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Thermal Transient 1D

thermal_transient_1d
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Solve 1-D transient conduction in a plane wall cooled or heated by convection, returning center, surface, and lumped temperatures over time.

Instructions

Analytic 1-D plane-wall transient conduction (one-term Heisler series), valid for Fourier ≳ 0.2 — the closed-form transient the Elmer thermal_transient solve is gated against, and the distributed (spatial-gradient) answer the lumped screen only approximates. A wall of half-thickness L cools/heats toward ambient by surface convection: Bi = h·L/k, Fo = α·t/L², α = k/(ρ·cₚ). Pass alpha_m2_s, or k+rho+cp, or a material (Materials DB: thermal_conductivity/Density/specific_heat); get h_conv from the h_estimate correlation screen rather than guessing.

As Bi→0 the body is isothermal and this collapses to the lumped exponential exp(−t/τ) (cross-checked via t_center_lumped_c / lumped_agrees). Returns {biot, fourier, eigenvalue_1, c1, t_center_c, t_surface_c, t_center_lumped_c, time_constant_s, one_term_valid, lumped_agrees}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
cpNo
rhoNo
h_convYes
materialNo
alpha_m2_sNo
duration_sYes
t_ambient_cNo
t_initial_cNo
half_thickness_mmYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint and openWorldHint, so the description carries the burden of explaining behavior. It discloses the one-term Heisler approximation, validity limits, material-input alternatives, the collapse to lumped behavior, and the exact output keys. This significantly exceeds what annotations alone provide, with no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence carries information: model, validity, physical setup, dimensionless numbers, input alternatives, guidance to a sibling tool, and return fields. It is front-loaded with the core definition and avoids filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, listing the return keys is essential and is done thoroughly. The description also covers the physical geometry, assumptions, validity range, input alternatives, and relationship to lumped and FEA tools. Nothing critical is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: it defines α = k/(ρcₚ), Bi = hL/k, Fo = αt/L², and explains the acceptable input paths (alpha_m2_s, k+rho+cp, or material). A few parameters like duration_s, t_initial_c, and t_ambient_c are left to their titles/defaults rather than explicit prose, preventing a perfect score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a specific verb and resource: an analytic 1-D plane-wall transient conduction calculation via one-term Heisler series. It distinguishes itself from the lumped approximation and the Elmer thermal_transient solve, so an agent can tell exactly what this tool computes and why it is different.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states the validity regime (Fourier ≳ 0.2), contrasts the distributed answer with the lumped screen, and directs the agent to obtain h_conv from the h_estimate correlation screen rather than guessing. It also explains the Bi→0 collapse to the lumped exponential, giving clear contextual guidance on when this approximation is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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