Antranova Engineering AB Engineering Analysis & Systems Engineering

From real system to verified solution

Antranova combines field work, measurement and reconstruction of real systems with physics-based analysis, modelling, and verification in operation.

Field analysis System reconstruction Root-cause analysis Physics-based modelling Pump systems Flow & cooling systems Verification in operation Training & simulators
// Profile overview
Positioning Practical + analytical
Strength Field → model → solution
Specialty Flow, heat and process systems
Assignment types Troubleshooting → action → verification
Tools Measurement, Python, OpenModelica
Focus area Industry & infrastructure
Boundary No energy production

Services

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.

Field analysis & system reconstruction

Inspection, measurement, and reconstruction of actual system function – even when documentation is incomplete.

📐

Analysis & modelling

Physics-based models used to analyse dynamics, causes, consequences, and robustness in technical systems.

  • Transient analysis and scenario comparisons
  • Sensitivity analysis and reference cases
  • Decision support with traceable logic
🛡

Root-cause analysis & risk assessment

Identification of underlying causes, not only symptoms, with explicit assumptions and reasonableness checks.

  • Operational disturbances and deviating scenarios
  • Risk at modifications and investments
  • Verifiable recommendations

Actions & verification

Technically feasible solutions followed up against real system behaviour after implementation.

  • Implementation-oriented decision basis
  • Support during startup and follow-up
  • Verification in the real plant
📊

Technical calculations & decision support

Sizing, capacity assessment, and structured technical support for decisions and prioritisation.

  • Pressure drop, flow, and heat-balance studies
  • Load cases, requirements, and constraints
  • Reports with explicit assumptions
📚

Training & competence support

Knowledge transfer through models, simulators, visualisations, and pedagogical material adapted to the organisation.

Processpilot — interaktiv simulator

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.

Antranova Engineering AB — CDS-100 v21
Process Simulator
Speed:
3D view — drag to rotate · scroll to zoom
Flow path: V-101 → P-101/P-102 → CV-101 → HX-101 → return → V-101
P&ID — live process view
V-101
Thermal Volume
5 m³ water
35.0°C
SP 35°C
LAH-101
T ≥ 45°C
LAHH-101
T ≥ 55°C
FT
101
25.0 m³/h
P-101
RUN
P-102
STANDBY
AO
4–20 mA
CV-101
80% open
TIC-101
AUTO
SP=35°C
4–20 mA
TT
101
35.0°C
HX-101
Shell & Tube Cooler
UA·η=13333 W/K
200 kW
CW IN 20°C
CW OUT
TT
102
31.8°C
LEGEND
Process (main)
Standby
Utility CW
Control signal
Instrument
Antranova Engineering AB — CDS-100 — PFD/P&ID Demo Rev A — NOT FOR CONSTRUCTION
Pumps: 1 Q_proc: 200 kW FT-101: 25.0 m³/h
Trends
Measurements
TT-101
35.0
°C
FT-101
25.0
m³/h
Cooling Power
200
kW
Sim Time
0
LAH-101 — T ≥ 45°C
LAHH-101 — T ≥ 55°C
Pumps & Valve
80%
100%
200 kW
35°C
On
PID Controller
0.1000
0.0300
0.0000
0.50
50%
0.000
Quick Scenarios
Saved States
No saved states
Event Log
Process description

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

  • ρ = 1000 kg/m³ — water density
  • cₙ = 4180 J/(kg·K) — specific heat
  • V = 5 m³ — tank volume → thermal mass M·cₙ = 20.9 MJ/K
  • Qₙ = adjustable heat load (50–400 kW)
  • Qₕₕₓₙ = heat removed by HX-101

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)

  • UA₀ = 13 333 W/K — design conductance at nominal flow
  • h𝑓 = HX capacity factor (1.0 = clean, <1 = fouled)
  • 0.8 exponent — Dittus-Boelter turbulent convection dependence
  • Cₙ = F · cₙ — process stream heat capacity rate [W/K]

