Solar-fuel fired cogeneration plants—Sizing and costing model for molten salt storage systems

The large-scale utilization of solar energy will be facilitated by economical and efficient energy storage. The proposed energy storage systems have been critically reviewed, and capital cost estimates compared on a common basis. A model for sizing an energy storage system is proposed and used to determine the size range of practical interest. Based on selection criteria and relevant data two storage systems have been investigated: an all sodium system and a molten salt system. The design equations, cost estimates, and correlations indicate that, for the energy storage systems developed to date, in the capacity range of 700–2100 MWh, a molten salt, two-tank isolated-type system is the most cost effective and technically feasible for a solar, central receiver, hybrid cogeneration plant. At the extremes of the above range the unit capital cost for the molten salt storage system was found to be 22.8–26.7 $/kWh of stored energy, compared to 43.0–45.4 $/kWh for the sodium storage system.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

Investigation of long term drift of an intraocular pressure sensor

Microsystem Technologies - “Zero drift” behavior of an optical intraocular pressure sensor is studied using an analytical model based on the deflection of a circular membrane. Results...     

An efficient neural-network model for real-time fault detection in industrial machine

Neural Computing and Applications - Induction machines have extensive demand in industries as they are used for large-scale production and, therefore, vulnerable to both electrical and mechanical...     

Numerical simulation of dispersed gas-liquid flows

This paper reviews the available information on numerical simulation of dispersed gas-liquid flows. Emphasis is on informing the reader about various aspects of constructing simulation models rather than giving an exhaustive literature review. The information is organised in a way so as to provide answers to the following questions: how to formulate model equations? how to select suitable algorithms and numerical techniques to solve these model equations? how to translate these into workable computer codes? how to use such codes for simulating flows in industrial equipment? Though greater emphasis is given to dispersed gas-liquid flows, the methodology can be applied to any multi-phase problem. Special features of multi-phase flow simulation over single-phase simulation are highlighted. A case of gas-liquid flow in a bubble column is presented as an illustration for the general methodology. The simulated mean flow field agrees reasonably with the experimental data. Properly validatedcfd codes thus can serve as a useful tool for design engineers of multi-phase systems. Some of the common pitfalls in using simulation codes for design are also discussed. This review is expected to give an overall idea about the present state-of-art of two-phase simulation in industrial equipment.     

The variable property grain model applied to the zinc oxide-hydrogen sulfide reaction

The variable property grain model, including the effect of grain diffusion resistance, has been applied to experimental results from the reaction of hydrogen sulfide with zinc oxide. Grain radius is assumed to vary under the combined effects of sintering and extent of reaction. Property variations are correlated by the specific surface area, an easily measured quantity. All model parameters with the exception of the grain diffusion coefficient have been evaluated by literature correlations or independent experimental measurements. Significant improvement in the match with experimental data, as compared to the constant property grain model, has been achieved.     

Highly Efficient Quasi 2D Blue Perovskite Electroluminescence Leveraging a Dual Ligand Composition

Perovskite light-emitting diodes (PeLEDs) are advancing because of their superior external quantum efficiencies (EQEs) and color purity. Still, additional work is needed for blue PeLEDs to achieve the same benchmarks as the other visible colors. This study demonstrates an extremely efficient blue PeLED with a 488 nm peak emission, a maximum luminance of 8600 cd m⁻², and a maximum EQE of 12.2% by incorporating the double-sided ethane-1,2-diammonium bromide (EDBr₂) ligand salt along with the long-chain ligand methylphenylammonium chloride (MeCl). The EDBr₂ successfully improves the interaction between 2D perovskite layers by reducing the weak van der Waals interaction and creating a Dion–Jacobson (DJ) structure. Whereas the pristine sample (without EDBr₂) is inhibited by small stacking number (n) 2D phases with nonradiative recombination regions that diminish the PeLED performance, adding EDBr₂ successfully enables better energy transfer from small n phases to larger n phases. As evidenced by photoluminescence (PL), scanning electron microscopy (SEM), and atomic force microscopy (AFM) characterization, EDBr₂ improves the morphology by reduction of pinholes and passivation of defects, subsequently improving the efficiencies and operational lifetimes of quasi-2D blue PeLEDs.     

A Formal Methodology for Detecting Managerial Vulnerabilities and Threats in an Enterprise Information System

From information security point of view, an enterprise is considered as a collection of assets and their interrelationships. These interrelationships may be built into the enterprise information infrastructure, as in the case of connection of hardware elements in network architecture, or in the installation of software or in the information assets. As a result, access to one element may enable access to another if they are connected. An enterprise may specify conditions on the access of certain assets in certain mode (read, write etc.) as policies. The interconnection of assets, along with specified policies, may lead to managerial vulnerabilities in the enterprise information system. These vulnerabilities, if exploited by threats, may cause disruption to the normal functioning of information systems. This paper presents a formal methodology for detection of managerial vulnerabilities of, and threats to, enterprise information systems in linear time.     

DeepKnuckle: revealing the human identity

Multimedia Tools and Applications - Identification and authentication are ubiquitous questions which pan across various systems. In certain domains, they are of paramount importance. Like, security...