# Column Flotation Design MCP. AI Agent Connect

> Column Flotation Design MCP gives your AI client the engineering math needed to design mineral processing circuits. You can calculate column dimensions, set up air distribution systems, and determine how wash water affects concentrate purity. It bridges the gap between raw feed data and optimized flotation performance.

## Overview
- **Category:** engineering
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_ye4AH9jCYqbcnmnAV5fDFSrkir3Zxkvpp7ZfAqjg/ai-agent-connect
- **Tags:** flotation, mining, metallurgy, chemical-engineering, mineral-processing

## Description

You can use this MCP to handle the heavy lifting of flotation circuit design. Instead of manually running hydraulic and geometric calculations, you provide your feed characteristics to your AI client and let it determine the physical requirements for the column. It handles the math for column height and diameter based on your recovery targets. You can also model how different sparger configurations will affect bubble size or how much wash water is required to hit a specific grade. It's built to help you move from initial feed analysis to a set of optimized operating setpoints without the manual spreadsheet grind. Whether you're sizing a new column or adjusting an existing circuit, this MCP provides the specific engineering logic needed for mineral processing.

## Tools

### design_sparger_configuration
Specifies the air distribution system required to produce the right bubble size for your feed.

### evaluate_wash_water_impact
Calculates the necessary wash water volume and its effect on concentrate purity and bias.

### optimize_circuit_parameters
Generates a final set of optimized operating setpoints using your established geometry and water constraints.

### calculate_column_geometry
Determines the physical dimensions of the flotation column based on your specific recovery goals.

## Prompt Examples

**Prompt:** 
```
Calculate the column dimensions for a feed with 15% grade, a 90% recovery target, and a mass flow rate of 50 t/h.
```

**Response:** 
```
The required column height is 8.5 meters, the diameter is 1.2 meters, and the total volume is 9.94 cubic meters.
```

**Prompt:** 
```
What is the impact of using 5 m3/h of wash water on a 1.2m diameter column for a 95% target grade?
```

**Response:** 
```
Using 5 m3/h of wash water will result in an expected grade improvement of 4.2% and a resulting bias of 1.15.
```

**Prompt:** 
```
Design a sparger for a 1.2m diameter column with a fine particle size distribution.
```

**Response:** 
```
The recommended sparger type is a porous plate with an orifice diameter of 2.5mm and an air flow capacity of 15 m3/h.
```

## Capabilities

### Geometric Sizing
Your agent calculates column height and diameter to meet recovery targets.

### Air Distribution Modeling
The AI selects sparger configurations to control bubble size.

### Purity Analysis
Your client evaluates how wash water affects concentrate grade and bias.

### Setpoint Optimization
The MCP generates final operating parameters based on physical constraints.

## Use Cases

### New Circuit Design
Calculate the necessary column height and diameter for a new mineral processing installation.

### Grade Optimization
Determine how much wash water to add to improve concentrate purity.

### Sparger Selection
Match air distribution systems to specific feed particle sizes.

### Operational Tuning
Find the best operating setpoints after the column geometry is set.

## Benefits

- Automates column dimensioning based on recovery targets.
- Predicts concentrate purity changes from wash water adjustments.
- Links feed characteristics directly to optimized circuit setpoints.
- Standardizes sparger design for specific particle size distributions.

## How It Works

Connect your AI client to Vinkius to access these engineering tools instantly.

1. Connect your preferred MCP-compatible client to Vinkius.
2. Provide your feed characteristics and recovery targets to your AI client.
3. The AI invokes the necessary engineering tools to run calculations.
4. Receive precise dimensions, configurations, or optimized setpoints.

## Frequently Asked Questions

**What can this MCP calculate for flotation columns?**
It calculates physical dimensions like height and diameter, sparger configurations, wash water impacts, and optimized operating setpoints.

**How does the MCP handle wash water calculations?**
It evaluates how much wash water is needed and predicts the resulting impact on concentrate purity and bias.

**Can I use this to design air distribution systems?**
Yes, the design_sparger_configuration tool specifies the air distribution system needed to create the correct bubble size for your feed.

**What information do I need to provide for column sizing?**
You typically need to provide the feed grade, recovery target, and mass flow rate to get accurate dimensions.

**Which AI clients can use this MCP?**
You can use this with any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code.