Flow + heat transfer
CFD Heat Transfer Lab
Explore how flow and heat transfer shape cooling performance in a simplified heat exchanger.
SIA · Your autonomous engineering engine
Better designs.
Better processes.
Fewer costly iterations.
Describe the problem. Share your drawings or data. SIA selects the models, coordinates the scientific tools and connects the findings to your next decision—so you can improve designs, sharpen experiments and scale processes without managing a simulation toolchain.
Your engineering question. An autonomous path from models to insight.Focus on the decision. Leave the modelling workflow to SIA.
Autonomous by design · Simple to use
You define the problem.
SIA drives the investigation.
From a flow bottleneck to a chemistry experiment or fermentation scale-up, SIA connects the physics, models and scientific tools around your goal. It handles model selection, geometry and numerical setup where needed, and brings the results together into a clear engineering answer.
Engineering insight.
Without assembling the toolchain.
See how the autonomous engine works →Without assembling the toolchain.
Start in plain language. Add the information you have. SIA asks for the physical inputs that matter and handles the modelling workflow, with assumptions and evidence available to inspect.
01
Define the outcome.
Set the performance target and the constraints that matter—throughput, energy, temperature, conversion or product quality.
02
Find what controls performance.
Connect flow, heat transfer, reaction kinetics and data to identify the mechanisms behind the bottleneck.
03
Compare the changes that matter.
Evaluate design and operating alternatives on a consistent basis. Focus modelling effort and physical trials where they can change the decision.
04
Act on the evidence.
See what the findings mean for your next design, process change or experiment, with the assumptions and reasoning available to inspect.
Engineering questions worth answering
What are you trying
to improve?
Reduce pressure losses. Meet thermal targets. Learn more from each chemistry experiment. Preserve fermentation performance at scale. Explore the questions behind your next improvement.
Pump curve + system balance → local CFD where needed → design comparison
Flow & energy
Will a bigger pump solve the problem?
“Our flow is below target. Should we change the pump, the pipe size, or the layout?”
Choose the intervention that addresses system resistance and delivers the required flow.
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Energy balance → thermal sizing → spatial flow and heat where needed
Heat & design
Meet the temperature target. Understand the energy cost.
“What tube length or cooling arrangement will reach the target temperature at the required throughput?”
Size the thermal path and identify whether area, flow, material resistance or local cooling is the limiting factor.
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Drawing → fluid domain → flow solution → local and system comparison
Flow & geometry
Find the geometry that is costing you performance.
“Which bend or transition is creating the pressure loss—and what should we change?”
Focus the redesign on the geometry that controls useful flow delivery.
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Reaction knowledge + experiment data → hypothesis → next experiment → model update
Chemistry & experiments
Make the next experiment answer a better question.
“Which temperature, concentration or reaction-time experiment will best explain the performance gap?”
Choose experiments that distinguish competing explanations and improve the next process decision.
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Kinetics + energy balance ⇄ jacket response → operating comparison
Reactions & heat
Can the cooling system keep up with the reaction?
“How will changing the batch conditions affect conversion, temperature and cooling demand?”
Compare operating strategies against both reaction performance and heat removal.
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Batch data + kinetics ⇄ oxygen, mixing and heat transport → scale-up experiment
Fermentation & scale-up
The cells are the same. Their environment is not.
“Why does a fermentation that performs in the lab lose productivity in a larger vessel?”
Identify the process or transport constraint and choose a focused scale-up experiment.
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Thermodynamic state → enthalpy balance → equilibrium or transport model
Properties & phases
When heating changes the phase, change the model.
“At this pressure and heat input, are we heating a liquid, creating vapour, or doing both?”
Choose a thermal model that represents the actual fluid state and the output you need.
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System balance ⇄ detailed component ⇄ process model → design decision
Systems & scale-up
Resolve the bottleneck. Keep the whole system connected.
“Can we study the critical component in detail without simulating every metre of the plant?”
Put modelling effort where it can change the answer while retaining the surrounding system’s behaviour.
Explore this use case →Fermentation scale-up · Preserve process performance
The cells haven’t changed.
Their environment has.
Why does a process that works in the lab lose performance in a larger vessel?
01 / Kinetics
What the
cells need.
Growth, substrate use and oxygen demand.
Demand informs the flow model.
Local conditions feed back into growth.
02 / CFD
What the
vessel delivers.
Mixing, oxygen transport and local temperature.
Reveal the gradients a vessel-average measurement can miss.
Explore / Interactive engineering
Make the physics tangible.
Kinetics + transport
Fermenter Lab
Explore the oxygen and cooling constraints that can limit fermentation performance at scale.
Engineering + energy
Draught Fan Lab
Explore how airflow and pressure requirements translate into fan power and energy demand.
Insights / From the company
Engineering questions.
Useful perspectives.
Use cases and ideas on choosing the right model, learning from experiments and turning scientific insight into practical decisions.
Read our insights →