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RiskSpectrum^® Analysis Tools (RSAT)

General Features

Analysis Tools (RSAT) is the RiskSpectrum MCS generation and calculation engine.
The MCS analysis is based on an improved version of the RSMCS algorithm. The RSMCS algorithm is a top-down algorithm using features such as fault tree structure optimization, modularisation and probabilistic cutoff. The RSMCS algorithm has been widely recognized as the fastest and most powerful existing fault tree solution algorithm.
RSMCS has been completely rewritten in the C programming language as a part of the development of the Windows version of RiskSpectrum. Compared to the earlier version of RSMCS, the new 32-bit C version has the following main features:

• An improved code structure, facilitating software maintenance and further development.
• Improved efficiency of algorithm.
• Ability to handle event tree structures. The application can handle individual sequence top events and consequence top events.
  In sequence top events, the application builds an internal sequence fault tree structure, automatically linking all fault trees included in the sequence, including the success logic.
  In consequence top events, the program builds a large OR-gate with the sequence fault trees for all sequences ending with the specified consequence as input. The application can also automatically handle linking between different event trees.
• Ability to handle exchange events, i.e. replace basic events and/or gates triggered by TRUE house events.
• Ability to handle automated CCF modelling and quantification through CCF groups.
• Ability to handle NOTed basic events and house events, NOR-gates and NAND-gates.
• Relative cutoff value in addition to an absolute cutoff. The relative cutoff is dynamically updated as a specified fraction of the sum of probabilities for currently determined MCSs (during MCS generation).
• Automatic increase of cutoff if "Too many MCS" is reached. This is repeated until the analysis is completed.
• No absolute limits in number of basic events, gates, MCS, etc.

Uncertainty Analysis

The uncertainty analysis is based on Monte-Carlo simulation. The simulation process is performed by simulating parameter uncertainty distributions. The sampled parameter values are then used in re-quantifying basic events and CCF events, and these are in turn used to re-quantify the MCS equation.

Importance Analysis

Importance calculation can be performed for:

• Individual basic events and CCF events
• CCF groups
• Parameters
• Attributes (groups of basic events sharing the same attribute)
• Basic event groups
• Components
• Systems
• Initiating events

In each case, the following importance values can be calculated:

• Fussell-Vesely
• Fractional Contribution
• Risk Reduction
• Risk Achievement

Sensitivity Analysis

Sensitivity calculation can be performed for:

• Individual basic events and CCF events
• CCF groups
• Parameters
• Attributes (groups of basic events sharing the same attribute)
• Basic event groups
• Components
• Systems
• Initiating events

In each case, the following sensitivity values can be calculated (sensitivity factor given by user):

• Sensitivity low (Top probability, frequency …) when event divided with sensitivity factor
• Sensitivity high (Top probability, frequency …) when event multiplied with sensitivity factor
• Sensitivity (Sens. High / Sens. Low)

Capabilities

Analysis Tools has no "hard" limit in number of gates, basic events, minimal cut sets (MCS), etc. The total limit is defined by the available RAM on the system running the analysis. For practical reasons, some of the maximum limits will not be determined completely dynamically at run-time, but will be read from a configuration file that can be controlled by the user. For example, the user can control the upper limit in number of MCSs.

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