# ISYE/NE 574: Methods for Probabilistic Risk Analysis of Nuclear Power Plants | UW–Madison

[View on UW Courses](https://uwcourses.com/courses/ISYE_NE_574)

## Dataset

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

### repository

twangodev/uwcourses

### schema version

6

### importer version

7

### projection id

52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07

### observed at

2026-09-07T15:55:43.033547+00:00

### built at

2026-09-10T19:50:42.743001+00:00

### courses

8951

### current instructors

5754

### limited

false

### terms

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### term

1272

### departments

| subject   | count |
| --------- | ----- |
| AAE       | 90    |
| ABT       | 20    |
| ACCTIS    | 36    |
| ACTSCI    | 14    |
| AFAERO    | 10    |
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| AFROAMER  | 71    |
| AGROECOL  | 21    |
| AMERIND   | 53    |
| ANAT\&PHY | 7     |
| ANATOMY   | 2     |
| ANESTHES  | 8     |
| ANSCI     | 57    |
| ANTHRO    | 95    |
| ART       | 125   |
| ARTED     | 10    |
| ARTHIST   | 121   |
| ASIALANG  | 129   |
| ASIAN     | 109   |
| ASIANAM   | 28    |
| ASTRON    | 38    |
| ATMOCN    | 69    |
| BIOCHEM   | 51    |
| BIOCORE   | 10    |
| BIOLOGY   | 14    |
| BIOMDSCI  | 18    |
| BME       | 66    |
| BMI       | 41    |
| BMOLCHEM  | 10    |
| BOTANY    | 69    |
| BSE       | 44    |
| C\&ESOC   | 73    |
| CBE       | 48    |
| CHEM      | 101   |
| CHICLA    | 52    |
| CIVENGR   | 133   |
| CLASSICS  | 47    |
| CNP       | 10    |
| CNSRSCI   | 50    |
| COMARTS   | 137   |
| COMPBIO   | 15    |
| COMPLIT   | 11    |
| COMPSCI   | 138   |
| COUNPSY   | 78    |
| CRB       | 19    |
| CS\&D     | 71    |
| CSCS      | 40    |
| CURRIC    | 193   |
| DANCE     | 93    |
| DERM      | 8     |
| DS        | 88    |
| DYSCI     | 35    |
| ECE       | 155   |
| ECON      | 145   |
| EDPOL     | 114   |
| EDPSYCH   | 97    |
| ELPA      | 70    |
| EMA       | 53    |
| EMERMED   | 17    |
| ENGL      | 206   |
| ENTOM     | 40    |
| ENVIRST   | 148   |
| EP        | 15    |
| EPD       | 67    |
| ESL       | 16    |
| F\&WECOL  | 60    |
| FAMMED    | 22    |
| FINANCE   | 50    |
| FOLKLORE  | 40    |
| FOODSCI   | 43    |
| FRENCH    | 63    |
| GEN\&WS   | 145   |
| GENBUS    | 72    |
| GENECSLR  | 17    |
| GENETICS  | 60    |
| GEOG      | 113   |
| GEOSCI    | 83    |
| GERMAN    | 82    |
| GLE       | 48    |
| GNS       | 38    |
| GREEK     | 27    |
| HDFS      | 41    |
| HEBR-BIB  | 13    |
| HEBR-MOD  | 10    |
| HISTORY   | 233   |
| HISTSCI   | 56    |
| HONCOL    | 13    |
| ILS       | 43    |
| INFOSYS   | 9     |
| INTEGART  | 7     |
| INTEGSCI  | 22    |
| INTER-AG  | 18    |
| INTER-HE  | 11    |
| INTER-LS  | 22    |
| INTEREGR  | 16    |
| INTLBUS   | 21    |
| INTLST    | 50    |
| ISYE      | 83    |
| ITALIAN   | 53    |
| JEWISH    | 56    |
| JOURN     | 88    |
| KINES     | 128   |
| LACIS     | 26    |
| LANDARC   | 61    |
| LATIN     | 24    |
| LAW       | 120   |
| LEGALST   | 48    |
| LINGUIS   | 35    |
| LIS       | 89    |
| LITTRANS  | 78    |
| LSC       | 52    |
| M\&ENVTOX | 7     |
| MARKETNG  | 62    |
| MATH      | 153   |
| MDGENET   | 8     |
| ME        | 130   |
| MEDHIST   | 43    |
| MEDICINE  | 60    |
| MEDIEVAL  | 32    |
| MEDPHYS   | 39    |
| MEDSC-M   | 29    |
| MEDSC-V   | 41    |
| MHR       | 68    |
| MICROBIO  | 45    |
| MILSCI    | 16    |
| MM\&I     | 22    |
| MOLBIOL   | 6     |
| MS\&E     | 59    |
| MUSIC     | 165   |
| MUSPERF   | 126   |
| NAVSCI    | 20    |
| NE        | 44    |
| NEURODPT  | 11    |
| NEUROL    | 7     |
| NEURSURG  | 4     |
| NTP       | 11    |
| NURSING   | 111   |
| NUTRSCI   | 65    |
| OBS\&GYN  | 18    |
| OCCTHER   | 39    |
| ONCOLOGY  | 14    |
| OPHTHALM  | 5     |
| OTM       | 43    |
| PATH      | 34    |
| PATH-BIO  | 29    |
| PEDIAT    | 26    |
| PHARMACY  | 31    |
| PHILOS    | 77    |
| PHMCOL-M  | 11    |
| PHMPRAC   | 45    |
| PHMSCI    | 60    |
| PHYASST   | 37    |
| PHYSICS   | 88    |
| PHYSIOL   | 3     |
| PHYTHER   | 37    |
| PLANTSCI  | 52    |
| PLPATH    | 35    |
| POLISCI   | 192   |
| POPHLTH   | 58    |
| PORTUG    | 33    |
| PSYCH     | 101   |
| PSYCHIAT  | 22    |
| PUBAFFR   | 54    |
| PUBLHLTH  | 23    |
| RADIOL    | 11    |
| REALEST   | 41    |
| RELIGST   | 90    |
| RHABMED   | 9     |
| RMI       | 24    |
| RP\&SE    | 102   |
| S\&APHM   | 17    |
| SCANDST   | 73    |
| SLAVIC    | 89    |
| SOC       | 149   |
| SOCWORK   | 87    |
| SOILSCI   | 46    |
| SPANISH   | 83    |
| SRMED     | 21    |
| STAT      | 94    |
| STDYABRD  | 52    |
| STS       | 8     |
| SURGERY   | 25    |
| SURGSCI   | 33    |
| THEATRE   | 91    |
| URBRPL    | 60    |
| UROLOGY   | 5     |
| ZOOLOGY   | 89    |

