.. Auto-generated by scripts/generate_problem_catalog_docs.py. Do not edit by hand. Decision Problem - MSEval Spacecraft Component (High Strength) ============================================================== Choose one material for Spacecraft Component with emphasis on High Strength, using expert MSEval survey responses as the evaluation benchmark. See :doc:`../decision` for the decision family index. Quick Facts ----------- .. list-table:: :header-rows: 1 :widths: 20 80 * - Field - Value * - Problem ID - ``decision_mseval_spacecraft_component_high_strength`` * - Problem Family - decision * - Implementation - ``design_research_problems.problems.decision._mseval:MSEvalEmpiricalChoiceProblem`` * - Capabilities - ``citation-backed``, ``statement-markdown`` * - Study Suitability - none * - Tags - ``decision``, ``material-selection``, ``mseval``, ``spacecraft_component``, ``high_strength`` 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``, ``high_strength`` Statement --------- .. code-block:: markdown # Decision Problem - MSEval Spacecraft Component (High Strength) You are selecting a material for **Spacecraft Component**. Primary criterion: **High Strength**. ## 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 ---------------- .. list-table:: :header-rows: 1 :widths: 25 75 * - 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 ---------- .. list-table:: :header-rows: 1 :widths: 10 22 10 13 10 15 20 * - Key - Label - Sense - Domain - Executable - Variables - Expression * - expert_agreement - Tie-adjusted expert top-choice share - maximize - empirical-choice - yes - ``material`` - sum_i I(choice in argmax_i)/\|argmax_i\| / N Candidate Space --------------- .. list-table:: :header-rows: 1 :widths: 25 75 * - Field - Value * - Candidate Kind - empirical-choice * - Candidate Count - 9 * - Default Choice Metric - top-choice-share * - Response Count - 67 Empirical Benchmarks ~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 14 30 14 14 14 14 * - Key - Label - Top Choice Share - Mean Rating - Median Rating - Std Rating * - steel - Steel - 0.122181 - 6.8209 - 8 - 2.79027 * - aluminium - Aluminium - 0.052529 - 6.38806 - 7 - 2.43681 * - titanium - Titanium - 0.489594 - 8.61194 - 9 - 2.06673 * - glass - Glass - 0.012231 - 2.23881 - 2 - 2.16787 * - wood - Wood - 0.003524 - 1.77612 - 1 - 1.86532 * - thermoplastic - Thermoplastic - 0.009494 - 3.31343 - 3 - 2.47539 * - elastomer - Elastomer - 0.004643 - 2.10448 - 1 - 2.36217 * - thermoset - Thermoset - 0.037604 - 3.41791 - 3 - 2.87702 * - composite - Composite - 0.268201 - 7.46269 - 8 - 2.77067 Sources ------- .. list-table:: :header-rows: 1 :widths: 20 80 * - Key - Summary * - ``jain2024msevaldatasetmaterialselection`` - 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 -------------------- .. code-block:: bibtex @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}, }