UNS S32760超级双相不锈钢作为一种优良的高合金化材料,以其出色的耐腐蚀性和高强度特性,在石油、化工和船舶等强腐蚀环境中得到了广泛应用。然而,超级双相不锈钢在工程实践应用中存在成型和焊接等一些关键制造问题,需要重点研究和解决...UNS S32760超级双相不锈钢作为一种优良的高合金化材料,以其出色的耐腐蚀性和高强度特性,在石油、化工和船舶等强腐蚀环境中得到了广泛应用。然而,超级双相不锈钢在工程实践应用中存在成型和焊接等一些关键制造问题,需要重点研究和解决,以保证产品尺寸、材料和焊接接头性能满足制造要求。本文旨在通过对UNS S32760超级双相不锈钢的焊接工艺研究及应用案例,为该材料的工程应用提供数据支持和实践指导。展开更多
The differential evolution algorithm is an evolutionary algorithm for global optimization and the un-capacitated facility location problem (UFL) is one of the classic NP-Hard problems. In this paper, combined with the...The differential evolution algorithm is an evolutionary algorithm for global optimization and the un-capacitated facility location problem (UFL) is one of the classic NP-Hard problems. In this paper, combined with the specific characteristics of the UFL problem, we introduce the activation function to the algorithm for solving UFL problem and name it improved adaptive differential evolution algorithm (IADEA). Next, to improve the efficiency of the algorithm and to alleviate the problem of being stuck in a local optimum, an adaptive operator was added. To test the improvement of our algorithm, we compare the IADEA with the basic differential evolution algorithm by solving typical instances of UFL problem respectively. Moreover, to compare with other heuristic algorithm, we use the hybrid ant colony algorithm to solve the same instances. The computational results show that IADEA improves the performance of the basic DE and it outperforms the hybrid ant colony algorithm.展开更多
UN燃料具有铀密度高、熔点高、热导率高、热膨胀系数低、辐照稳定性好等优点，是未来空间核电源、核火箭、快堆和ADS的重要候选燃料。本文采用金属铀粉与氮气在300～400℃直接发生化合反应，制得单相U2 N3粉末。粒度为38.3μm的 U2 N3...UN燃料具有铀密度高、熔点高、热导率高、热膨胀系数低、辐照稳定性好等优点，是未来空间核电源、核火箭、快堆和ADS的重要候选燃料。本文采用金属铀粉与氮气在300～400℃直接发生化合反应，制得单相U2 N3粉末。粒度为38.3μm的 U2 N3粉末在1600℃真空热压烧结，制得相对密度为93.5％、存在少量金属铀相的U N陶瓷；而18.1μm的U2 N3粉末在1550℃真空热压烧结，制得相对密度为96.1％、不残留金属铀相的 U N陶瓷，U与N的总质量分数为99.57％，每个金属杂质含量均低于50μg/g ，氧含量为1048μg/g ，碳含量为502μg/g。U2 N3在1027℃以上将会完全分解成UN ，UN在1627℃以上也会发生分解。展开更多
文摘The differential evolution algorithm is an evolutionary algorithm for global optimization and the un-capacitated facility location problem (UFL) is one of the classic NP-Hard problems. In this paper, combined with the specific characteristics of the UFL problem, we introduce the activation function to the algorithm for solving UFL problem and name it improved adaptive differential evolution algorithm (IADEA). Next, to improve the efficiency of the algorithm and to alleviate the problem of being stuck in a local optimum, an adaptive operator was added. To test the improvement of our algorithm, we compare the IADEA with the basic differential evolution algorithm by solving typical instances of UFL problem respectively. Moreover, to compare with other heuristic algorithm, we use the hybrid ant colony algorithm to solve the same instances. The computational results show that IADEA improves the performance of the basic DE and it outperforms the hybrid ant colony algorithm.
