Reliability analysis of solar-gas hybrid receivers for Central Tower Plants

A novel Solar-Gas Hybrid Receiver (SGHR) that combines the function of a solar receiver and a gas boiler in a single device is presented. This concept requires less equipment and maintenance compared to the Solar Gas Hybrid(SGH) concept, in which the boiler and the solar receiver (SR) are independent devices. The economic benefit is attributed to the increased sharing of infrastructures. Additionally, it has less thermal stress, cycles and shocks, which reduce the failure risk. However, the additional benefit in the reliability of these receivers has not been analyzed so far. In this work, a mathematical model of SGHR is presented. It determines the stress in steady state which is used to estimate the allowable transient stress in order to achieve the required 30 years life design. The results show that the SGHR is exposed to lower thermal stress due to much better temperature distribution. Moreover the higher …info:eu-repo/semantics/publishedVersio

Exploring Statistical and Population Aspects of Network Complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples