What is a key difference between deterministic analyses and PRA?

What is a key difference between deterministic analyses and PRA?

• A. Deterministic analyses are faster to compute than PRA
• B. PRA ignores multiple failures
• C. Deterministic analyses are faster to compute than PRA
• D. PRA uses only qualitative judgments

Answer: (C)

Deterministic analyses focus on a single, fixed scenario with specific inputs and produce a definite result for that scenario. PRA, on the other hand, builds a probabilistic model of the plant, accounting for initiating events, component failures, and human errors across many possible paths. It propagates uncertainties and combines probabilities through fault trees and event trees to estimate overall risk, often requiring data gathering, sensitivity studies, and sometimes Monte Carlo simulation. Because you’re solving one concrete path in a deterministic analysis, it’s usually much quicker to compute than PRA, which must explore and quantify a wide range of possible failure sequences and their likelihoods. That broader, probabilistic scope is what makes PRA more computationally intensive. The other statements aren’t accurate: PRA does not ignore multiple failures, and PRA typically uses quantitative probabilities rather than relying solely on qualitative judgments.

Deterministic analyses focus on a single, fixed scenario with specific inputs and produce a definite result for that scenario. PRA, on the other hand, builds a probabilistic model of the plant, accounting for initiating events, component failures, and human errors across many possible paths. It propagates uncertainties and combines probabilities through fault trees and event trees to estimate overall risk, often requiring data gathering, sensitivity studies, and sometimes Monte Carlo simulation.

Because you’re solving one concrete path in a deterministic analysis, it’s usually much quicker to compute than PRA, which must explore and quantify a wide range of possible failure sequences and their likelihoods. That broader, probabilistic scope is what makes PRA more computationally intensive.

The other statements aren’t accurate: PRA does not ignore multiple failures, and PRA typically uses quantitative probabilities rather than relying solely on qualitative judgments.