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Experimental and finite element studies on the mechanical properties of high-strength concrete using natural zeolite and additives
Addressing high carbon footprints is a critical global problem in cement production. Using environmentally friendly materials has proven to be a solution to environmental challenges. In this study, High-Strength Concrete of M60 is produced with Natural Zeolite and industrial waste materials. The combinations of 5 % zeolite and varying percentages of industrial wastes such as Silica Fume, Metakaolin, and Fly Ash are tested for mechanical properties. The laboratory test data is compared with numerical simulations to assess the accuracy and determine the error percentage for concrete strength predictions. The process involves the development of numerical solutions by ANSYS to predict strength. The developed numerical solution determines the accuracy of identifying the difference between the experimental and numerical data. The present research on the comparison of experimental and numerical data by ANSYS showed the lowest error percentage, which is acceptable for all the strength properties of concrete. 2024 -
Efficacy of Natural Zeolite and Metakaolin as Partial Alternatives to Cement in Fresh and Hardened High Strength Concrete
Urbanization and industrialization have dramatically increased the manufacture of cement causing substantial pollution of the environment. The primary global concern related to cement manufacture has been the management of the large carbon footprints. The usages of environmentally friendly cementitious materials in the construction of structures have proved to be a viable option to deal with this environmental concern. Therefore, it is necessary to further explore the usage of cementitious materials which can replace cement albeit partially. In this direction of research, two such cementitious materials, namely, natural zeolite and metakaolin have been investigated in this study. High-strength concrete M60 with natural zeolite and metakaolin as the partial replacements for the cement has been prepared in this work. Polycarboxylic ether-based superplasticizer solution has been used to enhance workability. The test specimen cast and cured for 3, 7, 28, 60, and 90 days at ambient room temperature has been tested for compressive strength, split tensile strength, and flexural strength as per the Indian standards. The optimum mix of high-strength concrete thus manufactured has met the Indian standards, and the combination of cement +5% natural zeolite +10% metakaolin has exhibited the highest compressive, split tensile, and flexural strengths at 90 days of curing. Natural zeolite and metakaolin when used in smaller proportions have increased the concrete strength, and these materials are recommended for partial replacement of cement. 2021 Iswarya Gowram et al. -
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Performance Investigation of the High Strength Concrete Using Natural Zeolite with Industrial Waste Materials
Concrete is used in the construction of various structural elements. High Strength newlineConcrete (HSC) production for huge infrastructure projects is challenging. The newlinemanufacture of cement significantly causes global carbon dioxide (CO2) emissions. newlineModifications have been made to cement concrete problems to minimize CO2 emissions and Ordinary Portland Cement (OPC) consumption. This research focuses on developing HSC blended with Natural Zeolite (NZ) and industrial by-products like newlineSilica Fume (SF), Fly Ash (FA), and Metakaolin (MK) to enhance concrete quality, newlinesustainability, and performance. Partial replacement of OPC with 5% NZ and industrial waste materials in 5%, 10%, and 15% amounts to produce M60 grade HSC mixes. In the laboratory, 1,200 concrete specimens were tested for mechanical properties for 3, 7, 28, 60, and 90 days, as well as durability tests such as the Rapid Chloride Penetration Test (RCPT) for 28 days and the acid attack test for 60 days. Mix M3 (85% OPC + 5% NZ + 10% MK) exhibited the highest compressive strength at 72 MPa, split tensile strength at 5.3 MPa, and flexural strength at 9.4 MPa for 90 days curing period, attributed to its low porosity. The reactive silica (SiO2) and alumina (Al2O3) in the mix transformed calcium hydroxide (Ca(OH)2) into calcium silicate hydrate (C-S-H) gel and aluminate compounds. This process improved the newlinemicrostructure of the hardened concrete, resulting in increased imperviousness. The newlinestudy also includes the effect of these industrial waste materials on Zeolite concrete by microstructure analysis. The mathematical models were developed using SPSS software to predict the durability and mechanical properties of all the concrete mixes based on the laboratory data, considering parameters like mix proportions and curing days. -
Enhanced Security in Payment Gateways Through Face Detection: An Advanced Approach Using DenseNet 121- BiLSTM Models
Because it is one of the most promising applications of image analysis, face recognition has been the subject of intense research and development for many decades. Many modern identification and verification requirements have found a potential new home with the introduction of face recognition (FR) technology. Facial recognition is just one of numerous uses for biometric pattern recognition algorithms. Sequencing is essential for many tasks, including as feature extraction, model training, and preprocessing. Eliminating background noise and obtaining dense vertical edges are part of the preprocessing procedures. Facial feature extraction will be employed to extract features after feature extraction. Use attributes cautiously when training a Desnet121-BiLSTM model. In every respect, the suggested method outperforms two state-of-the-art algorithms, Desnet121 and BiLSTM. An accuracy rating of 97.19% was indicative of a considerable improvement in the figures. 2024 IEEE. -
