Antranova combines field work, measurement and reconstruction of real systems with physics-based analysis, modelling, and verification in operation.
Assignments are built around the full chain: first understand real system behaviour, then analyse it, define actions, and verify that the solution works in operation.
Inspection, measurement, and reconstruction of actual system function – even when documentation is incomplete.
Physics-based models used to analyse dynamics, causes, consequences, and robustness in technical systems.
Identification of underlying causes, not only symptoms, with explicit assumptions and reasonableness checks.
Technically feasible solutions followed up against real system behaviour after implementation.
Sizing, capacity assessment, and structured technical support for decisions and prioritisation.
Knowledge transfer through models, simulators, visualisations, and pedagogical material adapted to the organisation.
CDS-100 is a web-based process simulator for a closed cooling-water system with a circulation pump, a control heat exchanger, and PID control. The simulator demonstrates Antranova’s capability to build dynamic analysis tools directly in the browser — without installation.
Try it: change setpoints, start/stop pumps, freeze and resume the simulation, and load scenarios. Everything runs locally in your browser.
CDS-100 is a single-loop cooling demonstration system. Water stored in vessel V-101 (volume V = 5 m³) is continuously heated by a process heat load Qₙ and cooled by a shell-and-tube heat exchanger HX-101.
Energy balance — tank temperature
ρ · V · cₙ · dT/dt = Qₙ − Qₕₕₓₙ
Flow
Each running pump delivers nominal flow Fₙ = 25 m³/h through CV-101. Two pumps in parallel double the flow. Flow is zero when no pump runs or CV-101 is fully closed.
F = nₘ · Fₙ · x𝐶𝑉 [kg/s]
Heat exchanger — NTU effectiveness method
HX-101 is modelled using the ε-NTU method for a single-pass heat exchanger with cooling water inlet temperature T𝑢 = 20°C:
UA = UA₀ · h𝑓 · (F/Fₙ)^0.8
ε = 1 − exp(−UA / Cₙ)
Qₕₕₓₙ = ε · Cₙ · (T − T𝑢)
Alarms
Instrumentation
Cooling water side
The cooling water (CW) enters HX-101 at Tu = 20°C. The outlet temperature is estimated assuming a nominal CW circulation rate of 30 m³/h (8.33 kg/s):
TCW,out = Tu + Qcool / (ṁCW · cp)
TIC-101 controls the tank temperature T by adjusting the position of control valve CV-101. The controller acts in reverse: when T rises above setpoint, the valve opens further to increase cooling flow.
PID equation (positional form, discrete)
u(t) = bias + Kₙ · e(t) + K𝑖 · ∫e dt + K𝑑 · de/dt
e(t) = T(t) − Tⱼₙ (error, positive when too hot)
Parameters
| Parameter | Symbol | Default | Effect |
|---|---|---|---|
| Bias | b | 0.50 | Valve position at zero error — set to expected steady-state opening |
| Proportional gain | Kₙ | 0.10 | Larger → faster response, smaller offset; too large → oscillation |
| Integral gain | K𝑖 | 0.030 | Eliminates steady-state offset; too large → slow oscillation / windup |
| Derivative gain | K𝑑 | 0.000 | Damps fast changes; amplifies measurement noise — use cautiously |
Anti-windup
The simulator uses conditional integration: the integral accumulates only when the output u is within [0, 1]. When the valve is saturated (fully open or fully closed), the integral is frozen unless accumulating in that direction would reduce saturation. This prevents integral windup during pump trips and large setpoint steps.
Tuning guide
Modelling is not used as an end in itself. The right model level is chosen based on the real system, the question at hand, the decision impact, and the need for verification.
Higher model fidelity → deeper physical representation → higher complexity → greater demands on verification, tools, and documentation.
CDS-100 illustrates how a browser-based model can be used to understand process behaviour, analyse pump trips, heat-exchanger impact, and PID control in real time. This level is intended for fast orientation, pedagogical visualisation, first scenario comparisons, and early decision discussions.
Use
Concept studies, communication, initial sensitivity analysis, and demonstration of methodology.
Open simulatorMost technical questions should begin at a simpler model level in order to quickly establish reasonable assumptions, scope the problem, and identify which parts actually justify higher model fidelity.
A broader background, project portfolio, and detailed professional profile are available in the full CV.
Senior systems engineer combining field work, technical analysis, model development, and verification in complex industrial and infrastructure systems. The strength lies in connecting real behaviour to physics-based understanding and implementable action.
CV and references are available on request. Contact Antanas directly for more information.
Assignments follow the same method chain as the rest of the website: field, reconstruction, analysis, action, and verification. Documentation and models are scaled to the complexity of the question.
The system, the problem, and the real operating conditions are mapped. Assignments are scoped with regard to confidentiality, risk, and decision impact.
The system function is recreated at the level needed to understand behaviour and build the right analysis model.
Scenarios, causes, and alternatives are evaluated. Recommendations are developed with clear technical reasoning.
The solution is followed up in operation or against reference data. Results, assumptions, and lessons learned are communicated clearly to the organisation.
Send a short description of the system, the problem, or the question. You will normally receive feedback with a proposed setup and scope within 1–2 business days.
Assignments are always scoped with regard to confidentiality and conflicts of interest. Energy production is not included in the business scope.