Shell-and-tube heat exchanger
Fouling costs a little every day. The twin tells you when cleaning pays.
A crude preheat exchanger saves furnace fuel by moving heat from a hot product into the crude. Deposits build on the tubes and the duty falls a little each day. The twin works out U from the four temperatures and two flows, prices the lost duty, and says when a cleaning pays for itself.
TEMA AES, crude preheat, 8 MW, U clean 450 W/m²·K, 420 m²
Built and run to TEMA, API 660
- Duty, clean
- 8.0 MW
- U at 18 months
- 331 W/m²·K
- Best cleaning interval
- 365 days
- Payback at 18 months
- 170 days
Anatomy and nameplate
- 1Crude inlet temperature. Cold-side start of the heat balance.
- 2Crude outlet temperature. Falls as the tubes foul. The furnace makes up the rest.
- 3Hot inlet temperature. Hot-side start of the heat balance.
- 4Hot outlet temperature. Rises as less heat leaves the hot stream.
- 5Crude flow. With the crude temperatures, gives the duty.
- 6Hot product flow. Checks the duty from the other side.
- 7Tube-side pressure drop. Deposits narrow the bore and the drop climbs.
- 8Shell-side pressure drop. Bypass and maldistribution show here.
| Thermal | |
|---|---|
| Duty, clean | 8.0 MW |
| U clean | 450 W/m²·K |
| Area | 420 m² |
| Crude, tube side | 150 → 200 °C |
| Hot product, shell side | 245 → 205 °C |
| LMTD and F | 49.9 K, F = 0.85 |
| NTU and effectiveness | 1.18, 53% |
| Streams | |
| Crude | 69.6 kg/s, about 44,500 bbl/d |
| Hot product | 74.1 kg/s |
| Tube-side pressure drop, clean | 70 kPa |
| Mechanical | |
| Type | TEMA AES: removable channel and cover, one-pass shell, floating head |
| Passes | One shell pass, two tube passes |
| Tubes | 1 in OD, 19.86 mm bore, carbon steel |
| Baffles | Single segmental |
| Fouling model | R_f settles at 9 × 10⁻⁴ m²·K/W, time constant 250 days |
From the well to market
Wells lift the fluid. The separator splits it. Oil goes to the tank battery and gas to the compressor station, and both leave by pipeline for processing.
- Well fluid
- Crude oil
- Gas
- Has its own twin page
The physics
The equations behind every curve on this page.
Duty
Q = U·A·F·LMTD
8.0 MW clean, with LMTD 49.9 K and F 0.85 for one shell pass and two tube passes.
Fouling resistance
R_f = 1/U_dirty − 1/U_clean
Each deposit adds a layer of resistance on top of the clean tube.
Effectiveness
Q = ε·C_min·(T_hot,in − T_cold,in)
Gives the duty a fouled bundle can make with today’s inlet temperatures.
Cleaning payback
Σ (fuel saved) = C_clean
Days until the fuel a cleaning saves adds up to what it costs.
Fouling and cleaning
U falls as deposits build. The lost duty is fuel the furnace burns instead. Cleaning costs a lot at once and puts U back.
Overall heat transfer coefficient over time
Clean U 450 W/m²·K, 420 m²
- Never cleaned
- Cleaned every 365 days
- Fouling at 18 months
- 8.0 × 10⁻⁴ m²·K/W
- U after fouling settles
- 320 W/m²·K
Deposits add a layer of resistance on top of the clean tube. U falls fastest at first, then levels off. Cleaning puts it back.
R_f = 1/U_dirty − 1/U_clean R_f(t) = R_∞·(1 − e^(−t/τ))
What fouling costs against what cleaning costs
Lost duty made up in the furnace at 85% efficiency, fuel at $4.00/MMBtu
- Extra fuel since cleaning
- Cleaning plus fuel, per day of cycle (right axis)
- Fuel cost at 18 months
- $376 a day
- Clean at 18 months, pays back in
- 170 days
Each day of fouling costs a little. Cleaning costs a lot at once. The best interval is where the two, spread over the cycle, cost least per day.
cost per day = (C_clean + Σ fuel_extra) / T fuel_extra = (Q_clean − Q) / η_furnace
Pressure drop
Deposits that block heat also narrow the tubes. Reading both tells fouling from a flow problem.