An approach for document pre-processing and K Means algorithm implementation
The web mining is a cutting edge technology, which includes information gathering and classification of information over web. This paper puts forth the concepts of document pre-processing, which is achieved by extraction of keywords from the documents fetched from the web, processing it and generating a term-document matrix, TF-IDF and the different approaches of TF-IDF (term frequency Inverse document frequency) for each respective document. The last step is the clustering of these results through K Means algorithm, by comparing the performance of each approach used. The algorithm is realized on an X64 architecture and coded on Java and Matlab platform. The results are tabulated. 2014 IEEE. -
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Process development to synthesize plasma sprayable powders from nano alumina ceramic powders
Nano sized (?100 nm) alumina powders were converted into micron sized (30-75 mm) plasma sprayable powders by employing synthetic polymers to agglomerate them. The agglomeration process was carried out (a) in a spray dryer and (b) through systematic manual granulation procedure. The importance of process parameters that govern the plasma spray powder synthesis and thereby the characteristics were being suitable for being plasma spray coated have been brought out in this research paper. A comparative study has been made between the two synthesis methods by testing the powders synthesized under different processing conditions for their flowability characteristics. Micro-structural features related with the shape morphology and powder grain sizes were studied by Scanning Electron Microscope and the elemental composition characterization was carried out by Energy Dispersive Spectroscopy. The most suitable plasma sprayable powders were further coated onto metal substrates by using an Atmospheric Plasma Spray coating unit. The plasma sprayable powders were developed with a goal to explore their potential for their applications as wear resistant nano coatings. 2019 Elsevier Ltd. All rights reserved. -
Plasma sprayed nano refractory coatings
Nano powders may be reconstituted into micron sized plasma sprayable powders either by using a spray drier or a manual process by employing organic binders to agglomerate them. This paper deals with the synthesis of nano sized alumino-silicate plasma sprayable powders and plasma sprayed coatings prepared from them. Nano sized raw materials involving kyanite and andalusite refractory powders were converted into plasma sprayable powders by using polyvinyl alcohol (PVA) binders. The preparation methodology involved obtaining free flowing, micron sized agglomerated nano-alumino-silicates particles which could be plasma spray coated by using an Atmospheric Spray Coating Facility. About 220 microns thick nano-alumino silicate coatings were deposited on 75 microns thick commercial NiCrAlY bond coat on stainless steel substrates. The challenges involved in plasma spray coating the nano material with low density was in obtaining good deposition efficiency, retaining the nano micro structures and the structural phase composition of the coating. The coatings were evaluated for materials characteristics such as crystal structural phase via XRD, microstructure via SEM and chemical composition via EDS. The microstructure depicted fine grained nano-sized surface morphologies, kyanite and andalusite phase structure, with high potential for application as refractory coatings. Published under licence by IOP Publishing Ltd. -
Synthesis of Yttria-Stabilized Zirconia Nano Powders for Plasma Sprayed Nano Coatings
Plasma sprayed Yttria Stabilized Zirconia (YSZ) coatings, with few microns sized microstructure/grain morphology has been well researched, reported and established as an industrial Thermal Barrier Coatings (TBC) material/system. However, nano structured YSZ coatings possess improved characteristics when compared with their micron sized counterparts. However, due to their nano sizes, light weight, and low density, plasma spray coating process of nano powders suffers from flowability issues due to lack of nano powder inertia/momentum, leading to poor deposition/uneven coating thickness. In this research work, nano structured YSZ coatings were synthesized by using an Atmospheric Spray Coating (APS) facility. Nano powders of YSZ were used as the starting materials to prepare micron sized plasma sprayable powders. 80?m thick NiCrAlY bond coat (commercial) and 200?m thick YSZ top coat with nano microstructure (lab synthesized) were built on steel substrates. The starting nano crystalline (YSZ) powders, measuring 30-70 nanometers (nm) were synthesized in the laboratory via chemical method (sol-gel) by employing zirconium oxy chloride hexa-hydrate and yttrium nitrate as precursors, citric acid as chelating agent and ethylene glycol for the diversification reaction followed by calcination @ 1000C. They were then re-constituted into micron sized (53-106 ?m) plasma sprayable powders by agglomerating with polyvinyl alcohol (PVA) binders. The nano crystallite morphology of powders and coatings were analyzed by Scanning Electron Microscope (SEM), chemical composition by Energy Dispersive spectroscopy (EDS) and crystal structural phase by X-ray diffraction (XRD). The influence of calcination temperature of 1150C on nano crystallite morphology was also studied. 2019 Elsevier Ltd. -
Experimental Approach and CFD Analysis on Flow Devices
