Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems.

The blending of hydrogen in natural gas may have effects on the safety of its usage in a domestic house. In this work, the leakage accident of hydrogen-blended natural gas (HBNG) in the kitchen of a domestic house is analyzed by CFD with a hydrogen blending ratio (HBR) ≤ 30%. The whole process is divided into the gas accumulation process and the ventilation process. In the initial leakage stage, the influence of heights and the HBR on the gas distribution is analyzed. HBNG concentration increases with increasing height. Based on the exit Froude number, the formation of a gas cloud in the kitchen is significantly influenced by the initial momentum and buoyancy, while it is more driven by the concentration gradient beyond the kitchen. In contrast to height, the variation of HBR on the HBNG distribution is not significant. In the ventilation process, the evolution of the hazardous gas cloud volume is analyzed. With windows and doors closed, the hazardous gas cloud fills the house in approximately 3600 s after the leakage occurs. When windows and doors are open for ventilation, the volume of the hazardous gas cloud first declines rapidly and then slowly. The reasons for the variation rate of hazardous gas cloud volume are analyzed according to ventilation conditions. The difference during the decline stage for different HBRs is analyzed according to the gas layering properties. Under a lack of convection condition, the ventilation process finally reaches a stagnant stage. In addition, another ventilation process has been investigated after extending the gas accumulation time. After extending the gas accumulation time, the effect of different HBRs on the ventilation process remains the same as before. However, it postpones the time point to enter the stagnation stage. As gas accumulation time extends from 3600 to 5400 and 7200 s, the ventilation time into the stagnation stage increases from about 4800 to 5400 and 6000 s, respectively. This study has implications for the establishment of a risk assessment system based on hazardous gas cloud volume.