METHODS FOR PROBABILISTIC RISK ANALYSIS OF NUCLEAR POWER PLANTS

Name: METHODS FOR PROBABILISTIC RISK ANALYSIS OF NUCLEAR POWER PLANTS
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Rating: 4.3 (83 reviews)

ISYE/NE 574

과목 설명

Methods for risk and reliability analysis of engineered systems, particularly as applied in the nuclear power industry. Fault trees and event trees, Bayesian data analysis, probabilistic risk management. Some familiarity with nuclear plant safety systems is helpful, but not required.

선수과목

(MATH/STAT 309 , STAT 311 , 224, STAT 324 , or MATH/STAT 431 ), graduate/professional standing, or member of Engineering Guest Students

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

미보고

평점

3.85

12.72% 과거 데이터 대비

수료율

100%

3.75% 과거 데이터 대비

A 비율

80%

114.19% 과거 데이터 대비

학급 규모

-3.61% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

INTRODUCTION TO DECISION ANALYSIS

ISYE 516

Overview of modeling techniques and methods used in decision analysis, including multiattribute utility models, decision trees, and Bayesian models. Psychological components of decision making are discussed. Elicitation techniques for model building are emphasized. Practical applications through real world model building are described and conducted.

ADVANCED NUCLEAR POWER ENGINEERING

NE 550

Analysis of nuclear systems for the production of useful power. Emphasis: thermodynamic cycles, reactor types, coupling of reactor and power plant, design synthesis, and plant economics.

SOCIETAL RISK MANAGEMENT OF TECHNOLOGICAL HAZARDS

C&ESOC/ISYE/NE/SOC 708

Issues involved in decision-making regarding technological risks and risk management in areas such as nuclear power, hazardous waste disposal, and pollution control. Risk perception and cognitive biases; risk analysis and decision analysis; political issues in risk management; regulatory mechanisms; and risk communication. Selected case studies.

NUCLEAR REACTOR DESIGN

NE 412

Reactor design projects, reactor hazards, economics.

STOCHASTIC MODELING TECHNIQUES

ISYE 624

Techniques for modeling systems in which uncertainty is an essential factor. Emphasizes why, how and when techniques can or cannot be applied, rather than their mathematical derivation. Case studies and/or examples from such areas as logistics, production, and service industries.