Abstract: Described herein are systems and methods for evaluating and mitigating the wax risks of a given hydrocarbon composition such as crude oil. The disclosed systems and methods enable rapid and ready prediction of wax risks using algorithms based on a small sample of the hydrocarbon composition. The wax risks are predicted using predictive models developed from machine learning. The disclosed systems and methods include mitigation strategies for wax risks that can include chemical additives, operation changes, and/or hydrocarbon blend.

Abstract: Described herein are systems and methods for evaluating and mitigating the wax risks of a given hydrocarbon composition such as crude oil. The disclosed systems and methods enable rapid and ready prediction of wax risks using algorithms based on a small sample of the hydrocarbon composition. The wax risks are predicted using predictive models developed from machine learning. The disclosed systems and methods include mitigation strategies for wax risks that can include chemical additives, operation changes, and/or hydrocarbon blend.

Abstract: A genset monitoring and control device that interactively monitors and can control a genset having an internal network over which engine data is communicated is implemented with a network interface for coupling with the genset's internal network to receive engine data therefrom and pass data and commands thereover. The genset monitoring and control device's processor uses the engine data received directly from the genset's internal network via the network interface to control and monitor the operation of the genset. Also, the genset monitoring and control device can request various engine data from the genset's internal network, and command new data to be collected in response to a command. The internal network is preferably a controller area network (CAN), and the engine data is preferably communicated on the CAN in the SAE J1939 messaging protocol.