore platforms and liquefied natural gas (LNG) storage and import sites.

Each demonstration must be reviewed periodically to show that risks are controlled and reduced to an acceptable level according to applicable legislation and internal company governance requirements.

Risk evaluation can also help the decision-making process, in comparing the risks involved in alternative processes or layouts, and optimising expenditure to improve safety.

QRA helps to identify and evaluate possible accidental events, including their causes and consequences, and provides a basis for emergency preparedness and land use planning.

Modelling of consequences from major hazard such as fires, explosions and toxic clouds is an important part of risk assessments and is normally done by applying a wide range of models, from low-complexity empirical models to advanced computational fluid dynamics (CFD) models.

Entry Requirements

Minimum engineering degree or diploma with 2 years of working experience

Course Details

Duration 24 hours
Language English
Training Commitment Not specified
Total Enrolled 51 students
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