Applying mechanistic models to reliability evaluation of mechanical components – An illustration

The traditional reliability analyses, considers components to be in binary state, either functional or faulty, and does not consider the concept of multi state or intermediate states between these two binary states. However, there are several components, which need to be operated in different states and their failure criterion also depend on these states. Hence, when dealing with these types of components one should use multi state concept. This can be achieved by modeling the components with mechanistic models, which can give a new dimension for reliability analysis for multiple states. The mechanistic model approach is based on the first principles of science and engineering which provides details about the various failure mechanisms and thereby improved understanding of the associated root causes of the failure and driving forces responsible for component failures. In this paper a general methodology for modeling the components with mechanistic models has been explained and is further illustrated with an example component. A case study on feed water system (consisting of control valves and other mechanical components) of a typical nuclear reactor has been presented.     

Structural, optical and electrical properties of indium tin oxide thin films prepared by spray pyrolysis

Spray pyrolysis process has been used to deposit highly transparent and conducting films of tin-doped indium oxide onto glass substrates. The electrical, structural and optical properties have been investigated as a function of various deposition parameters namely dopant concentrations, temperature and nature of substrate. The morphology of the surface as a function of the substrate temperature has been studied using atomic force microscopy. XRD has shown that deposited films are polycrystalline without second phases and have a preferred orientation (4 0 0). Indium tin oxide layers with low resistivity values around 4×10⁻⁵ Ω cm and transmission coefficients in the visible and near-infrared range of about 85–90% have been easily obtained.     

Target oriented network intelligence collection: effective exploration of social networks

World Wide Web - Target Oriented Network Intelligence Collection (TONIC) is a crawling process whose goal is to find social network profiles that contain information about a given target. Such...     

An Optimal Method for High-Resolution Population Geo-Spatial Data

Mainland China has a poor distribution of meteorological stations. Existing models’ estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature, and low for relative humidity and wind speed (few studies reported). This study compared the typical generalized additive model (GAM) and autoencoder-based residual neural network (hereafter, residual network for short) in terms of predicting three meteorological parameters, namely air temperature, relative humidity, and wind speed, using data from 824 monitoring stations across China’s mainland in 2015. The performance of the two models was assessed using a 10-fold cross-validation procedure. The air temperature models employ basic variables such as latitude, longitude, elevation, and the day of the year. The relative humidity models employ air temperature and ozone concentration as covariates, while the wind speed models use wind speed coarse-resolution reanalysis data as covariates, in addition to the fundamental variables. Spatial coordinates represent spatial variation, while the time index of the day captures time variation in our spatiotemporal models. In comparison to GAM, the residual network considerably improved prediction accuracy: on average, the coefficient of variation (CV) R² of the three meteorological parameters rose by 0.21, CV root-mean square (RMSE) fell by 37%, and the relative humidity model improved the most. The accuracy of relative humidity models was considerably improved once the monthly index was included, demonstrating that varied amounts of temporal variables are crucial for relative humidity models. We also spoke about the benefits and drawbacks of using coarse resolution reanalysis data and closest neighbor values as variables. In comparison to classic GAMs, this study indicates that the residual network model may considerably increase the accuracy of national high spatial (1 km) and temporal (daily) resolution meteorological data. Our findings have implications for high-resolution and high-accuracy meteorological parameter mapping in China.     

Global characteristics of low-flow-rate aviation fuel sprays by image processing

Journal of Mechanical Science and Technology - Spray characteristics should be measured to understand fluid atomization. In this study, we investigated the atomization of kerosene fuel with...     

African mustard (Brassica tournefortii) as source of nutrients and nutraceuticals properties

Brassica tournefortii is an annual herbaceous plant, native to the North Africa and Middle East. It is considered as an excellent medicinal plant due to its richness by antioxidant like isothiocyanates and polyphenols. The present study is the first phytochemical investigation on Brassica tournefortii organs (leaves, stems, and roots) in terms of nutraceutical, chemical composition, and bioactivity. Brassica tournefortii leaves exhibited the highest values of nutraceutical contents. Interestingly, gas chromatograph-y-mass spectrometry (GC-MS) analysis enabled to identify three new isothiocyanates: iberverin nitrile and iberin detected only in roots, and iberin nitrile detected in all organs. HPLC chromatograms displayed different profiles depending on organic solvent and extracted organ. Icariin and 5,7-dihydroxy 4-propylcoumarin showed the highest concentrations with 2.3 and 1.3 mg/g of dr among other molecules identified by high performance liquid chromatography (HPLC). Some phenolic compounds were identified in more than one organ extracts such as phenoxodiol and 4-hydroxy-3-propylbenzoic acid methyl ester. Brassica tournefortii extracts showed a moderate total phenolic contents and anti-15-LOX activity, while they exhibited a good anti-α-glucosidase activity ranging from 40% to 60%. Furthermore, leaves-MeOH and root-dichloromethane (DCM) extracts induced the highest cytotoxicity against MCF-7 cell lines, while roots-cyclohexane (CYHA) extract highlighted the highest inhibition activity against, both, HCT-116 and OVCAR cell lines.     

Process simulation and optimization for enhanced biophotolytic hydrogen production from green algae using the sulfur deprivation method

This article explores the modeling, simulation and optimization of a biophotolytic cyclic process for enhanced hydrogen production from microalgae, employing the sulfur deprivation method. To achieve sulfur deprivation, each process cycle contained two temporally separated steps of sulfur-controlled algae growth and sulfur-deprived anaerobic hydrogen production.Reaction kinetics were modeled via an empirical logistic model. Reaction times, sulfate concentrations, and medium pH levels of each cycle were controlled to optimize the rate and yield of hydrogen production. Consequently, 65% and 23% improved values were obtained, respectively, with a smaller total process time (?11%), higher ratio of algae growth-to-hydrogen production time (29% vs. 21%), buffered pH (7.8), controlled sulfate injection and intermediary algae concentrations. Two- and 15-times higher hydrogen yields were obtained for 2- and 12-times lower initial algae concentrations. The proposed method is a significant tool for the design and optimization of a process for enhanced hydrogen production from microalgae.     

Microservice transition and its granularity problem: A systematic mapping study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying that transition. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modeling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.