Reasoning & math
AuraScore 81/100

Intermodal Terminal Throughput Optimization Specification

Model crane cycle times, yard dwell curves, and maximum daily container throughput for intermodal hubs.

Use this specification when analyzing transfer capacity constraints between rail spurs and road carriers. It provides a clean mathematical formula spec to quantify bottleneck risks and yard density.

Template

Role: Principal Intermodal Operations Research Analyst

Context

  • Terminal facility: {{terminal_name}}
  • Daily inbound volume: {{daily_container_volume}}
  • Handling equipment speed: {{crane_handling_rate}}
  • Average yard dwell duration: {{mean_dwell_time_hours}}
  • Surge volatility factor: {{peak_surge_coefficient}}
  • Total ground slot capacity: {{buffer_storage_capacity}}

Task

Develop an intermodal capacity and throughput mathematical specification that defines crane cycle limitations, yard saturation curves, and gate transfer formulas for {{terminal_name}}.

Method

  1. Define the hourly crane service rate formula based on {{crane_handling_rate}} under single and dual-cycling modes.
  2. Compute peak hourly arrival rates by applying {{peak_surge_coefficient}} to {{daily_container_volume}}.
  3. Formulate Little's Law relationship ($L = \lambda W$) governing static yard inventory using {{mean_dwell_time_hours}} and inbound flows.
  4. Derive the yard saturation index showing slot utilization against {{buffer_storage_capacity}}.
  5. Model queue buildup equations at the railhead and gate when arrival rates exceed crane service capacities.
  6. Formulate the dwell penalty calculation identifying the point of exponential handling re-handle overhead.
  7. Establish critical operational thresholds where crane productivity drops due to yard density exceeding 75%.

Constraints

  • Calculations MUST define all rates in twenty-foot equivalent units (TEU) per hour or day.
  • Formulas MUST distinguish between gross crane moves and net productive moves (accounting for re-handles).
  • You MUST NOT assume infinite storage buffer or zero-variance arrival schedules.
  • Do not include software simulation code; provide closed-form analytical formulas.

Output format

  • Section 1: Throughput and Crane Capacity Equations (hourly rated moves, net throughput)
  • Section 2: Storage Density & Little's Law Yard Model (slot utilization vs. {{buffer_storage_capacity}})
  • Section 3: Bottleneck Trigger Limits (mathematical conditions for congestion alerts at {{terminal_name}})
  • Total length: 450-700 words.

Self-review

  • Ensure Little's Law units (time, rate, units) are mathematically consistent.
  • Confirm {{peak_surge_coefficient}} is correctly applied to calculate worst-case yard pressure.
  • Verify that equations account for re-handle moves as a function of storage density.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

research-analysis
research-reasoning-math
transport-logistics
intermodal
operations-research
terminal-throughput