GPU-accelerated chemical process simulation, running headless and continuously re-calibrated against live plant data. One ranked board for operations. The same engine for design studies. Every team — engineering, economics, design — looking at the same numbers.
DWSIM and Aspen are rigorous — and rigid. Wall-clock time per run is measured in minutes to hours. Tuning a model to live plant data is effectively a full-time job. By the time it's calibrated, the plant has drifted.
The result: most plants run on weeks-old assumptions. Economics is checked weekly. End-of-run is estimated. Heat exchanger cleaning is on a calendar, not on physics.
A deterministic, GPU-accelerated engine running headless 24/7. It subscribes to your historian, continuously re-tunes itself against live data, and exposes its output through both a structured API and an optional natural-language layer. The math is rigorous. The interface is convenient. The model is always current.
Each ranked entry on the Top-10 board is generated by one of four continuous workflows, running in the background against a model that is always current.
Optimal setpoints re-checked against current feedstock and product pricing on a continuous loop. Not weekly. Not monthly. Continuously.
Multi-parameter scenario sweeps run in the background, producing a calculated turnaround date with confidence bounds — not a calendar guess.
Heat exchanger cleaning scheduled based on live fouling trajectory and forecasted weather over the coming months — physics, not fixed intervals.
Any process engineer can ask "what happens if…" in plain language and get an answer in minutes, against a model that reflects today's plant.
The Top-10 board is what continuous mode looks like. But the same GPU-accelerated engine also runs in study mode for process design — and the speed differential changes what's practical to explore.
The engine runs 24/7 against live data, continuously re-calibrating and publishing the Top-10 $/day board. Engineering owns the model; economics consumes the ranking; operations and management see one shared picture of the plant.
The same engine sweeps hundreds of design cases in the time a handful used to take. Design teams explore the full space — column sizing, exchanger areas, reflux ratios, feed sensitivities — instead of pre-narrowing to a base case.
Same calibration discipline. Same rigorous output. Same optional LLM layer for asking questions in plain language. The 100× speed differential simply changes what's worth attempting.
Rigorous process simulation now runs at speeds that make autonomous, continuous re-calibration feasible — not just possible in theory.
Natural-language access to a deterministic engine removes the scripting bottleneck. Engineers ask questions; the math stays rigorous underneath.
Historians, OPC UA, cloud connectivity — the integration that took six months in 2018 takes days in 2026. The model can finally subscribe to reality.
The current engine accelerates the unit operations that dominate refinery and petrochemical wall-clock time. These two are deliberately first: they sit on the critical path of nearly every economic and turnaround decision.
Lower wall-clock time than DWSIM on equivalent distillation and heat exchanger problems — the speed differential that makes continuous re-calibration and scenario sweeps practical, instead of hypothetical.
Narwal Twin is built for the people who actually make plants run and the people who design them — engineering, economics, and design — working off the same rigorous, dollar-quantified picture.
The process engineering manager and team validate the calibration, sign off on each unit operation, and decide when to expand scope. They get a model that is *accurate* and *current* — without the full-time-job tradeoff.
Process technologists become the daily power users, running what-if scenarios in plain language instead of driving a desktop simulator.
The Top-10 $/day board replaces stale weekly LP runs with a continuously updated view of margin opportunities — the moment market prices move, the ranking updates.
Operations leadership and plant management look at the same board: one ranked list everyone agrees on, instead of competing optimization studies.
Design and revamp engineers — at owner-operators, EPCs, and licensors — use the same engine in study mode to explore hundreds of cases instead of pre-narrowing to a base case.
Sensitivity studies, side-by-side trade-offs, and feed variation sweeps that used to need overnight runs now finish over coffee.
The fastest way to know whether this fits your plant is to point it at real data. Tell us about your unit and we'll set up a walkthrough.