AST inspection software - Storage tank inspection - Synergi Plant - RBI AST
With our AST inspection software, storage tank farms are able to substantially reduce costs. Synergi Plant's risk-based inspection (RBI) software solution, supporting EEMUA 159 and API 581, is the key to optimizing AST inspection strategy
AST inspection software from DNV GL
Atmospheric storage tanks (ASTs) in the oil, chemical and transportation industry are used to store flammable and toxic liquids, and must be inspected at regular intervals. Their content might be kept under atmospheric temperature and pressure but can also be refrigerated. AST leaks can cause serious environmental problems if they reach surface or underground waters. Floor leaks may go undetected over long periods and can cause serious contamination of soil or sub-surface water. Rapid floor failure or catastrophic shell failure are rare events but they do occur and can have extremely serious consequences. Clean-up of the ground, groundwater and surface water are very costly operations.
The main objective of the risk based inspection (RBI) methodology for AST inspection is to provide the basis for managing storage tank inspection intervals and methods and coverage through risk assessment.
API 580 is a recommended practice developed by the American Petroleum Institute (API) that outlines the basic elements for developing, implementing and maintaining an RBI program for AST inspection. API RP 581 describes a specific quantitative RBI methodology with full details: data tables, algorithms, equations, and models. The essential idea of RBI is to design an optimized inspection program that can reduce the risk of equipment failures and possibly reduce inspection and maintenance costs without compromising safety.
It is known that a large percentage of the total unit risk will be concentrated in a relatively small percent of the storage tank equipment items. From all equipment items that are competing for attention, the inspection plan will focus on those components with the highest risk. As the process plant changes with ongoing operations, AST inspection priorities and frequencies will be guided by the RBI process.
Goals for AST inspection:
- Define, quantify and rank the risk of process equipment failure to target the most important elements in a process plant
- Give the ability to review safety, environmental, and business-interruption risks in an integrated, cost-effective manner
- Systematically reduce the likelihood by allocating inspection resources to high risk equipment
Storage tank inspection software
DNV GL’s Synergi Plant – RBI AST inspection software is being used by tank storage farms to optimize storage tank inspection strategies. Storage tank farms spend between USD 2 and 3 million on each storage tank refurbishment, which can decommission a tank for 12 to 18 months during repairs and repainting. AST inspections and storage tank refurbishment should be done regularly, but as they can have environmental consequences (toxic substances are released when the tank is opened) and can also represent a danger to workers, it is important that refurbishment is done when needed, not before. Some DNV GL customers have used the risk-based inspection methodology of Synergi Plant to improve AST maintenance strategy to an optimum level that reduces both costs and risk levels.
With Synergi Plant – RBI AST, users can run different scenarios on the computer, quantifying influences AST of inspections as well as operation and design parameters. Synergi Plant - RBI software includes methods for semi-quantitative and quantitative RBI. The AST inspection software helps to decide how and when to do storage tank inspections and subsequent repairs. It offers a detailed calculation of the consequence of failure, the probability of failure, financial risk, and AST inspection optimization with quantitative modules.
EEMUA 159 and API 581 methodologies in Synergi Plant
The software enables users to evaluate and justify AST inspection budgets and set storage tank inspection targets using standard and user-definable risk matrices.