LIVEdataset aec-bench@releasetasks 552models 18disciplines 5last submission … · built …

civilwith-tool

Thermal Stress Calculation

Computes the longitudinal thermal stress and force in continuously welded rail (CWR) using sigma = E * alpha * delta_T. Critical for managing rail buckling risk in hot conditions and rail pull-apart risk in cold conditions, per AREMA Chapter 5 and ARTC ETS-05-00.

with-tool: The model is given an executable Python calculator script.

Standards

AREMA MRE Chapter 5 ARTC ETS-05-00 UIC 720 R

How this task is generated

One template produces many comparable benchmark tasks while keeping the scoring contract fixed.

01
Template
The reusable contract shown on this page.
02
Scenario
An archetype and site context are sampled.
03
Difficulty tier
Inputs may be hidden at harder tiers.
04
Task prompt
The model responds with the declared outputs.

Parameters

Inputs the model receives, and the outputs it is scored on.

Inputs

4 inputs

Always given

Included directly in every task prompt.

Rail area
rail_area_mm2
Rail cross-sectional area A
4000 – 9000 mm²
Temperature change
temperature_change_c
Temperature change from neutral temperature ΔT = T_rail − T_neutral
-50 – 50 °C

Derived from scenario

Sampled from the scenario and inferable from its description.

Thermal expansion coeff micro per c
thermal_expansion_coeff_micro_per_c
Coefficient of linear thermal expansion α
Derived from the archetype scenario. Hidden at hard difficulty.
1 – 15 ×10⁻⁶ per °C
Elastic modulus
elastic_modulus_mpa
Modulus of elasticity E of rail steel
Derived from the archetype scenario. Hidden at hard difficulty.
195000 – 215000 MPa

Scored outputs

3 outputs

Thermal stress mpa

thermal_stress_mpa

Thermal stress magnitude σ (MPa)

Scores if within ±3% of the reference value.

Thermal force kn

thermal_force_kn

Thermal force magnitude F (kN)

Scores if within ±3% of the reference value.

Stress state

stress_state

Stress state: 1.0 = compression, -1.0 = tension, 0.0 = neutral

Scores if within ±1% of the reference value.

Difficulty

Each template is sampled at three tiers. Harder tiers may hide inputs, forcing the model to infer them from the scenario description.

easy

All inputs given

All parameters given, moderate temperature changes on mainline corridors

medium

All inputs given

All parameters given, any corridor type including extreme inland and alpine conditions

hard

Some inputs hidden

Material properties hidden — agent must infer E and α for standard rail steel from engineering knowledge

Hidden inputs

Thermal expansion coeff micro per cthermal_expansion_coeff_micro_per_c
Elastic modulus mpaelastic_modulus_mpa

Prompt replacement text

The rail is standard carbon-manganese rail steel on a {{ archetype.description }} ({{ archetype.site_context }})

Task bundle

The exact instruction and parameter contract used to generate this task, pinned to the published library source.

/workspace

instruction.md
thermal-stress-calculation_calc.py

Teal lines show Jinja input conditions, not task visibility policy. A line renders only when that input or tool is visible.

1You are a senior civil engineer specializing in railway track engineering and continuously welded rail (CWR) design.2 3## Problem4 5Determine the thermal stress, thermal force, and stress state (compression or tension) in a continuously welded rail due to temperature change from the neutral (stress-free) temperature.6 7## Given8 9| Parameter | Value | Unit |10|-----------|-------|------|11| Rail cross-sectional area (A) | {{ rail_area_mm2 }} | mm² |12| Temperature change from neutral (ΔT) | {{ temperature_change_c }} | °C |13{% if thermal_expansion_coeff_micro_per_c is defined %}14| Coefficient of thermal expansion (α) | {{ thermal_expansion_coeff_micro_per_c }} | ×10⁻⁶ per °C |15{% endif %}16{% if elastic_modulus_mpa is defined %}17| Modulus of elasticity (E) | {{ elastic_modulus_mpa }} | MPa |18{% endif %}19{% if archetype_description is defined %}20 21### Site Conditions22 23{{ archetype_description }}24{% endif %}25 26{% if tool_available %}27## Available Tool28 29A thermal stress calculation tool is available at `/workspace/{{ meta.name }}_calc.py`. Run it with:30 31```bash32python3 /workspace/{{ meta.name }}_calc.py --help33```34 35You may use this tool to verify your calculations or compute values directly.36{% endif %}37 38## Required39 40Calculate the following:41 421. Thermal stress magnitude σ (MPa)432. Thermal force magnitude F (kN)443. Stress state: 1.0 if compression (rail hotter than neutral), -1.0 if tension (rail cooler than neutral), 0.0 if neutral45 46## Applicable Standards47 48- AREMA Manual for Railway Engineering, Chapter 5 (Track)49- UIC Code 720 R (Laying and Maintenance of CWR Track)50- ARTC Engineering Track Standard ETS-05-0051 52## Constraints53 54- No internet access is available. Work from engineering knowledge and the provided tool.55- Use the standard thermal stress formula for restrained rail:56  - σ = E × α × |ΔT|57  - where E is the modulus of elasticity (MPa), α is the coefficient of thermal expansion (per °C), ΔT is the temperature change from neutral (°C)58  - Report σ as a positive magnitude regardless of sign59- Calculate thermal force:60  - F = σ × A / 100061  - where A is the rail cross-sectional area (mm²), F is in kN62  - Report F as a positive magnitude63- Determine stress state from the sign of ΔT:64  - If ΔT > 0 (rail hotter than neutral): compression → report 1.065  - If ΔT < 0 (rail cooler than neutral): tension → report -1.066  - If ΔT = 0: neutral → report 0.067{% if elastic_modulus_mpa is not defined %}68- For standard rail steel: E ≈ 207,000 MPa (typical for carbon-manganese rail steel)69{% endif %}70{% if thermal_expansion_coeff_micro_per_c is not defined %}71- For standard rail steel: α ≈ 11.5 × 10⁻⁶ per °C72{% endif %}73 74## Output Format75 76Show your step-by-step working in Markdown. At the end of your solution, include a JSON block with your final answers in exactly this format:77 78```json79{80  "thermal_stress_mpa": <numeric_value>,81  "thermal_force_kn": <numeric_value>,82  "stress_state": <numeric_value>83}84```85 86Write your complete solution to `/workspace/output.md`.87