## course

### run id

20260907T155543-ce3781c4

### semester

1272

### observed at

2026-09-07 15:55:43.033547+00:00

### record version id

3892c871a430b23fa924072b78472eb4ce574e48cd25c6acce0e34c9f7c148c6

### course id

ISYE/NE 574

### course uid

course\_beaec3fa5cba8f7ea7379188

### catalog version id

9c9ca17a50b6eccb8239f8dbf0c352c7b593e574724255f3048f837d3a2c6358

### course number

574

### subjects

* ISYE
* NE

### title

METHODS FOR PROBABILISTIC RISK ANALYSIS OF NUCLEAR POWER PLANTS

### description

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.

### requirements text

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

### credit offering ids

None recorded.

### llm job id

enrich-8b774950c2b6adfdc46d1b82

### llm output id

8a87540be6ccf8207488640bc86dfb304e23f86ce3a81077091dc5273aa85cc4

### llm model

nvidia/Qwen3.6-35B-A3B-NVFP4

### llm model revision

1355db6a052410cfd62085d94b58866fd0f2c3c5

### llm task version

14

### llm search status

valid

### llm summary

This course teaches methods for probabilistic risk analysis of engineered systems, focusing on fault trees, event trees, Bayesian data analysis, and risk management in the nuclear power industry.

### llm topics

* Risk and reliability analysis in the nuclear power industry.
* Fault tree and event tree analysis.
* Bayesian data analysis.
* Probabilistic risk management.

### llm skills

* Risk and reliability analysis, fault and event tree modeling, Bayesian data analysis, and probabilistic risk management.

### llm assumed background

* Probability theory, mathematical statistics, and statistical inference.

### llm search phrases

* probabilistic risk analysis nuclear
* fault tree analysis
* event tree analysis
* Bayesian data analysis
* reliability engineering
* risk management

### llm requirements status

needs\_review

### llm student summary status

valid

### llm experience status

insufficient\_evidence

### catalog variants

None recorded.

### student summary

#### context hash

fdc10048319d498ae304a3cdaa09fa3c4b5cb46b7f7934f4966eb1c66fdadc6e

#### course id

ISYE/NE 574

#### current instructors

None recorded.

#### difficulty workload

None recorded.

#### errors

None recorded.

#### historical context

None recorded.

