Numerical analysis of the sediment erosion of the balance valve in a buoyancy regulation system was performed. A numerical model for the two-phase flow inside the balance valve was constructed based on the discrete phase model. The sediment erosion rate on the balance valve was discussed, and the effects of five parameters were considered. The effects of the sediment concentration and valve opening were found to be significant, while the effects of the pressure difference, sediment density, and size were found to be moderate. The erosion rate, according to the numerical results, increased linearly with the sediment concentration, so long-term operation of a buoyancy regulation system in high-concentration areas should be avoided. The erosion rate was the highest when the valve opening was 46.3%, so half-open operating conditions are not recommended. The erosion rate was proportional to the square root of the pressure difference. However, adjusting the pressure difference may not be an effective method for regulating the total erosion. The superposition of the secondary flow and the main stream caused particles to spiral along with the fluid, resulting in asymmetric erosion at the working edge. The erosion rate on the working edge decreased with the increase in the sediment size. Conversely, the erosion rate on the valve ball surface increased with the sixth power of the sediment size. Considering that large particles are more likely to cause a blockage, it is recommended to install a seawater pretreatment device at the inlet to prevent large sediments from entering the valve and to improve the working life of the buoyancy regulation system.

Dynamic target following in underwater environments is challenging because delayed target-state feedback, external disturbance, and model uncertainty can significantly reduce tracking performance. This paper proposes a delay-compensated predictive robust tracking method for underwater robots. A relative-following framework is first constructed by defining a reference point with a prescribed offset from the target. To reduce the adverse effect of delayed target information, a prediction mechanism is introduced for reference generation. A robust tracking controller is then designed to improve disturbance rejection and robustness against model mismatch. The proposed method is evaluated through multi-scenario simulations with progressively increased delay, target maneuverability, disturbance intensity, and uncertainty. Comparative results with PID, robust-only, and prediction-only controllers show that the proposed method achieves the smallest mean tracking error in all considered scenarios and provides more reliable tracking performance in difficult underwater conditions. The results demonstrate that the integration of delay compensation and robust control is effective for dynamic target-following tasks with delayed and uncertain target-state feedback.

Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-objective optimization can substantially reduce CFD evaluations, local prediction errors in decision-sensitive Pareto regions may alter feasibility classification and engineering recommendations near active constraints. To address this issue, this study proposes a Pareto-active-region-guided sequential surrogate modeling framework (PAR-SSM) for multi-objective optimization of liquid-cooled battery thermal management systems. Starting from 15 face-centered central composite design (FCCD) samples, the framework selectively introduces additional high-fidelity CFD evaluations into Pareto-active and constraint-sensitive regions, yielding a 21-sample refined surrogate model. Rather than uniformly improving global prediction accuracy, PAR-SSM directs the limited CFD budget toward regions where surrogate errors can directly influence engineering decisions. After model freezing, three independent Fluent cases were used exclusively for validation, yielding mean absolute deviations of 0.098 °C for maximum temperature and 0.341 °C for temperature difference, while also revealing residual feasibility risk near active constraint boundaries. Application to an autonomous underwater vehicle (AUV) battery module showed that the N = 3 configuration dominated the nominally constrained Pareto set and provided a favorable thermal–hydraulic trade-off under low auxiliary energy consumption. Overall, PAR-SSM provides a decision-oriented strategy for balancing computational cost and optimization credibility in CFD-intensive, constrained multi-objective design.