Applications of Thermal Energy Storage in Saudi Arabia

In Saudi Arabia, the heating, ventilating and air conditioning (HVAC) system typically accounts for 65% of the total electrical energy consumption in buildings. This is due to a very high ambient temperature which persists for a long period of time in a summer season. Moreover, gas turbines efficiency decrease also with the high ambient temperatures. In the HVAC industry cool storage, or commonly known as Thermal Energy Storage (TES) is the most preferred demand side management (DSM) technology for shifting cooling electrical demand from peak daytime periods to off‐peak night‐time. The most popular and well‐suited TES concept for Saudi Arabia is either chilled water or ice storage system, depending upon the applications and the required storage capacity. This paper shows how TES offers a means of reducing the electrical demand in large commercial buildings. Additionally, it is seen that efficiencies of the air cooled chillers are increased if they run overnight. Similarly efficiencies of gas turbine is also increased when a TES based pre‐cooled air is used as an inlet to the turbine. This paper also discusses favouring conditions and other aspects of cool storage applications in Saudi Arabia. TES economics are considered and a cost analysis is presented to illustrate the potential savings that can be achieved by the use of TES in Saudi Arabia. Copyright © 1999 John Wiley & Sons, Ltd.     

Effect of Dimethylol Urea as a Flame Retardant Formulation on Some Cellulosic Fabric Materials

Samples of unscoured, scoured, bleached and mercerized cellulosic fabrics were treated with dimethylol urea (DMU). It was observed that this treatment imparted to the fabrics flame retardant (FR) characteristics. These observations were interpreted in terms of the fact that DMU reacts bifunctionally with glucopyronosyl hydroxyls in such a way that a three-dimensional (hence more stable) structure develops in addition to the possibility of release of acid residues within the flaming zone.     

Green Nanoarchitectonics of Cu/Fe3O4 Nanoparticles Using Helleborus niger Extract Towards an Efficient Nanocatalyst,Antioxidant and Anti-lung Cancer Agent

Biogenic nanoarchitectured magnetic materials have drawn serious attention throughout the last decade. We have attempted the Helleborus niger flower extract functionalized and templated biogenic synthesis of Cu nanoparticles supported Fe₃O₄ as a likewise novel material. The plant phytomolecules were deployed as a non-toxic sustainable reductant and an outstanding capping agent to stabilize the synthesized NPs. The synthesized Cu/H.niger@Fe₃O₄ nanocomposite was undergone comprehensive characterizations through Fourier transformed infrared spectroscopy (FT-IR), electron microscopy (SEM and TEM), energy dispersive X-ray spectroscopy (EDX), elemental mapping, vibrating sample magnetometer (VSM), X-ray diffraction (XRD) and inductively coupled plasma (ICP) techniques. The material was catalytically explored in the synthesis of diverse pyrano[3,2-c]chromene derivatives by coupling 4-hydroxycoumarin, malononitrile and a range of aldehydes in hot water when it afforded excellent yields. Based on its core magnetism, the catalyst was easily recovered using a magnet and reused for 8 successive times without considerable loss in catalytic activity. After the chemical application, the synthesized Cu/H.niger@Fe₃O₄ nanocomposite was engaged in biological assays like study of anti-oxidant properties by DPPH mediated free radical scavenging test using BHT as a reference molecule. Thereafter, on having a significant IC₅₀ value in radical scavenging assay, we extended the bio-application of the desired nanocomposite in anticancer study of A549 and H358 human lung cell lines in-vitro through MTT assay. The cell viability of malignant lung cell line reduced dose-dependently in the presence of desired nanocomposite. So, these results suggest that synthesized Cu/H.niger@Fe₃O₄ as a chemotherapeutic nanomaterial have a suitable anticancer activity against lung cell lines.

     

Intelligent Deep Convolutional Neural Network Based Object Detection Model for Visually Challenged People

Artificial Intelligence (AI) and Computer Vision (CV) advancements have led to many useful methodologies in recent years, particularly to help visually-challenged people. Object detection includes a variety of challenges, for example, handling multiple class images, images that get augmented when captured by a camera and so on. The test images include all these variants as well. These detection models alert them about their surroundings when they want to walk independently. This study compares four CNN-based pre-trained models: Residual Network (ResNet-50), Inception v3, Dense Convolutional Network (DenseNet-121), and SqueezeNet, predominantly used in image recognition applications. Based on the analysis performed on these test images, the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and speed. To further improve the performance of the Inception v3 model, the thermal exchange optimization (TEO) algorithm is applied to tune the hyperparameters (number of epochs, batch size, and learning rate) showing the novelty of the work. Better accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer, hyperparameter optimizer, and factorization approach. Additionally, Inception V3 can handle images of different sizes. This makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things (IoT)-based devices.     

An Extremely Stable,Highly Soluble Monosubstituted Anthraquinone for Aqueous Redox Flow Batteries

An extremely stable, energy-dense (53.6 Ah L⁻¹, 2 m transferrable electrons), low crossover (permeability of <1 × 10⁻¹³ cm² s⁻¹ using Nafion 212 (Nafion is a trademark polymer from DuPont)), and potentially inexpensive anthraquinone with 2-2-propionate ether anthraquinone structure (abbreviated 2-2PEAQ) is synthesized and extensively evaluated under practically relevant conditions for use in the negolyte of an aqueous redox flow battery. 2-2PEAQ shows a high stability with a fade rate of 0.03–0.05% per day at different applied current densities, cut-off voltage windows, and concentrations (0.1 and 1.0 m ) in both a full cell paired with a ferro/ferricyanide posolyte as well as a symmetric cell. 2-2PEAQ is further shown to have extreme long-term stability, losing only ≈0.01% per day when an electrochemical rejuvenation strategy is employed. From post-mortem analysis (nuclear magnetic resonance (NMR), liquid chromatography–mass spectrometry (LC-MS), and cyclic voltammetry (CV)) two degradation mechanisms are deduced: side chain loss and anthrone formation. 2-2PEAQ with the ether linkages attached on carbons non-adjacent to the central ring is found to have three times lower fade rate compared to its isomer with ether linkages on the carbon adjacent to the central quinone ring. The present study introduces a viable negolyte candidate for grid-scale aqueous organic redox flow batteries.     

The Laplacian Energy of Hesitancy Fuzzy Graphs in Decision-Making Problems

Decision-making (DM) is a process in which several persons concurrently engage, examine the problems, evaluate potential alternatives, and select an appropriate option to the problem. Technique for determining order preference by similarity to the ideal solution (TOPSIS) is an established DM process. The objective of this report happens to broaden the approach of TOPSIS to solve the DM issues designed with Hesitancy fuzzy data, in which evaluation evidence given by the experts on possible solutions is presents as Hesitancy fuzzy decision matrices, each of which is defined by Hesitancy fuzzy numbers. Findings: we represent analytical results, such as designing a satellite communication network and assessing reservoir operation methods, to demonstrate that our suggested thoughts may be used in DM. Aim: We studied a new testing method for the artificial communication system to give proof of the future construction of satellite earth stations. We aim to identify the best one from the different testing places. We are also finding the best operation schemes in the reservoir. In this article, we present the concepts of Laplacian energy (LE) in Hesitancy fuzzy graphs (HFGs), the weight function of LE of HFGs, and the TOPSIS method technique is used to produce the hesitancy fuzzy weighted-average (HFWA). Also, consider practical examples to illustrate the applicability of the finest design of satellite communication systems and also evaluation of reservoir schemes.