Decision Problem - MSEval Spacecraft Component (Lightweight)#
Choose one material for Spacecraft Component with emphasis on Lightweight, using expert MSEval survey responses as the evaluation benchmark.
See Decision Problem Catalog for the decision family index.
Quick Facts#
Field |
Value |
|---|---|
Problem ID |
|
Problem Family |
decision |
Implementation |
|
Capabilities |
|
Study Suitability |
none |
Tags |
|
Taxonomy#
- Formulation
empirical_discrete_choice
- Design Variable Type
categorical
- Is Dynamic
no
- Orientation
engineering_practical
- Objective Mode
single
- Constraint Nature
preference-derived
- Tags
decision,material-selection,mseval,spacecraft_component,lightweight
Statement#
# Decision Problem - MSEval Spacecraft Component (Lightweight)
You are selecting a material for **Spacecraft Component**.
Primary criterion: **Lightweight**.
## Task
1. Choose **one** material from the list below.
2. Briefly justify the choice in terms of the stated criterion and likely use context.
3. Optionally note one follow-up risk or tradeoff to validate next.
## Candidate Materials
- Steel
- Aluminium
- Titanium
- Glass
- Wood
- Thermoplastic
- Elastomer
- Thermoset
- Composite
## Output Format
- Selected material:
- Justification (3-6 sentences):
- Risk or tradeoff to check next (optional):
Decision Context#
Field |
Value |
|---|---|
Decision Maker |
A designer selecting one material conceptually for a spacecraft component. |
Market Segment |
MSEval expert benchmark with 67 complete responses for this prompt. |
Decision Scope |
Choose a single candidate material from the provided materials using an empirical preference benchmark derived from MSEval survey responses. |
Objectives#
Key |
Label |
Sense |
Domain |
Executable |
Variables |
Expression |
|---|---|---|---|---|---|---|
expert_agreement |
Tie-adjusted expert top-choice share |
maximize |
empirical-choice |
yes |
|
sum_i I(choice in argmax_i)/|argmax_i| / N |
Candidate Space#
Field |
Value |
|---|---|
Candidate Kind |
empirical-choice |
Candidate Count |
9 |
Default Choice Metric |
top-choice-share |
Response Count |
67 |
Empirical Benchmarks#
Key |
Label |
Top Choice Share |
Mean Rating |
Median Rating |
Std Rating |
|---|---|---|---|---|---|
steel |
Steel |
0.007048 |
3.28358 |
3 |
2.55726 |
aluminium |
Aluminium |
0.170481 |
7.14925 |
8 |
2.29792 |
titanium |
Titanium |
0.268242 |
6.77612 |
7 |
2.91194 |
glass |
Glass |
0.006302 |
2.16418 |
1 |
2.32638 |
wood |
Wood |
0.006302 |
2.31343 |
1 |
2.56556 |
thermoplastic |
Thermoplastic |
0.092123 |
4.64179 |
5 |
3.19422 |
elastomer |
Elastomer |
0.025705 |
3.46269 |
3 |
2.81408 |
thermoset |
Thermoset |
0.017496 |
4.34328 |
4 |
2.7719 |
composite |
Composite |
0.406302 |
7.86567 |
9 |
2.29555 |
Sources#
Key |
Summary |
|---|---|
|
Yash Patawari Jain, Daniele Grandi, Allin Groom, Brandon Cramer, Christopher McComb (2024). MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models |
Raw Citation Records#
@misc{jain2024msevaldatasetmaterialselection,
title={MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models},
author={Yash Patawari Jain and Daniele Grandi and Allin Groom and Brandon Cramer and Christopher McComb},
year={2024},
eprint={2407.09719},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2407.09719},
}