DesignBench-Truss

Overview

DesignBench-Truss is the benchmark split (problems 090–099) of DesignBench, a dataset for teaching and evaluating large language models on iterative structural engineering design via Tree-of-Thought reasoning.

Each problem requires minimising the mass of a 2-D pin-jointed truss structure while satisfying structural safety constraints (factor of safety ≥ 1.5 for both buckling and yielding failure modes). A finite-element analysis oracle (trussme) provides deterministic feedback after every design modification.

Task Description

Given an initial truss design with known joint positions, member cross-sections, material properties, and loading conditions, a model must produce a sequence of discrete grammar actions that transform the design into a feasible, mass-minimised structure.

Grammar Actions

Action	Signature	Description
SCALE_PARAM	SCALE_PARAM(member_id_or_all, param, factor)	Scale one parameter of one (or all) members
SCALE_MULTI_PARAM	SCALE_MULTI_PARAM([member_ids], [param:factor, ...])	Scale multiple parameters simultaneously
ADD_MEMBER	ADD_MEMBER(joint1, joint2, material, shape_type, r, t)	Add a new pipe member between two joints

Data Format

benchmark.json

Flat list of examples — one per gold trace — with the following fields:

{
  "problem_id": "auto_problem_090",
  "trace_id": "auto_problem_090_trace_0",
  "problem_text": "PROBLEM: Truss optimization ...",
  "initial_state": {
    "mass": 142.5,
    "fos_buckling": 0.31,
    "fos_yielding": 1.09,
    "deflection": 0.038,
    "is_feasible": false
  },
  "gold_action_sequence": [
    "ADD_MEMBER(5, 6, 6061_T6_Aluminum, Pipe, 0.0497, 0.0056)",
    "SCALE_PARAM(all_members, thickness, 1.28)"
  ],
  "reaches_solution": true,
  "trace_quality": 0.98
}

problems/

Raw problem JSON files containing joint positions, member topology, loads, and design constraints.

trees/

Full modification trees as JSON. Each tree contains all explored design states (nodes) and the grammar actions connecting them (edges).

traces/

Serialized gold traces — lists of node-sequences extracted from each tree.

Metrics

Metric	Description
feasibility_rate	Fraction of episodes reaching is_feasible=True
mass_reduction	(initial_mass - final_mass) / initial_mass
grammar_validity_rate	Fraction of steps with parseable grammar actions
avg_steps_to_feasibility	Mean episode length when a feasible design is found
overall_score	Weighted composite: design_correctness (0.5) + structural_validity (0.25) + reasoning_quality (0.15) + grammar_compliance (0.10)

Example Usage

import json

with open("benchmark.json") as f:
    examples = json.load(f)

print(f"Loaded {len(examples)} benchmark examples")

for ex in examples[:3]:
    print(ex["problem_id"], "->", ex["reaches_solution"],
          "actions:", len(ex["gold_action_sequence"]))

Citation

@misc{designbench2025,
  title  = {DesignBench: A Benchmark for Iterative Structural Engineering Design},
  author = {DesignBench Authors},
  year   = {2025},
  note   = {https://huggingface.co/datasets/DesignBench-Truss}
}