Heat Integration · Linnhoff Method · Energy Targeting
| # | Tsupply (°F) | Ttarget (°F) | CP (BTU/hr-°F) | |
|---|---|---|---|---|
| H1 | ||||
| H2 |
| # | Tsupply (°F) | Ttarget (°F) | CP (BTU/hr-°F) | |
|---|---|---|---|---|
| C1 | ||||
| C2 |
Deep dive into pinch analysis, the Problem Table Algorithm, composite curves, grand composite curves, and heat exchanger network design.
Pinch analysis is a method for heat integration and energy optimization that determines minimum utility requirements, pinch temperature, and maximum heat recovery.
It uses the Problem Table Algorithm to determine the pinch point, minimum hot and cold utility requirements, and maximum heat recovery potential.
The pinch temperature is the point where heat transfer between hot and cold streams is most constrained, dividing the system into heat surplus and heat deficit regions.
Pinch analysis is a systematic heat integration method that identifies the minimum hot and cold utility requirements for a process. It determines the pinch temperature — the thermodynamic bottleneck — and the maximum possible heat recovery through process-to-process heat exchange.
The Problem Table Algorithm is the systematic method used to calculate energy targets in pinch analysis. It cascades heat through temperature intervals defined by the stream data to find the pinch point and minimum utility requirements without designing the actual heat exchanger network.
The three pinch rules are: do not transfer heat across the pinch, do not use cold utility above the pinch, and do not use hot utility below the pinch. Violating any rule increases total utility consumption beyond the minimum target.
The minimum temperature approach (ΔTmin) is the smallest allowed temperature difference between hot and cold streams in a heat exchanger. It balances capital cost (smaller ΔTmin means larger exchangers) against energy cost (larger ΔTmin means more utility usage).