#### message

No course-specific reviews available

#### offered

false

#### profile hash

5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02

#### quick take

Recent recorded grades — Spring 2016: 3.56 GPA, 75.0% A/AB (n=16 letter grades); Spring 2018: 3.29 GPA, 58.3% A/AB (n=12 letter grades); Spring 2025: 3.85 GPA, 90.0% A/AB (n=10 letter grades).

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```

#### student experience

None recorded.

#### task hash

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#### teaching history

None recorded.

#### term id

1272

#### term name

2026 Fall

#### version

2

### requirements

#### nodes

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```

#### notes

* STAT 224 is referenced in requirements but course details are unavailable in the provided snapshot, requiring manual review.

#### root

n0

#### status

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### instructors

None recorded.

### offerings

None recorded.

### sections

None recorded.

### grade instructors

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```

### grades

```json
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    "total": 0,
    "source_aliases": [
      "ISYE/NE 574"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "ISYE/NE 574",
    "course_uid": "course_beaec3fa5cba8f7ea7379188",
    "term_id": "1254",
    "term_name": "Spring 2025",
    "instructors": [
      "Juliana Pacheco Duarte"
    ],
    "a": 8,
    "ab": 1,
    "b": 1,
    "bc": 0,
    "c": 0,
    "d": 0,
    "f": 0,
    "satisfactory": 0,
    "unsatisfactory": 0,
    "credit": 0,
    "no_credit": 0,
    "passed": 0,
    "incomplete": 0,
    "no_work": 0,
    "not_reported": 0,
    "other": 0,
    "total": 10,
    "source_aliases": [
      "ISYE/NE 574"
    ]
  }
]
```

### statistics

#### gpa

3.5

#### graded

81

#### counts

* 31
* 27
* 18
* 4
* 0
* 1
* 0

### grade conflicts

None recorded.

### evidence

#### history

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_beaec3fa5cba8f7ea7379188-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_beaec3fa5cba8f7ea7379188-0.json)

#### traces

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_beaec3fa5cba8f7ea7379188-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_beaec3fa5cba8f7ea7379188-0.json)

#### results

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_beaec3fa5cba8f7ea7379188-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_beaec3fa5cba8f7ea7379188-0.json)

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

## context

### all

#### term



#### gpa

3.5

#### count

81

#### university

##### size

3234

##### gpa Percentile

31

##### count Percentile

39

##### median Count

108

##### histogram

| range   | count | current |
| ------- | ----- | ------- |
| 0.0–0.4 | 0     | false   |
| 0.4–0.8 | 0     | false   |
| 0.8–1.2 | 0     | false   |
| 1.2–1.6 | 0     | false   |
| 1.6–2.0 | 0     | false   |
| 2.0–2.4 | 0     | false   |
| 2.4–2.8 | 18    | false   |
| 2.8–3.2 | 333   | false   |
| 3.2–3.6 | 983   | true    |
| 3.6–4.0 | 1900  | false   |

#### departments

```json
[
  {
    "subject": "ISYE",
    "comparison": {
      "size": 48,
      "gpaPercentile": 21,
      "countPercentile": 30,
      "medianCount": 144.5,
      "histogram": [
        {
          "range": "0.0–0.4",
          "count": 0,
          "current": false
        },
        {
          "range": "0.4–0.8",
          "count": 0,
          "current": false
        },
        {
          "range": "0.8–1.2",
          "count": 0,
          "current": false
        },
        {
          "range": "1.2–1.6",
          "count": 0,
          "current": false
        },
        {
          "range": "1.6–2.0",
          "count": 0,
          "current": false
        },
        {
          "range": "2.0–2.4",
          "count": 0,
          "current": false
        },
        {
          "range": "2.4–2.8",
          "count": 0,
          "current": false
        },
        {
          "range": "2.8–3.2",
          "count": 3,
          "current": false
        },
        {
          "range": "3.2–3.6",
          "count": 14,
          "current": true
        },
        {
          "range": "3.6–4.0",
          "count": 31,
          "current": false
        }
      ]
    }
  },
  {
    "subject": "NE",
    "comparison": {
      "size": 18,
      "gpaPercentile": 41,
      "countPercentile": 47,
      "medianCount": 84,
      "histogram": [
        {
          "range": "0.0–0.4",
          "count": 0,
          "current": false
        },
        {
          "range": "0.4–0.8",
          "count": 0,
          "current": false
        },
        {
          "range": "0.8–1.2",
          "count": 0,
          "current": false
        },
        {
          "range": "1.2–1.6",
          "count": 0,
          "current": false
        },
        {
          "range": "1.6–2.0",
          "count": 0,
          "current": false
        },
        {
          "range": "2.0–2.4",
          "count": 0,
          "current": false
        },
        {
          "range": "2.4–2.8",
          "count": 0,
          "current": false
        },
        {
          "range": "2.8–3.2",
          "count": 2,
          "current": false
        },
        {
          "range": "3.2–3.6",
          "count": 10,
          "current": true
        },
        {
          "range": "3.6–4.0",
          "count": 6,
          "current": false
        }
      ]
    }
  }
]
```

