Computational Energy Engineering

We design
CHP Diagnostics
with code.

Inspired by LEAP 71's Computational Engineering Models. 30 years of energy technology expertise, encoded into 19 causal chains and 70 live sensors. A new way to operate biogas plants.

--Score
--Live Sensors
--Active Alarms
19Causal Chains

THE MANIFESTO

Individual issues are identified, but their impact on the overall systemunderestimated.

— Michael Wentzke, IG Biogasmotoren. Wentzke describes the core problem of modern CHP plants: data is available, but not actionable for leadership. Decisions are based on good feeling, not on numbers. We solve this withDecathlon Logic+ Causal Engine — each of the 10 disciplines measurable, holistically connected, with encoded engineering knowledge.

# Causal Engine — Layer 2: Traversing Causal Chains CAUSAL CHAINS = { "K01": { // Wentzke D3 Mixture Preparation "name": "Gas Quality → Engine → Power", "trigger_var": "awite_gasanalyse_rch1_ch4", "trigger_op": "<", "trigger_limit": 50.0, "effect": "Lambda decreases → Cylinder temps rise → Power decreases", "subsystems": [1, 3, 4, 6, 8], }, # ... 18 additional causal chains }

10 DISCIPLINES · DECATHLON LOGIC

Ameasurable discipline after another.

Methodology after Michael Wentzke (IG Biogasmotoren). Each discipline monitored by our live sensors. Real-time assessment against manufacturer limits and 30 years of field experience.

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THE COMPUTATIONAL STACK

Knowledgeencoded. dataconnected. forecastsvalidated.

LAYER 0
feeding
Substrate mix → KTBL → Target gas production
SCHICHT 1
subsystems
10 Wentzke disciplines, 70 sensors with 3-stage limits
SCHICHT 2
Causal Chains
19 chains K00-K19, traversing domain knowledge
SCHICHT 3
Market + heat
Electricity price · Weather · 53 district heating customers
SCHICHT 4
forecasts
Delayed predictions in ClickHouse
SCHICHT 5
Validation
Learned Confidence per Causal Chain