This paper deals with the study of experimental approach and investigation by using computational fluid dynamics (CFD) on various flow devices. An orifice meter, venturimeter and a nozzle meter are the most common type of measuring devices used for rate of flow by creating the differences in velocity and pressure. Pressure drop is an important parameter occurring in these flow devices, which is due to restricted passage of flow, properties, diameter ratio, etc. The focus here is to calculate the coefficient of discharge and other flow parameters to analyze theoretically with the application of Bernoullis equation. The main objective of this paper is to analyze the variations across the sections of orifice meter, venturimeter and nozzle meter. Comparison of results by both experimental and computational methods was clearly understood, and also, the flow level was calibrated by calculating the coefficient of discharge in both the methods. 2021, Springer Nature Singapore Pte Ltd. -
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Machine
Imbalanced data are a common classification problem. Since it occurs in most real fields, this trend is increasingly important. It is of particular concern for highly imbalanced datasets (when the class ratio is high). Different techniques have been developed to deal with supervised learning sets. SMOTE is a well-known method for over-sampling that discusses imbalances at the level of the data. In the area, unequal data are widely distributed, and ensemble learning algorithms are a more efficient classifier in classifying imbalances. SMOTE synthetically contrasts two closely connected vectors. The learning algorithm itself, however, is not designed for imbalanced results. The simple ensemble idea, as well as the SMOTE algorithm, works with imbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Hybrid AODV: An Efficient Routing Protocol for Manet Using MFR and Firefly Optimization Technique
A MANET is a category of ad hoc protocol that could vary positions and track itself on the flutter. It utilizes wireless connections that are attached to several networks. They include wirelessly in a self-configured, self-healing network while not having permanent communication linked in a collection of mobile networks. The network topology of nodes typically varies in MANET, and nodes are free to stir errantly and independently as a router as they accelerate traffic to more nodes within the network. Ad hoc on-demand distance vector (AODV) was employed for node selection to attain the shortest path strategy in existing techniques. In the proposed system, the hybrid AODV (HAODV) technique incorporates the MFR (Most Forward within Radius) technique to detect the shortest path routing algorithm. The MFR method was deployed for selecting the neighbor node, while HAODV was deployed to find the shortest path. To find the shortest path based on the updating equation, the Firefly algorithm is also implemented into the Hybrid AODV. The proposed work's performance is calculated by different network parameters like the end to end delay, average routing overhead, throughput, and packet delivery ratio. After comparing AODV and DSR algorithms, the proposed algorithm (HAODV) shows improvement in packet delivery ratio, end-To-end delay, Routing overhead, and throughput. 2021 World Scientific Publishing Company. -
Reliability, maintainability and sensitivity analysis of physical processing unit of sewage treatment plant
India is facing radical change in perspective of inadequate water resources which can reduce by using treated water. In this direction, sewage treatment plants play a key role. Sewage treatment plant comprises three units namely physical processing, chemical processing and biological process. The physical process is the most important part and it has five component arranged in series configuration. It becomes necessary to perform this process with high efficiency and reliability, availability, maintainability, and dependability (RAMD) is the methodology to analyze the performance. The failure and repair rates of the subsystems has been considered exponentially distributed. ChapmanKolmogorov differential equations are derived using Markovian birthdeath process and several measures like mean time between failures, mean time to repair and dependability ratio are derived. The sensitivity analysis of reliability of the plant has also been performed. RAMD investigation shows that: availability of system is 0.952177, reliability of the system after 20days is 0.2018 and after 60days 0.00823, maintainability of the plant is 0.999948, dependability ratio is 0.9541 and raw sewage sump is the most sensitive subsystem of the plant with reliability 0.382893. This work is projected to support as an informative exertion in steering a RAMD analysis of physical processing unit and vary few work is available in literature related to the performance features of physical processing units of the sewage treatment plants. The main findings may be very useful for sewage treatment plants designers. 2019, Springer Nature Switzerland AG. -
Identification and structure-activity relationship studies of small molecule inhibitors of the human cathepsin D
Cathepsin D, an aspartyl protease, is an attractive therapeutic target for various diseases, primarily cancer and osteoarthritis. However, despite several small molecule cathepsin D inhibitors being developed, that are highly potent, most of them show poor microsomal stability, which in turn limits their clinical translation. Herein, we describe the design, optimization and evaluation of a series of novel non-peptidic acylguanidine based small molecule inhibitors of cathepsin D. Optimization of our hit compound 1a (IC50 = 29 nM) led to the highly potent mono sulphonamide analogue 4b (IC50 = 4 nM), however with poor microsomal stability (HLM: 177 and MLM: 177 ?l/min/mg). To further improve the microsomal stability while retaining the potency, we carried out an extensive structureactivity relationship screen which led to the identification of our optimised lead 24e (IC50 = 45 nM), with an improved microsomal stability (HLM: 59.1 and MLM: 86.8 ?l/min/mg). Our efforts reveal that 24e could be a good starting point or potential candidate for further preclinical studies against diseases where Cathepsin D plays an important role. 2020 Elsevier Ltd -
