Reliability Analysis of Repairable Systems Using Stochastic Point Processes

In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.

Seismic response evaluation of the impact of corrosion on buried pipelines based on the Markov process

Water distribution and gas supply systems are among the infrastructure systems that have many buried steel pipelines. Corrosion gradually appears inside and outside of the pipe walls over the service life of these pipelines, the corrosion is primarily caused by the surrounding soil and the materials that flow through the pipelines. However, due to the uncertainty of the characteristics of the soil and materials, the size of the corrosion region is a stochastic variable. In this paper, using a homogeneous Markov process, a model is presented to simulate the occurrence of corrosion. Then, in combinations with a linear corrosion development model, the probability density function of the pipeline area corrosion percentage is derived. Based on the corrosion model, the pipeline seismic displacements and stresses are predicted. Furthermore, using the random perturbation approach, the mean and variance of the pipeline seismic response are given. To illustrate the validity of the proposed approach, a 200-meter long pipeline is numerically investigated and its random seismic response is obtained.

Solar Photochemical Pre-Treatment for Sulphurous Ground Water Purification Process

The sulfurous water deposit exploitation in volcanic, swamp, or wetland regions, represents an alternative option for potable water supply in cities and communities around the world. However, before its consumption, it must be treated by the application of physicochemical or biological methods with the ability to separate high contents in sulfates, hydrogen sulphite and sulphides which have laxative, allergic and toxic properties in humans. Conventional methods require the supply of chemical compounds or the adequate control of different parameters such as pH, temperature, etc., and the constant maintenance within their reactors. For these reasons, the systems could have elevated operating costs and require additional steps to enable the treatment of its separated products and the final disposal of its residual waste generated. In this research, compound parabolic collectors are implemented for the use of solar energy radiation, UV-B type, in Solar Advanced Oxidation Processes in H2O2/O3/UVsolar homogeneous phase. Its application during the pre-treatment of four sulfur water wells from the region of Puebla, Mexico, demonstrated its ability to transform their sulfur compounds in sulfates of easy removal by a later stage of reverse osmosis, in an approximately 15 min treatment time process.

DURATION OF NEGATIVE SURPLUS FOR A TWO STATE MARKOV-MODULATED RISK MODEL

We consider a continuous time risk model based on a two state Markov process, in which after an exponentially distributed time, the claim frequency changes to a different level and can change back again in the same way. We derive the Laplace transform for the first passage time to surplus zero from a given negative surplus and for the duration of negative surplus. Closed-form expressions are given in the case of exponential individual claim. Finally, numerical results are provided to show how to estimate the moments of duration of negative surplus.

Resolving Mixed Intermediate Phases in Methylammonium-Free Sn-Pb Alloyed Perovskites for High-Performance Solar Cells

The complete elimination of methylammonium(MA)cations in Sn-Pb composites can extend their light and thermal stabilities.Unfortunately,MA-free Sn-Pb alloyed perovskite thin films suffer from wrinkled surfaces and poor crystallization,due to the coexistence of mixed intermediate phases.Here,we report an additive strategy for finely regulating the impurities in the intermediate phase of Cs_(0.25)FA_(0.75)Pb_(0.6)Sn_(0.4)I_(3)and,thereby,obtaining high-performance solar cells.We introduced d-homoserine lactone hydrochloride(D-HLH)to form hydrogen bonds and strong Pb-O/Sn-O bonds with perovskite precursors,thereby weakening the incomplete complexation effect between polar aprotic solvents(e.g.,DMSO)and organic(FAI)or inorganic(CsI,PbI_(2),and SnI_(2))components,and balancing their nucleation processes.This treatment completely transformed mixed intermediate phases into pure preformed perovskite nuclei prior to thermal anneal-ing.Besides,this D-HLH substantially inhibited the oxidation of Sn^(2+) species.This strategy generated a record efficiency of 21.61%,with a Voc of 0.88 V for an MA-free Sn-Pb device,and an efficiency of 23.82%for its tandem device.The unencapsulated devices displayed impressive thermal stability at 85℃ for 300 h and much improved continuous operation stability at MPP for 120 h.

Arithmetic Reduction of Intensity or Age Models with Bathtub Failure Intensity

In this paper, the authors will study the estimation of maintenance efficiency in Arithmetic Reduction of Intensity （ARI） and Arithmetic Reduction of Age （ARA） models with a memory m. These models have been proposed by Doyen （2005）, the failure process is simply Non Homogeneous Poisson Process （NHPP）. Our models are defined by reformulation of ARI and ARA ones using bathtub failure intensity. This form is presented like a superposition of two NHPP and Homogeneous Poisson Process （HPP）. Moreover, the particularity of this model allows taking account of system state improvement in time course. The maintenance effect is characterized by the change induced on the failure intensity before and after failure during degradation period. To simplify study, the asymptotic properties of failure process are derived. Then, the asymptotic normality of several maintenance efficiency estimators can be proved in the case where the failure process without maintenance is known. Practically, the coverage rate of the asymptotic confidence intervals issued from those estimators is studied.

Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

Due to irregular deployment of small base stations （SBSs）, the interference in cognitive heterogeneous networks （CHNs） becomes even more complex; in particular, the uncertainty of spectrum mobility aggravates the interference context. In this case, how to analyze system capacity to obtain a closed-form expression becomes a crucial problem. In this paper we employ stochastic methods to formulate the capacity of CHNs and achieve a closed-form expression. By using discrete-time Markov chains （DTMCs）, the spectrum mobility with respect to the arrival and departure of macro base station （MBS） users is modeled. Then an integral method is proposed to derive the interference based on stochastic geometry （SG）. Also, the effect of sensing accuracy on network capacity is discussed by concerning false-alarm and miss-detection events. Simulation results are illustrated to show that the proposed capacity analysis method for CHNs can approximate the conventional sum methods without rigorous requirement for channel station information （CSI）. Therefore, it turns out to be a feasible and efficient way to capture the network capacity in CHNs.