mackorn_grading_porosity

Is my material bed dense enough to keep the reduction ratio constant?

What it answers

按粗/中/细三组分配比计算料层孔隙率 φ = 0.42 − 0.30·min(中料占比,0.35) + 0.15·max(0, 细料占比 − 0.30),与最优配比窗口对比。

Input parameters

ParameterTypeDescription
coarse_fracnumber粗骨料占比(可为任意一致单位,内部归一化)。
mid_fracnumber中间粒级占比(关键充填相)。
fine_fracnumber细颗粒占比。

Worked example (real output, not a mock-up)

Run via: local plugin

Input:

{
  "coarse_frac": 50,
  "mid_frac": 30,
  "fine_frac": 20
}

Output (first fields):

FieldValue
input_normalized.coarse0.5
input_normalized.mid0.3
input_normalized.fine0.2
porosity0.33
optimal_porosity_reference0.28
gap_to_optimal0.05
optimal_grading.coarse_frac0.5
optimal_grading.mid_frac0.3
optimal_grading.fine_frac0.2
optimal_grading.porosity_min0.28
optimal_grading.note中间粒级为最优孔隙率充填的关键,过多细粉反使密实度过高、应力传导失配
verdict可接受,建议增加中间粒级充填
assumptions[2 项]
warnings[0 项]

How to call it

POST a JSON-RPC 2.0 request to the public MCP endpoint — no installation, no API key:

curl -s https://mackorn.cn/ai/api/mcp.php \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
       "params":{"name":"mackorn_grading_porosity","arguments":{"coarse_frac":50,"mid_frac":30,"fine_frac":20}}}'

Endpoint: https://mackorn.cn/ai/api/mcp.php · Registry: cn.mackorn/mackorn-cone-crusher · npm: mackorn-cone-crusher

Data sources and limits

Particle-size and flow models are independently implemented from published literature (Whiten 1972; Bond 1952). Vendor parameters come from MACKORN NH/NS tables. Every output carries assumptions[] and warnings[]; unknown values are returned as null, never estimated. Literature parameters must be calibrated against on-site sieve data before use in a formal proposal.

A hydraulic cone crusher is a secondary/tertiary machine: feed above roughly 350 mm is refused.