This research paper presents a comprehensive modeling approach for the common rail fuel injection system of a four-cylinder hydrogen-fueled engine. Hydrogen fuel, with its potential to contribute to a low-carbon energy landscape, necessitates a detailed understanding of its injection system dynamics. The study involves the development of a mathematical model that captures the intricate interactions within the common rail system, including high-pressure fuel storage, injector behavior, and pressure wave propagation. Through simulation and analysis, the model's accuracy and effectiveness in representing the hydrogen injection process are evaluated. This investigation sheds light on the critical aspects of hydrogen fuel injection, enhancing the knowledge base for optimizing engine performance and emissions in a sustainable energy context.

In the process of separating the fiber from the seed, the speed of the seed roll in the roll box of the saw gin varies depending on the diameter of the saw. As the blade diameter decreases, the peripheral speed does not change, but the linear speed does. This leads to a deterioration in the quality of the fiber and seed, and a decrease in the productivity of the machine. For this reason, the regulation of the linear speed of the saw is one of the important problems in the ginning process. To do this, the speed of rotation of the saw cylinder is changed following the change in the diameter of the saw. Thus, the speed of the seed roll is regulated.

This study presents a novel approach to efficiently monitor electronic equipment loads in ferry ship passenger rooms using Long Range Wireless Communication (LoRA) telemetry technology. The system enables real-time data collection, allowing ship operators to manage and optimize energy consumption effectively. By leveraging LoRA's long-range capabilities, the solution offers a cost-effective and reliable means of monitoring various electrical devices, enhancing passenger safety, comfort, and energy efficiency. This research showcases the potential of LoRA wireless telemetry in maritime applications, particularly in optimizing electronic equipment loads in passenger environments.

Efficient energy management and monitoring in maritime transportation play a crucial role in reducing operational costs and environmental impact. This study presents an innovative approach to monitor electronic equipment loads in passenger rooms aboard ferry ships using Low-Power Wide-Area Network (LoRaWAN) wireless telemetry technology.

The proposed system consists of IoT sensors equipped with LoRa transceivers strategically placed within passenger rooms to collect real-time data on the power consumption of electronic devices such as air conditioning units, lighting, and charging ports. These sensors communicate wirelessly with a central monitoring and control unit, providing ship operators with valuable insights into energy usage patterns.

Key features of this system include low power consumption, long-range communication capabilities, and scalability. By employing LoRaWAN technology, the system achieves reliable data transmission over extended distances, making it suitable for large vessels like ferry ships. Furthermore, the low-power nature of LoRa enables extended battery life for the sensors, reducing maintenance efforts.

The collected data is processed and analyzed to optimize energy usage and improve overall operational efficiency. Operators can remotely monitor and control electronic equipment loads, allowing for immediate adjustments in response to changing passenger demands or energy efficiency goals. Additionally, historical data analysis facilitates predictive maintenance, reducing downtime and repair costs.

This study showcases a successful implementation of the LoRa-based electronic equipment load monitoring system in a real-world ferry ship environment. Preliminary results demonstrate significant reductions in energy consumption and improved operational efficiency. Furthermore, the system contributes to sustainability efforts by lowering greenhouse gas emissions associated with maritime transportation.