Approach Towards Web for Exploring the Suitable Job for Individuals
In light of future work challenges, true human resource management (HRM) must be rebuilt. This involves over time human resource development; it must also contain the concept of sustainability to move from consuming to generating human resources. The labor market is constantly changing, with nontraditional jobs becoming increasingly important, especially in light of the current COVID-19 legislation. A useful teaching strategy in a variety of academic fields, including career development, is experiential learning. Important elements for establishing experiential learning programs at the institutional level are also covered by researchers. Our framework may assist businesses in identifying the type of experiential learning that best fits their objectives and setting for professional training. It can also help ensure that the training is successfully designed and delivered. 2024 IEEE. -
Importance Of Artificial Intelligence in Improving Human Resource Management For Companies To Find Suitable Candidature
The efficient use of pertinent human resources both inside and outside the company via management structures guided by economic and humanistic principles is known as human resource management. It is a catch-all word for a set of actions that guarantee the accomplishment of group objectives and the optimization of member growth. Employers need the correct recruitment tools to fill available positions since traditional recruiting approaches are not up to par in the global talent battle. First, as the digital tool redesigns business, we look at how talent acquisition has evolved from digital 1.0 to 3.0 (AI-enabled). Artificial intelligence technology has made recruiting more efficient and made recruiters' daily tasks easier. Additionally, the analysis in the paper shows that artificial intelligence (AI) is crucial to every step of the hiring process, including promotion, application, screening, evaluation, and coordination. This study demonstrates how organizations are realizing the value of talent management in gaining a competitive edge as the need for higher-level talent grows. Even though some HR managers are using AI for talent acquisition, our research shows that there is still an opportunity for development. 2024 IEEE. -
Unique helical conformation of the fourth cytoplasmic loop of the CB1 cannabinoid receptor in a negatively charged environment
The proximal portion of the C-terminus of the CB1 cannabinoid receptor is a primary determinant for G-protein activation. A 17 residue proximal C-terminal peptide (rodent CB1 401-417), the intracellular loop 4 (IL4) peptide, mimicked the receptor's G-protein activation domain. Because of the importance of the cationic amino acids to G-protein activation, the three-dimensional structure of the IL4 peptide in a negatively charged sodium dodecyl sulfate (SDS) micellar environment has been studied by two-dimensional proton nuclear magnetic resonance (2D 1H NMR) spectroscopy and distance geometry calculations. Unambiguous proton NMR assignments were carried out with the aid of correlation spectroscopy (DQF-COSY and TOCSY) and nuclear Overhauser effect spectroscopy (NOESY and ROESY) experiments. The distance constraints were used in torsion angle dynamics algorithm for NMR applications (DYANA) to generate a family of structures which were refined using restrained energy minimization and dynamics. In water, the IL4 peptide prefers an extended conformation, whereas in SDS micelles, 310-helical conformation is induced. The predominance of 310-helical domain structure in SDS represents a unique difference compared with structure in alternative environments, which can significantly impact global electrostatic surface potential on the cytoplasmic surface of the CB1 receptor and might influence the signal to the G-proteins. 2007 Elsevier Inc. All rights reserved. -
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Solution structure of the tachykinin peptide eledoisin
Both the aqueous and the lipid-induced structure of eledoisin, an undecapeptide of mollusk origin, have been studied by two-dimensional proton nuclear magnetic resonance spectroscopy and distance geometry calculations. Unambiguous nuclear magnetic resonance assignments of protons have been made with the aid of correlation spectroscopy experiments and nuclear Overhauser effect spectroscopy experiments. The distance constraints obtained from the nuclear magnetic resonance data have been utilized in a distance geometry algorithm to generate a family of structures, which have been refined using restrained energy minimization and dynamics. These data show that, while in water and dimethyl sulfoxide, eledoisin prefers to be in an extended chain conformation, whereas in the presence of perdeuterated dodecylphosphocholine micelles, a membrane model system, helical conformation is induced in the central core and C-terminal region (K4-M11) of the peptide. N terminus, though less defined, also displays some degree of order and a possible turn structure. The conformation adopted by eledoisin in the presence of dodecylphosphocholine micelles is similar to the structural motif typical of neurokinin-2 selective agonists and with that reported for kassinin in hydrophobic environment.