Scenario archetypes

Each generated task is drawn from one of these realistic scenario bands.

Site contexts ground each scenario in a real locale the model can use to infer hidden values.

Hot inland

hot_inland

Hot inland corridor with large positive temperature rise above neutral

artc-broken-hill-corridoralice-springs-adelaide-railpilbara-port-hedland-wa

Parameter ranges

rail_area_mm2: 6500 – 9000
thermal_expansion_coeff_micro_per_c: 11 – 12
elastic_modulus_mpa: 205000 – 210000
temperature_change_c: 20 – 50

Cold alpine

cold_alpine

Cold alpine or highland corridor with large negative temperature drop below neutral

nsw-blue-mountains-linevic-alpine-northeasttas-western-explorer

Parameter ranges

rail_area_mm2: 6500 – 9000
thermal_expansion_coeff_micro_per_c: 11 – 12
elastic_modulus_mpa: 205000 – 210000
temperature_change_c: -50 – -15

Coastal temperate

coastal_temperate

Coastal temperate corridor with moderate temperature variation

sydney-illawarra-linemelbourne-geelong-corridorperth-fremantle-coastal

Parameter ranges

rail_area_mm2: 5500 – 8000
thermal_expansion_coeff_micro_per_c: 11 – 12
elastic_modulus_mpa: 200000 – 210000
temperature_change_c: -15 – 20

Tropical north

tropical_north

Tropical northern corridor with sustained high temperatures above neutral

cairns-townsville-north-coastdarwin-adelaide-ghan-corridormt-isa-rail-qld

Parameter ranges

rail_area_mm2: 6000 – 8500
thermal_expansion_coeff_micro_per_c: 11 – 12
elastic_modulus_mpa: 205000 – 210000
temperature_change_c: 15 – 40

Example task

artc-broken-hill-corridor-hot-inland-preview — hard difficulty, some inputs hidden.

Hot inland corridor with large positive temperature rise above neutral. artc-broken-hill-corridor. Required outputs: thermal_stress_mpa, thermal_force_kn, stress_state

The model sees

Scenario context and visible inputs.

rail_area_mm2: 6500 to 9000 mm²
temperature_change_c: 20 to 50 °C

Executable tool: thermal-stress-calculation_calc.py

The model must infer

Inputs withheld at this difficulty.

Elastic modulus mpa
elastic_modulus_mpa
Thermal expansion coeff micro per c
thermal_expansion_coeff_micro_per_c

Stand-in text in the prompt

The rail is standard carbon-manganese rail steel on a {{ archetype.description }} ({{ archetype.site_context }})

The model must produce

The scored JSON answer schema.

{
  "thermal_stress_mpa": <number>,
  "thermal_force_kn": <number>,
  "stress_state": <number>
}

thermal_stress_mpa · scored within ±3%
thermal_force_kn · scored within ±3%
stress_state · scored within ±1%

Thermal Stress Calculation

How this task is generated

Template

Scenario

Difficulty tier

Task prompt

Parameters

Inputs

Scored outputs

Thermal stress mpa

Thermal force kn

Stress state

Difficulty

easy

medium

hard

Task bundle

Scenario archetypes

Hot inland

Cold alpine

Coastal temperate

Tropical north

Example task

The model sees

The model must infer

The model must produce