A distributed coupled framework system was developed. The framework consists of atmosphere model (MM5), ocean model (Princeton Ocean Model), wave model (WW3) and a coupled programme (coupled model). The coupled programme controls atmosphere–wave–ocean model calculations and data exchanges. The impact of air–sea–wave interactions was considered to examine the validity and performance of this coupled model. Two typical typhoon cases Vongfong (No. 0214) and Rananim (No. 0414) were modelled to examine the wave simulation validity in the China Seas. The coupled model can obviously improve the precision of the significant wave height when compared with the uncoupled run.

To improve the productivity of oil wells, perforation technology is usually used to improve the productivity of horizontal wells in oilfield exploitation. After the perforation operation, the perforation channel around the wellbore will form a near-well high-permeability reservoir area with the penetration depth as the radius, that is, the formation has different permeability characteristics with the perforation depth as the dividing line. Generally, the permeability is measured by the permeability tester, but this approach has a high workload and limited application. In this paper, according to the reservoir characteristics of perforated horizontal wells, the reservoir is divided into two areas: the original reservoir area and the near-well high permeability reservoir area. Based on the theory of seepage mechanics and the formula of open hole productivity, the permeability calculation formula of near-well high permeability reservoir area with perforation parameters is deduced. According to the principle of seepage continuity, the seepage is regarded as the synthesis of two directions: the horizontal plane elliptic seepage field and the vertical plane radial seepage field, and the oil well productivity prediction model of the perforated horizontal well is established by partition. The model comparison demonstrates that the model is reasonable and feasible. To calculate and analyze the effect of oil well production and the law of influencing factors, actual production data of the oilfield are substituted into the oil well productivity formula. It can effectively guide the technical process design and effect prediction of perforated horizontal wells.

Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO₂, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions.

In the field of maritime transportation, precise accurate prediction of ship-speed is paramount for route planning, ship scheduling, and navigational safety. However, the difficulty of the prediction lies in the fact that ship-speed is influenced by numerous complex and variable factors, and traditional speed prediction methods often struggle to attain the desired accuracy in the presence of complex maritime environments and ship characteristics. To address this challenge, this paper aims to develop a robust ship-speed prediction model capable of effectively capturing complex data relationships and improving prediction accuracy and stability. A stacking ensemble learning model is proposed, integrating extra trees (ET), random forest (RF), categorical boosting (CatBoost), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and histogram gradient boosting (HGBT) as base learners, with support vector machine (SVM) as the meta-learner to leverage diverse models’ strengths. A standardized workflow for data cleaning, multi-source data fusion, and feature engineering is established. Additionally, the SHapley Additive exPlanation (SHAP) is introduced for model interpretability. Experiments with historical trajectory data from five ships and meteorological-oceanographic data show that the stacking model outperforms single models in prediction accuracy and stability. SHAP analysis reveals that ship course and wave height are key influencing factors, with their impact varying across different navigation scenarios. The proposed model enhances operational efficiency, safety, and decision-making in the maritime industry by providing reliable speed predictions and interpretable insights.

Formulating effective typhoon avoidance routes is crucial for ensuring the safe navigation of ocean-going vessels. From a maritime safety perspective, this paper investigates ship route optimization under typhoon forecast uncertainty. Initially, the study calculates the probability of a ship encountering a typhoon based on the distribution of historical typhoon data within the radius of seven-level winds and the distance between the ship and the typhoon. Subsequently, the minimum safe distance is quantified, and a multi-objective ship route optimization model for typhoon avoidance is established. A three-dimensional multi-objective ant colony algorithm is designed to solve this model. Finally, a typhoon avoidance simulation experiment is conducted using Typhoon TAMRI and a classic route in the South China Sea as a case study. The experimental results demonstrate that under adverse conditions of uncertain typhoon forecasts, the proposed multi-objective typhoon avoidance route optimization model can effectively avoid high wind and wave areas of the typhoon while balancing and optimizing multiple navigation indicators. This model can serve as a reference for shipping companies in formulating typhoon avoidance strategies.

Weather routing of ships is increasingly recognized as an important contribution to safe, economical and reliable ship route. The environmental factors which mainly include wind, wave and current may severely affect ships' safety, speed and fuel consumption depending on their force and direction, so ship route should be decided and updated with the weather changes gradually. This paper outlines the basic isochrone method and attempts to obtain an optimal route on the basis of the dynamically changing weather, which can be forecasted by the coupled atmosphere-wave-ocean model. The forecasted weather and its changes are taken into account to estimate the isochrones and the time-minimum route step by step, and the route will be rectified with the updated environmental factors during the voyage. Finally, the time-minimum weather route is determined with the consideration of environmental factors and their changes.