### terms

#### 1084

##### term

1084

##### gpa

3.4285714285714284

##### count

14

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

#### 1114

##### term

1114

##### gpa

3.526315789473684

##### count

19

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

#### 1144

##### term

1144

##### gpa

3.35

##### count

10

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

#### 1164

##### term

1164

##### gpa

3.5625

##### count

16

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

#### 1184

##### term

1184

##### gpa

3.2916666666666665

##### count

12

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

#### 1254

##### term

1254

##### gpa

3.85

##### count

10

##### departments

| subject | comparison |
| ------- | ---------- |
| ISYE    |            |
| NE      |            |

### benchmarks

#### all

##### school

###### size

3234

###### gpa

3.6236249482266465

###### top Share

79.64381373307086

###### count

108

##### ISYE

###### size

48

###### gpa

3.67254991747504

###### top Share

82.69095277405928

###### count

144.5

##### NE

###### size

18

###### gpa

3.5125818992144104

###### top Share

73.23365931321685

###### count

84

#### terms

##### 1084

###### school

###### size

720

###### gpa

3.3670742938849725

###### top Share

63.42064564712246

###### count

70

###### ISYE

###### size

12

###### gpa

3.539479209717092

###### top Share

78.21357214803776

###### count

39.5

##### 1094

###### school

###### size

758

###### gpa

3.3891454428111527

###### top Share

64.36369814389255

###### count

71

###### ISYE

###### size

12

###### gpa

3.4056079638285452

###### top Share

65.2521379730913

###### count

39

##### 1114

###### school

###### size

804

###### gpa

3.3696004653806844

###### top Share

64.0389334741844

###### count

68

###### ISYE

###### size

11

###### gpa

3.412841793537643

###### top Share

66.98646701950561

###### count

44

##### 1144

###### school

###### size

878

###### gpa

3.4092443327803017

###### top Share

65.95978235963416

###### count

64

###### ISYE

###### size

14

###### gpa

3.4927104441409336

###### top Share

71.50317287737518

###### count

52

##### 1164

###### school

###### size

965

###### gpa

3.46491230798535

###### top Share

69.92376287143657

###### count

68

###### ISYE

###### size

19

###### gpa

3.629939118306125

###### top Share

80.5561261302253

###### count

49

##### 1184

###### school

###### size

1010

###### gpa

3.47925290354517

###### top Share

70.86270937115944

###### count

68

###### ISYE

###### size

22

###### gpa

3.5566129214689735

###### top Share

75.3813579514971

###### count

57

##### 1234

###### school

###### size

1188

###### gpa

3.5799441677552393

###### top Share

77.18256448537606

###### count

65

###### ISYE

###### size

24

###### gpa

3.6495043911288954

###### top Share

80.48020872988452

###### count

53

##### 1254

###### school

###### size

1289

###### gpa

3.6126423469389106

###### top Share

79.48050408754871

###### count

66

###### ISYE

###### size

22

###### gpa

3.6580253054677003

###### top Share

83.06204049789541

###### count

58

## instructor Trends

```json
[
  {
    "uid": "instructor_3bfb9698df128aba89bf336b",
    "name": "VICKI BIER",
    "count": 71,
    "terms": [
      {
        "term": "1084",
        "count": 14,
        "sections": 1,
        "gpa": 3.4285714285714284
      },
      {
        "term": "1114",
        "count": 19,
        "sections": 1,
        "gpa": 3.526315789473684
      },
      {
        "term": "1144",
        "count": 10,
        "sections": 1,
        "gpa": 3.35
      },
      {
        "term": "1164",
        "count": 16,
        "sections": 1,
        "gpa": 3.5625
      },
      {
        "term": "1184",
        "count": 12,
        "sections": 1,
        "gpa": 3.2916666666666665
      }
    ]
  },
  {
    "uid": "instructor_b652eba667400cb17dcb1c52",
    "name": "JULIANA PACHECO DUARTE",
    "count": 10,
    "terms": [
      {
        "term": "1254",
        "count": 10,
        "sections": 1,
        "gpa": 3.85
      }
    ]
  }
]
```

## following

None recorded.
