空冷器用高压水清洗与雾化降温系统集成设计与开发

高压水清洗系统和喷淋降温系统分别是春季保持空冷器翅片表面清洁和夏季保证空冷器在高温下正常运行的2个重要辅助系统。针对喷淋系统的缺点研究了高压射流雾化技术,通过试验论证了高压水清洗与雾化降温系统集成的可行性和合理性。根据设计思路开发的集成系统已在山西某项目获得应用并取得了良好的使用效果,此高压水清洗与雾化降温集成系统中高压水发生装置及介质输送管路共用,产生的高压水射流雾化颗粒可达到60μm,夏季降温效果较传统喷淋降温效果大幅提升,水资源的利用率得到极大提高,系统性价比更高。     

Exploring the role of the sharing economy in disasters management

Improvements in information and communications technologies (ICTs) have facilitated the inclusion of the sharing economy (SE) in societies more than ever. In the aftermath of recent disasters, the SE played significant roles to help the affected people and support official responders. However, the literature has not effectively explored these roles, and thus, no framework can support the systematic inclusion of the SE in disasters management. This paper aims to address the gap through a two-stage exploratory research approach. First, we conduct a systematic literature review to identify the extent to which the SE is taken into consideration in disasters. After that, we investigate the role of three Iranian SE-based companies that were involved in the 2019 Iran floods response. We collect empirical data by conducting semi-structured interviews and reviewing official reports.Our findings indicate that very few studies discuss the different roles of the SE in disasters, although SE companies have often provided effective solutions to address critical post-disaster logistics challenges. Four research propositions are presented to describe emerging roles for SE companies. The contribution of our study is twofold. First, our research identifies the different roles that the SE could play in disasters and therefore, brings a new perspective to the literature. Second, the study suggests opportunities for collaboration and partnership models from the point of origin to delivery that can support coordination and logistics in disasters.     

基于模拟退火优化BP神经网络的变形监测数据预测方法

针对BP神经网络模型用于变形监测数据处理时容易陷入局部极小值并且收敛速度慢的问题，提出一种基于模拟退火(Simulated Annealing,SA)算法优化BP神经网络的建筑物变形预测方法，利用SA的全局寻优能力对BP神经网络的模型参数进行优化，使参数迭代过程始终保持较高的“温度”和“能量”，从而确保BP神经网络能够得到全局最优解的同时具备较高的预测精度和收敛速度。采用实际算例对所提SA-BP方法在低信噪比和小样本条件下的预测精度进行验证，结果表明所提方法相对于传统BP神经网络法和小波方法能够获得更高的预测精度，并且在小样本和低信噪比条件下优势更加明显。     

浅析火力发电厂汽水系统中内径管与外径管的设计选择

按照管道加工工艺的不同,管道可分为内径控制管和外径控制管。通过热轧工艺生产的外径控制无缝钢管,可满足火力发电厂汽水系统中绝大部分管道的使用要求。对于超(超)临界机组的主蒸汽和高温再热蒸汽管道采用的P91/P92材质的大口径厚壁无缝钢管,由于对材料性能和加工工艺有特殊要求,因此宜采用内径控制管。     

Analysis and assessment of a nanoparticle seeded small scale absorption refrigeration system driven by a low‐grade waste heat source

The thermoeconomic behaviour of a nanoparticle seeded single effect LiBr‐H₂O absorption refrigeration system (ARS) is investigated for a small scale application. In the proposed method, alumina nanoparticles with volume concentrations of 3%, 5%, and 7% are dispersed into an aqua lithium bromide solution. The multiobjective heat transfer search algorithm is employed to examine the design trade‐off between the coefficient of performance (COP) and total annualized cost (TAC). To analyze the overall performance of the system, the influence of five design parameters, namely the temperatures of the generator, absorber, evaporator, condenser and heat exchanger pipe diameter, are studied. It is found that with an increase in the COP, the TAC of the system is initially raised marginally, and after that, raised rigorously with further increment. The comparative results indicate that the COP and TAC of the nanofluid based ARS system are increased by about 7% and decreased by about 3.2%, respectively, corresponding to the Pareto points of the base ARS system. A lower break‐even point of about 2.6 years is achieved for the ARS system containing nanoparticles compared to the base ARS system. Overall, the ARS system containing 5% nanoparticles is the best solution from a thermodynamic and economic point of view.     

Performance-based modelling of long-term deterioration to support rehabilitation and investment decisions in drinking water distribution systems

Managing the urban drinking water system in the long term in order to maintain system performance can be challenging due to the difficulty of modelling future deterioration of the networks. This paper establishes a methodology for cohort survival models where historical (empirical) data on decommissioning ages of pipes are used to calibrate survival functions of pipe cohorts according to service level targets. The benefit of the approach is that remaining useful life of pipes, future renewal rates and investment needs can be governed by a required level of service in the network. A case study shows how the methodology can be applied to a cohort of drinking water pipes to create a ‘calibration curve’, which is a survival function calibrated with empirical data.     

水电站大型竖井施工安全风险控制措施研究

竖井是大型水电工程中广泛采用的重要建筑物,但竖井的传统施工方法存在施工程序复杂、人工劳动强度大、施工效率不高等特点,同时还存在较大的安全风险。通过对杨房沟水电站大型竖井施工过程的研究,总结出精细化控制爆破、小溜渣井施工方式,同时也设计了一套用于运输的综合提升系统。采用上述创新方法不仅减少了繁琐的施工程序,降低了安全施工风险,而且大量采用机械化手段进一步提高了施工效率,确保了该工程竖井施工的安全风险可控。相关措施可为类似工程的竖井施工提供较好的借鉴作用。     

Incomplete analytic hierarchy process with minimum weighted ordinal violations

ABSTRACT

Incomplete pairwise comparison matrices offer a natural way of expressing preferences in decision-making processes. Although ordinal information is crucial, there is a bias in the literature: cardinal models dominate. Ordinal models usually yield nonunique solutions; therefore, an approach blending ordinal and cardinal information is needed. In this work, we consider two cascading problems: first, we compute ordinal preferences, maximizing an index that combines ordinal and cardinal information; then, we obtain a cardinal ranking by enforcing ordinal constraints. Notably, we provide a sufficient condition (that is likely to be satisfied in practical cases) for the first problem to admit a unique solution and we develop a provably polynomial-time algorithm to compute it. The effectiveness of the proposed method is analyzed and compared with respect to other approaches and criteria at the state of the art.     

Hollow mesoporous silica nanoparticles as nanocarriers employed in cancer therapy: A review

Hollow mesoporous silica nanoparticles (HMSNs) have become an attractive drug carrier because of their unique characteristics including stable physicochemical properties, large specific surface area and facile functionalization, especially made into intelligent drug delivery systems (DDSs) for cancer therapy. HMSNs are employed to transport traditional anti-tumor drugs, which can solve the problems of drugs with instability, poor solubility and lack of recognition, etc., while significantly improving the anti-tumor effect. And an unexpected good result will be obtained by combining functional molecules and metal species with HMSNs for cancer diagnosis and treatment. Actually, HMSNs-based DDSs have developed relatively mature in recent years. This review briefly describes how to successfully prepare an ordinary HMSNs-based DDS, as well as its degradation, different stimuli-responses, targets and combination therapy. These versatile intelligent nanoparticles show great potential in clinical aspects.     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.