SOLUTIONS · HEAT EXCHANGERS

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Saturation at the wall — where fouling actually starts.

AquaAdvisor resolves saturation at wall temperature, tracks fouling factor trajectory and thermal performance penalty, and keeps an asset-bound identity across cleanings and retubes — from the temperatures and chemistry you already collect on the account.

AquaAdvisor heat exchanger digital twin for a service-company demo tenant: overall U-coefficient and cleanliness measured versus predicted, fouling-factor margin, calcite saturation, and a 28-hour CaCO3 scale forecast with corrective options.
Product UI — heat-exchanger twin for a service-company demo tenant: U-coefficient forecast and fouling event. Not a customer site.

WHAT GOES WRONG

What goes wrong in heat exchangers

  • Bulk chemistry lies about the wall

    Calcite saturation in the bulk can look acceptable while the hot wall is already depositing. LSI on a sample from the header does not see the skin temperature — the failure the program is hired to catch early.

  • Fouling is discovered as duty loss

    Approach temperature creeps for weeks. Cleaning is scheduled by calendar or crisis, not by a predicted fouling-factor trajectory you can take to the account before the customer feels the duty hit.

  • History resets at every cleaning

    Spreadsheets and portal exports lose the exchanger’s chemical and thermal identity when the bundle is cleaned or retubed — the account still expects you to remember it.

  • Deposit composition is guessed

    Without speciation and kinetics tied to wall conditions, CIP and mechanical cleaning recommendations stay empirical.

WHAT AQUAADVISOR MODELS

What AquaAdvisor models

  • Wall-temperature-resolved saturation
  • Fouling factor trajectory and thermal performance penalty
  • Deposit composition
  • Asset-bound identity across cleanings
  • CFD-to-reduced-order correction from datasheets, thermography, and geometry

DATA BY FIDELITY

Required data inputs by tier

T1

Baseline

  • Process-side inlet/outlet temperatures or approach
  • Cooling-water chemistry and temperature
  • Nominal duty and design U or fouling allowance
T2

Instrumented

  • Continuous temperature and flow on process and water sides
  • Periodic lab chemistry aligned to the exchanger loop
  • Cleaning and retube event log
T3

Hourly speciation

  • Hourly chemistry state estimation for the serving loop
  • Measured pressure drop or performance curves where available
T4

High fidelity

  • Datasheet geometry, materials, and thermography
  • CFD-informed reduced-order correction terms

OUTPUTS

Outputs and decisions enabled

  • Wall-resolved saturation indices for deposit-forming minerals
  • Fouling factor trajectory with uncertainty bands
  • Thermal performance penalty vs clean baseline
  • Predicted deposit composition for cleaning strategy
  • Persistent asset identity across cleanings and retubes

Decisions enabled

What you can decide

  • When to recommend cleaning before duty loss becomes a unit constraint the customer feels
  • Whether chemistry or hydraulics is driving the penalty on the account
  • Which sensor or thermography pass to recommend next on the account

COMPLIANCE OVERLAYS

Relevant compliance overlays

  • Evidence packages your account team can take into reliability and turnaround conversations
  • Link to the Legionella / ASHRAE 188 programs you deliver when the exchanger sits on an evaporative loop
  • Exportable history that defends the program you run across cleanings and retubes

AI IN THIS ASSET

AI on heat exchanger fouling

Forecast narratives and cleaning triggers for the exchangers you treat — from wall-resolved chemistry, not approach-temperature vibes.

  • Root-cause narratives when fouling factor climbs: wall saturation vs hydraulic or duty changes — physics you can defend on the account
  • Twin residual monitoring that flags when the exchanger twin stops tracking measured approach
  • Recommended cleaning windows bounded by predicted thermal penalty and the site’s turnaround constraints
  • Value-of-information on thermography or wall-temperature sensors to recommend before the next outage

How the AI layer works →

Bring an exchanger from an account you treat.

We will walk wall saturation and fouling trajectory from the data you already collect on that account.