Post by Samba BA

🔥 Quantum‑Hybrid‑PINN: AI‑augmented industrial simulation arrives in Africa We are proud to share the first results of our hybrid simulation platform (CFD + PINN + FNO), designed to accelerate the energy transition and the industrialization of the continent. With our AI‑augmented physics engine, we have simulated 6 real‑world use cases: 1️⃣ Hydrogen pipeline (GTA – Senegal/Mauritania) 2️⃣ LH₂ cryogenic storage 3️⃣ Port energy optimization (Dakar, Abidjan, Tanger Med, Durban) 4️⃣ Pipeline safety (leak detection) 5️⃣ LNG/LH₂ cryogenic transport 6️⃣ Mining ventilation (cobalt, copper, lithium) ✓ See for yourself: our pressure, temperature, velocity, and thermal resistance curves – from real simulations, zero hallucination. --- ✓ Latest test on the GTA pipeline (Senegal–Mauritania) - Selected project: `GTA-Pipeline-H2-V8` - Active tab: Advanced PINN Analysis - Displayed analysis: `Validation GTA-Phase2` **Results:** - Credibility score: **68.4%** (status: completed) - Anomaly: **High Kalman Filter correction required (69.1% avg correction)** **Interpretation:** - A score of 68.4% is acceptable but improvable. It shows that the simulation is globally coherent, but there are significant gaps between model predictions and observations/physics. - The high Kalman correction (69.1%) means our Deep Kalman Filter had to adjust the system state by nearly 70% on average. For good assimilation, we expect <20%. This suggests either: - Initial uncertainty is too high (poorly known input parameters) - Observations (pressure, temperature, flow rate) are inconsistent with the simulated dynamics **What this means for the GTA project:** - Input parameters (length, diameter, pressure, temperature, flow rate) were not perfectly aligned with the PINN model. - We used automatic transcription (GPT‑4o extraction) from a text that contained approximations. - The Kalman filter forced a massive correction to bring the simulation closer to real physics. ✓ **Recommended action:** Rerun the simulation with better‑adjusted parameters (e.g., inlet pressure closer to the real GTA value, ≈80‑85 bar). If the score exceeds 80% and the Kalman correction drops below 30%, the model will be validated. --- ✓ **Conclusion** Our platform works correctly: it executes scenarios, computes a score, and detects anomalies. The 68.4% score and the Kalman anomaly are **realistic for a first pass**. They are not system errors, but quality indicators that guide us to refine the parameters. --- ✓ **We are looking for:** - Industrial partners for pilot projects (pipelines, ports, mines,....) - Technical partners (OpenFOAM, Fortran, hydrogen valleys,...) - DeepTech investors to scale up ✓ Live demo available upon request. DM me or send an email. #NumericalSimulation #GreenHydrogen #PINN #FNO #DeepTech #MadeInAfrica #QuantumHybridPINN #Industry4.0