A random-effects model for long-term degradation analysis of solid oxide fuel cells

Solid oxide fuel cells (SOFCs) are electrochemical devices converting the chemical energy into electricity with high efficiency and low pollutant emissions. Tough very promising, this technology is still in a developing phase, and degradation at the cell/stack level with operating time is still an issue of major concern. Methods to directly observe degradation modes and to measure their evolution over time are difficult to implement, and indirect performance indicators are adopted, typically related to voltage measurements in long-term tests. In order to describe long-term degradation tests, three components of the voltage measurements should be modelled: the smooth decay of voltage over time for each single unit; the variability of voltage decay among units; and the high-frequency small fluctuations of voltage due to experimental noise and lack of fit. In this paper, we propose an empirical random-effects regression model of polynomial type enabling to evaluate separately these three types of variability. Point and interval estimates are also derived for some performance measures, such as the mean voltage, the prediction of cell voltage, the reliability function and the cell-to-cell variability in SOFC stacks. Finally, the proposed methodology is applied to two real case-studies of long-term degradation tests of SOFC stacks

A New Estimation Algorithm for Interval Censored Data from Repairable Systems

For a minimally repaired system, whose failure process is described by a non-homogeneous Poisson process (NHPP), the classical maximum likelihood estimation procedures cannot be used when the system failures are hidden and detected only at inspection epochs. By assuming that the failure process follows a NHPP with power law intensity function, the Expectation-Maximization (EM) algorithm was recently proposed to estimate the model parameters and a procedure to test the presence of trend in the real failure data of some components of identical medical infusion pumps was discussed. However, the EM algorithm suffers in this application from some limitations due to its complexity and the large computational time required for convergence. This paper proposes a new estimation algorithm which is still iterative but, unlike the EM algorithm, is not based on the expectation of the log-likelihood function with respect to the conditional distribution of the unobserved data, but rather on the expectation of the conditioning variables, that is, of the unknown age of the system at the previous failure. This approach allows one to specify a simpler and much faster estimation procedure. A comparison between the proposed and the EM algorithms shows that the former performs as well as the latter, while requiring a drastically reduced computational burden. In addition, the proposed scheme can be applied to other intensity functions, such as the log-linear and the 2-parameter logarithmic functions. As a result, the test hypothesis of no trend in one of the analyzed datasets, which can not be rejected under the power law intensity function, is instead rejected under the alternative hypothesis of a log-linear intensity function

Semi-Markov Models for Performance Evaluation of Telecommunication Networks in the Presence of Failures

Planning and deployment of next generation telecommunication networks based on the Third Generation Partnership Project IP Multimedia Subsystem (IMS) must take into account the occurrence of random failures causing performance degradations, in order to assess and maintain the Quality of Service offered by telecommunication service providers to their subscribers. In particular, core network signalling servers of IMS can be modelled as repairable multi-state elements where server states correspond to different performance levels. In this paper, we evaluate IMS signalling network performance in terms of the number of sessions handled by the network per time unit, by adopting a semi-Markov model for the IMS servers, which allows as well for non-exponential probability distributions of sojourn times, as often observed in practical network scenarios. Furthermore, a redundancy optimisation problem is solved in an IMS-based realistic scenario, to the aim of minimizing the deployment cost of a telecommunication network with a given availability requirement

HASFC: a MANO-compliant Framework for Availability Management of Service Chains

Most softwarized telco services are conveniently framed as Service Function Chains (SFCs). Indeed, being structured as a combination of interconnected nodes, service chains may suffer from the single point of failure problem, meaning that an individual node malfunctioning could compromise the whole chain operation. To guarantee "highly available" (HA) levels, service providers are required to introduce redundancy strategies to achieve specific availability demands, where cost constraints have to be taken into account as well. Along these lines we propose HASFC (standing for High Availability SFC), a framework designed to support, through a dedicated REST interface, the MANO infrastructure in deploying SFCs with an optimal availability-cost trade off. Our framework is equipped with: i) an availability model builder aimed to construct probabilistic models of the SFC nodes in terms of failure and repair actions; ii) a chaining and selection module to compose the possible redundant SFCs, and extract the best candidates thereof. Beyond providing architectural details, we demonstrate the functionalities of HASFC through a use case which considers the IP Multimedia Subsystem, an SFC-like structure adopted to manage multimedia contents within 4G and 5G networks

Secure Mobile IPv6 for Mobile Networks based on the 3GPP IP Multimedia Subsystem

The rapid spread of new radio access technologies and the consequent service opportunities have stimulated thetechnical and scientific community to investigate future evolution scenarios for 3rd Generation networks (3G), generically referred to as Beyond-3G or 4G. They are going to be characterized by ever stronger requirements for security, as well as the capability for the final users to experience continuous connectivity and uninterrupted services of IP applications as they move about from one access network to another. Key issues are: i) securityprovision for applications exchanging data in diverse wireless networks; ii) seamless mobility (handoff) between different coverage domains and, in case, access technologies. Since many proposals are based on the use of the Mobile IPv6 protocol, in this paper we analyze the security threats emerging from some Mobile IPv6 mechanisms for mobility management, and we propose a solution against such threats, under the assumption that both end users (mobile or not) are attached to a Mobile IPv6-enabled 3GPP IP Multimedia Subsystem network

Innovative approaches to active and healthy ageing: Campania experience to improve the adoption of innovative good practices

The demographic projections on the European population predict that people aged over 60 will increase by about two million/year in the next decades. Since 2012, the Campania Reference Site of the European Innovation Partnership on Active and Healthy Ageing supports the innovation of the Regional Health System, to face up demographic changes and sustainability. Campania Reference Site provides the opportunity to connect loco-regional stakeholders in social and health care services (universities, healthcare providers, social services, local communities and municipalities), with international organizations, in order to adopt and scale up innovative solutions and approaches. This paper describes the building process of Campania Reference Site and the main results achieved, that have been allowing it to become a hub for open innovation in the field of active and healthy aging at regional, national and international level

A Bayesian approach for non-homogeneous gamma degradation processes

A Bayesian approach based on the Markov Chain Monte Carlo technique is proposed for the non-homogeneous gamma process with power-law shape function. Vague and informative priors, formalized on some quantities having a â\u80\u9cphysicalâ\u80\u9d meaning, are provided. Point and interval estimation of process parameters and some functions thereof are developed, as well as prediction on some observable quantities that are useful in defining the maintenance strategy is proposed. Some useful approximations are derived for the conditional and unconditional mean and median of the residual life to reduce computational time. Finally, the proposed approach is applied to a real dataset