Tube-side pressure drop as deposits build
19.86 mm tube bore, deposit conductivity 0.35 W/m·K
- Tube-side Δp at design flow
The same deposit that blocks heat also narrows the bore. Pressure drop and U moving together point to fouling. U falling with flat pressure drop points to bypass or a flow problem instead.
Δp ∝ d^(−4.75) d = d_clean − 2·R_f·k_deposit
Failure modes
What breaks, what it looks like, what the twin does about it.
| Failure mode | The physics | Signals that show it | How the twin catches it |
|---|---|---|---|
| Fouling | Asphaltenes, salts and corrosion products build up on the tube walls and add thermal resistance. | Crude outlet temperature down at the same flows and inlet temperatures. Tube-side pressure drop up. | Works out U and R_f from the heat balance every hour and prices the lost duty in furnace fuel. |
| Tube leak | A cracked or corroded tube lets the higher-pressure stream into the other side. | Heat balance no longer closes. Lab results on the low-pressure stream change. | Compares the duty from each side. A gap that grows points to a leak, not fouling. |
| Baffle bypass | Worn baffles or a loose bundle let shell-side fluid go round the tubes. | U down with shell-side pressure drop down, not up. | Reads U and both pressure drops together to tell bypass from fouling. |
| Flow maldistribution | Uneven flow across the passes leaves part of the bundle doing little work. | U down with flat pressure drop. Outlet temperature swings with flow. | Checks the duty against flow over time. Fouling does not change with flow, maldistribution does. |
What the twin does not do
- We say when cleaning pays. Planning the outage and isolating the bundle stay with your operations team.
- We never change furnace firing or bypass valves. TwinEdge is never in the safety loop.
How we catch it early
A physics twin and a PINN, working on one shell-and-tube heat exchanger.
The twin is a set of equations for this machine, tuned to its nameplate. Give it the flow, speed and conditions and it returns what every reading should be. It always gives the same answer for the same inputs.
A physics-informed neural network, or PINN, sits on top. It is trained on the plant’s own data and it is penalized whenever it breaks a physics rule. So it can only learn what the equations leave out: wear, fouling, friction. It cannot invent an answer that the machine could never produce.
Step 1
Measure
Flow, pressure, current, temperature, vibration. Whatever the asset already has.
Step 2
Physics twin
The equations of this machine, set to its nameplate. It says what the readings should be right now.
Step 3
Residual
Measured minus expected. Demand, weather and speed are already taken out.
Step 4
PINN
A small neural network that learns the cause of the gap, under the physics rules.
Step 5
Finding
A named cause, a date, and the kWh or hours at stake. An engineer reviews it.
loss = (measured − predicted)² + λ · (physics residual)²
The second term is the rulebook. It is zero when the network obeys the equations.
Why this beats black-box AI
A black-box model learns patterns from history. It needs examples of each failure, and it goes quiet when the pump runs at a point it has not seen. The twin starts from physics, so it works on day one. The PINN adds what physics cannot know about this particular machine.
That is also what makes the savings countable. The baseline is a calculation, not a guess, so the gap between baseline and meter is a number a customer can check.
What the twin checks on this asset
- U and R_f from the heat balance, every hour
- Duty from the crude side against duty from the hot side
- Tube and shell pressure drop against U
- Cost of fouling to date against the cost of a cleaning
| Fixed alarm | Black-box AI | Twin + PINN | |
|---|---|---|---|
| Needs failure history to learn | No | Yes, lots | No |
| Says what is wrong | No | Rarely | Yes, by name |
| Works at a flow it has never seen | No | Often fails | Yes, the equations still hold |
| Puts a number on the saving | No | No | Yes, in kWh and dollars |
| Lead time on slow wear | Late | Varies | Weeks to months |
| Every number can be traced | Yes | No | Yes, to an equation |
What the twin puts a number on
Energy and cost, from the equations.
Duty lost at 18 months
976 kW
Crude leaves 6.1 °C cooler. The furnace makes up the rest.
Extra furnace fuel
$376 a day
At $4.00/MMBtu and 85% furnace efficiency
Best cleaning interval
365 days
$331 a day over the cycle, with $45,000 per cleaning
Clean at 18 months
Pays back in 170 days
Fuel saved against the cost of one cleaning
What we do for you
We watch it. We catch it. We prove it.
Our reliability engineers run the twin on your shell-and-tube heat exchanger, review every finding, and help your crew fix it. After the repair we compare the meter to the baseline and write the result in the ledger.
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