Fall 2026

Advanced Topics in Finite Elements

Advanced finite element methods for linear and nonlinear media, covering stress, heat, fluid, and vibration analysis.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Spring 2022: 3.83 GPA, 88.9% A/AB (n=9 letter grades); Spring 2024: 4.00 GPA, 100.0% A/AB (n=14 letter grades); Spring 2026: 4.00 GPA, 100.0% A/AB (n=25 letter grades).

Grade history

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average GPA
letter grades
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AB
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
EMA 705

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Prerequisite text tree
  • Graduate/professional standing

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Student experience

the class

Recent recorded grades — Spring 2022: 3.83 GPA, 88.9% A/AB (n=9 letter grades); Spring 2024: 4.00 GPA, 100.0% A/AB (n=14 letter grades); Spring 2026: 4.00 GPA, 100.0% A/AB (n=25 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Stress analysis, heat transfer, and fluid dynamics
  • Vibration and transient analysis
  • Weighted residual methods
  • Material and geometric nonlinearity and nonlinear iteration

Skills

  • Applying finite element methods to stress, heat, and fluid problems.
  • Performing vibration and transient analysis.
  • Utilizing weighted residual methods.
  • Handling material and geometric nonlinearity with iteration methods.

Grades

Latest available · Spring 2026— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

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AB
B
BC
C
D
F

Grades over time

Through Spring 2026

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Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "ca1cf2a90b295851fbb616ac5ee706145b6c66dd2c6ba9ec83f845b3803cc538",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}