Alarms

  • LAH-101: T ≥ 45°C — high temperature warning
  • LAHH-101: T ≥ 55°C — high-high temperature, requires immediate action

Instrumentation

  • TT-101: Process temperature in V-101. Primary input to TIC-101. Also displayed as a readout tag next to the transmitter circle in the P&ID.
  • FT-101: Volumetric flow rate in the pump discharge header [m³/h]. Computed from pump count and CV-101 position.
  • TT-102: Process return temperature after HX-101, computed as T₂ = T − Qcool/(ṁ·cp). Represents the temperature entering the top of V-101.

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)

  • At 200 kW cooling duty: TCW,out ≈ 20 + 200 000 / (8.33 × 4180) ≈ 25.7°C
  • CW outlet temperature is displayed in the P&ID next to the CW OUT arrow.
PID controller — TIC-101

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
Biasb0.50Valve position at zero error — set to expected steady-state opening
Proportional gainKₙ0.10Larger → faster response, smaller offset; too large → oscillation
Integral gainK𝑖0.030Eliminates steady-state offset; too large → slow oscillation / windup
Derivative gainK𝑑0.000Damps 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

  • Temperature oscillates slowly after a setpoint step → K𝑖 is too large. Reduce K𝑖 by 30–50%.
  • Temperature never reaches setpoint (persistent offset) → K𝑖 is too small, or bias is far from the steady-state operating point. Increase K𝑖 or adjust bias.
  • Valve hunts rapidly (high-frequency oscillation) → Kₙ is too large. Reduce Kₙ by 50%.
  • Response is slow after a pump trip → Increase Kₙ. The large thermal mass (≈21 MJ/K) means the system is naturally slow.
  • Derivative makes the valve jitter → Set K𝑑 = 0. The process has no significant measurement noise but K𝑑 > 0.01 will still interact poorly with the discrete integration step.

From real system to the right model level

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 as a demonstration and concept level

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.

Live P&ID 3D view PID tuning Trend curves Scenario library

Use

Concept studies, communication, initial sensitivity analysis, and demonstration of methodology.

Open simulator

Interpretation

Most 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.

Competence

A broader background, project portfolio, and detailed professional profile are available in the full CV.

Open 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.

Tools

Python Jupyter Notebooks OpenModelica Excel / VBA FreeCAD

Core competence

  • Field analysis, measurement, and system reconstruction
  • Dynamic analyses, transients, and root-cause studies
  • Model development, parameterisation, and quality assurance
  • Flow, pump, cooling, and heat-transfer systems
  • Technical communication and decision support

Delivery capability

  • From rapid expert support to structured verification
  • Structured reports with explicit assumptions and conclusions
  • Reproducible calculation packages and model material
  • Support from analysis through implementation and follow-up

Approach

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.

01

Field analysis & scoping

The system, the problem, and the real operating conditions are mapped. Assignments are scoped with regard to confidentiality, risk, and decision impact.

02

System reconstruction & modelling

The system function is recreated at the level needed to understand behaviour and build the right analysis model.

03

Analysis & action development

Scenarios, causes, and alternatives are evaluated. Recommendations are developed with clear technical reasoning.

04

Verification & knowledge transfer

The solution is followed up in operation or against reference data. Results, assumptions, and lessons learned are communicated clearly to the organisation.

Typical input data

  • System/process description and goal/question
  • Drawings, flow diagrams, block diagrams
  • Data: measured values, design values, tolerances, load cases
  • Desired delivery format and schedule

Contact

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.

Send inquiry
Company Antranova Engineering AB
Org.nr 559565-2800
Country Sweden
Web antranova.se
Direct email antanas.romas@antranova.se
Mobile +46 760 212 640
General email kontakt@antranova.se
LinkedIn company/110775117

Assignments are always scoped with regard to confidentiality and conflicts of interest. Energy production is not included in the business scope.