柴油机排气微粒冷却演变特性的实验研究

对柴油机排气微粒在冷却条件下的演变特性进行了实验研究.结果表明,排气的冷却作用对微粒的质量浓度具有重要的影响.引起微粒质量浓度变化的主要原因是排气中气态碳氢的冷凝,从而增加了微粒的质量浓度.排气的冷却促使柴油机微粒增大,分布在0.01～1.0 μm粒径范围内的微粒数量有所减少,特别是小于0.1 μm以下的小微粒,微粒数量下降的幅度相对较大,并且冷却温度越低,变化越明显.排气冷却后,0.1-1.0 μm粒径范围内的微粒体积浓度呈减少的趋势.此外,流速对排气冷却条件下的微粒演变特性亦有一定的影响,随排气流速的降低,0.01～1.0 μm粒径范围内的微粒数量浓度和体积浓度减小.     

城市污水处理厂二级出水深度处理回用的设计与运行

将城市污水作为工业循环冷却补充水的水源已成为世界各国解决缺水问题的主要方案之一,但二级出水水质不符合循环冷却水对CODCr、硬度、氮、磷等指标要求,必须对其进行深度处理才能回用。本设计采用生物接触氧化+絮凝沉淀+机械搅拌澄清+连续动态过滤+消毒工艺,其出水补充至电厂循环冷却水系统。运行实践表明,该工艺处理效率高,动力消耗少,出水水质达到循环冷却水水质标准,且经过对工艺的改进完善,使操作更加简便,设备运行更加稳定。     

喹啉季铵盐絮凝-缓蚀剂FNQ-C的制备及其性能研究

本文研究了天然高分子改性喹啉季铵盐型阳离子絮凝-缓蚀剂FNQ-C的制备,确定了其最佳制备反应条件;考察了FNQ-C在模拟循环冷却水中的絮凝、缓蚀性能.絮凝实验表明FNQ-C的絮凝净水效果优于国产阳离子聚丙烯酰胺絮凝剂PAM-C,挂片腐蚀实验表明FNQ-C的缓蚀性能与国产商品缓蚀剂EDTMP相当.实验亦证实FNQ-C的缓蚀用药量与其絮凝净化用药量相容,可以一次投药同步满足絮凝、缓蚀两种水质要求.     

优化循环冷却水系统技术经济分析模型研究

应用系统分析方法以及最优化技术研究循环冷却水系统,分析了系统内部水量、水质等条件与系统运行费用之间的关系,运用技术经济的方法建立了循环冷却水的数学模型,通过判定最佳循环冷却水浓缩倍数确定系统的最优化结果,使循环冷却水系统的设计和运行管理更为科学合理.     

原位电化学杀菌技术处理循环冷却水

分别以金属氧化电极和不锈钢为阳极和阴极,在恒电流模式下,考察了电流密度、停留时间、放置时间、极间距和稀释比等因素对电厂循环冷却水杀菌效果的影响。实际现场结果表明,针对电厂循环冷却水,电化学杀菌处理是行之有效的,电流密度、停留时间、极间距、稀释比对杀菌效果影响较大;在电流密度120 A/m2、停留时间10 s、极间距1.8 cm的条件下,杀菌效果可以达到97%;在一定实验条件下及一定放置时间内,经处理后的循环冷却水异氧菌总数能得到有效抑制。     

电磁阻垢技术在火电厂大型循环水系统中的适用性研究

通过电磁阻垢技术在火电厂大型循环水系统中的应用情况进行研究分析,发现火电厂大型循环冷却水系统单独采用电磁阻垢处理方式和传统化学加药处理方式相比尚有欠缺,电厂在选择电磁阻垢处理方式进行循环水系统处理时应持谨慎态度,应用前应进行考证和试验。对于已采用电磁阻垢处理方式的电厂应加强循环水水质监督和机组热力参数监督,一旦发生异常情况,应立即恢复化学加药处理或进行两种方式的联合处理。     

适合严寒地区直流换流站外冷却系统的研究

针对目前严寒地区直流换流站外水冷系统多采用空气冷却方式,而空气冷却方式存在造价高、占地多、运行费用高等不利因素,设计了一种新型外水冷系统,冬季利用漏水孔板淋水带走内水冷系统的热量,并采取必要的防冻措施。该系统应用于北方严寒地区,可以大大降低初投资,减少占地面积,运行费用降低,噪声减小,同时也保证了直流输电系统的安全可靠运行,具有极大的经济效益和推广价值。     

烟塔排烟电厂大气影响预测分析

在系统分析我国烟塔排烟电厂大气影响评价及其相关研究成果的基础上,指出应关注的几个问题,并结合烟塔排烟电厂的负荷变化特点提出了解决问题的基本思路及需要重点研究的专题。     

Experimental investigation on the phase change material-based modular heat exchanger for thermal management of a building

A phase change material (PCM)-based flat plate modular heat exchanger for free cooling application, suitable for the diurnal temperature variation that prevails during the summer months of Bangalore city, India is designed and experimentally investigated. The flow and other parameters selected in the present study are meant to suit the accelerated charging of the PCM in the modular heat exchanger during the early morning hours, and to provide cool energy to the room during the daytime, by circulating the ambient air through the heat exchanger at a lower velocity. It is observed from the charging experiments that the decrease in the inlet air temperature has more influence in reducing the solidification time than the increase in the inlet air velocity. The heat exchanger designed in the present investigation is capable of maintaining the room temperature around 30°C for a longer duration of 8 hr when the heat load is 0.5 kW. It is suggested to design the modular heat exchanger with a surface area proportionate to the present heat exchanger size when the room heat load increases beyond 0.5 kW, in order to maintain a minimum comfortable temperature of 30°C in the room.     

A novel objective function for optimal DG allocation in distribution systems using meta-heuristic algorithms

Meta heuristic algorithms have been introduced as a powerful method to solve the nonlinear optimization problems. These algorithms have been employed in many complex engineering problems due to their high capability in finding the solutions and reaching the optimal results within a short period of time. Optimization of distributed generation units in distribution systems, which have profoundly impacted on the system losses and voltage profile, is one of these nonlinear problems. In this study, a novel objective function was proposed for optimization procedure by meta-heuristic algorithms. The related objective function consists of the total cost of distributed generation units, cost of the purchased natural gas, cost of distribution system power losses, and penalty for greenhouse gas emissions. The electrical, cooling, and heating loads were considered in this study. In the distribution system, the waste and fuel cell were used to supply the required heating and cooling loads. The meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Imperialist Competitive Algorithm (ICA) were employed to find the optimal location and size of distributed generation units in a distribution system. A detailed performance analysis was done on 13 bus radial distribution system. The performances of three algorithms were compared with each other and results showed that the PSO was the fastest; and had the best solution and optimum results. Furthermore, the PSO reached the optimum solution in a fewer number of iterations than the GA and ICA algorithms.