Liaoning Technical University

Pulsating heat pipes (PHPs) are promising passive heat-transfer devices for compact thermal management; however, their performance is highly sensitive to channel geometry. In particular, the operating-condition-dependent influence of sinusoidal corrugation amplitude on the condenser side remains unclear, despite its importance for oscillation regulation and heat dissipation. This numerical study investigates a single-loop PHP with sinusoidally corrugated condensers (A = 0.25 and 0.5 mm) under heat fluxes of 5000–12,500 W/m2 and filling ratios of 40–60%, using a uniform-diameter PHP as the baseline. The results show that the configuration with A = 0.25 mm exhibits better start-up performance, especially at low heat fluxes, whereas both corrugated configurations provide better thermal performance than the baseline. At a filling ratio of 50%, the thermal-resistance reductions for A = 0.25 and A = 0.5 mm are 14.5% and 9.2% at 5000 W/m2 and 8.4% and 10.5% at 12,500 W/m2, respectively. An operating-condition-dependent amplitude-matching relationship is identified: The smaller amplitude is more favorable for start-up under weak driving conditions, whereas the larger amplitude tends to provide lower thermal resistance and higher equivalent thermal conductivity under strong driving conditions. These findings provide useful guidance for condenser-geometry optimization in single-loop PHPs.

To enhance the accommodation capability and operational flexibility of renewable energy systems, address the insufficient architectural integration of existing ammonia-based energy systems, and overcome the limitations of current optimization algorithms in tackling complex nonlinear multi-objective problems, this paper proposes a synergistic integrated energy system with liquid ammonia as the central hub. The system integrates multi-energy flows encompassing electricity, hydrogen, ammonia, and heat, leveraging ammonia fuel cell power generation, ammonia cracking, and ammonia-blended gas turbines for both electricity and heat production. A bi-level optimization model is formulated, coupling upper-layer multi-objective capacity planning with lower-layer stochastic chance-constrained scheduling. To solve this model, a hybrid algorithm, designated as LSDBO-WOA, is developed by integrating an improved dung beetle optimizer (LSDBO) with the whale optimization algorithm (WOA). Case study results demonstrate that the proposed algorithm achieves markedly superior convergence performance compared to benchmark algorithms such as non-dominated sorting genetic algorithm II (NSGA-II), with an improvement of approximately 18.6% in comprehensive performance metrics. Furthermore, the proposed electricity-hydrogen-ammonia-heat system attains an overall energy efficiency exceeding 97.66% and reduces carbon emissions by 7.3% relative to the original system without ammonia integration.