a general library for fatigue and reliability
fatpack provides functions and classes for fatigue analysis of data series.
Fast rainflow counting written in C (C99). Including wrappers for MATLAB and Python
Calculate and optimise fatigue crack growth
A C++ implementation of the ASTM E1049-85 rain flow cycle counting algorithm for fatigue analysis
This python script converts any speed/torque (or current/voltage) profile of an electric drive into thermal power cycles, and then quantifies the lifetime damage produced by that profile.
Rainflow‑aware DQN for battery dispatch (arbitrage + FR/reserves): Gymnasium env with safety layer, exact cycle‑based degradation, time features & stacked observations; SB3 training.
This QuickApp predicts the rain in Europe with data from the Buienradar, two hours in advance
AI-agent-native low cycle fatigue strain-life analysis. Python library plus MCP server: reduce strain-controlled test data, fit Basquin, Coffin-Manson, and Ramberg-Osgood models, predict life with mean-stress corrections, and save results for recall.
Measurement analysis for mechanical test engineers: messy CSV/TDMS/MDF4 in, vibration/fatigue/thermal answers out — CLI, HTML reports, and an MCP server for LLM-driven analysis.
Grid battery operations against warranty and LTSA: metered RTE with auxiliaries, contractual availability, cycles and warranty violations, capacity tests and SoH forecast; monthly Excel/HTML report; benchmarked on every NEM battery (AEMO) and validated with operator data.
Wind turbine loads from SCADA data: detection of edgewise blade instabilities and their fatigue cost in a simulated 12-turbine fleet, and a machine-learning load emulator for power de-rating, built on a reduced-order aero-servo-elastic model and checked against real 20 Hz measurements of the Björkö 45 kW research turbine.
Key performance indicators for operating PV, wind and battery assets: PR, availability, energy bridge, power curves, reliability, RTE, cycles, capacity tests and contract damages
Grid battery state of charge from market data (validated on operator SoC), LFP ageing model fitted to cell data, and degradation-aware arbitrage in Australia's NEM
Fast C++ implementations of fatigue cycle-counting algorithms with Python bindings.
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