Anand Institute of Higher Technology
Recent publications
The study of concrete structure strengthening utilizing various ways has recently piqued the interest of researchers. The researchers concluded that strengthening structural concrete parts such as reinforced concrete (RC) columns with a concrete and Fiber-Reinforced Polymer (FRP) jacket can result in a significant increase in the maximum failure load. The aim of this analysis was to evaluate and test the effectiveness of using concrete and FRB as a reinforcing material to reinforce the entire height of downscaled historic RC columns. One identical Group (G1) unstrengthen reference column (C1) with cross sections of 200 × 200 mm and a height of 1500 mm was used in the experiments. In addition, seven monolithically cast columns with identical cross sections of 200 × 200 mm and a height of 1500 mm were fabricated. All the columns were composed of weak concrete. In this paper, the applied strengthened styles were Group (G2), which consisted of four columns cores reinforced by entirely concrete, CFRP, GFRP, and BFRP jackets, and Group3 (G3), which consisted of three columns reinforced by partial striped FRP as a strengthening material. The failure load, failure pattern, and longitudinal axial strain of all produced column specimens were studied in this work by testing them under monotonic uniaxial compression stress. The G1, G2, and G3 specimens provided a significant considerable improvement in ultimate load failure load after strengthening by nearly 1.8 times than the reference column, according to the testing data.
Deep learning is widely used for the classification of images that have various attributes. Image data are used to extract colour, texture, form, and local features. These features are combined in feature-level image fusion to create a merged remote sensing image. A trained depth belief network (DBN) processes and divides fusion images, while a Softmax classifier determines the land type. As tested, the proposed approach can categorise all types of land. Traditional methods of detecting distant sensing photographs have limitations that can be overcome by using convolutional neural networks (CNN). Traditional techniques are incapable of combining deep learning elements while doing badly in classification. After PCA decreases data dimensionality, deep learning is applied to generate effective features that employ deep learning after PCA has reduced the dimensionality of the data. Principal component analysis is commonly used because of its effectiveness in attaining linear dimension reduction. It may be used on its own or as a starting point for further study into various different dimensionality reduction approaches. Data can be altered by remapping onto a new set of orthogonal axes using a process known as projection-based principal component analysis. Following remote sensing of land resources, the pictures were classified using a support vector machine. Euroset satellite images are used to assess the suggested approach. Accuracy and kappa have both increased. It was accurate and within 95.83 % of the planned figures. The classification findings’ kappa value and reasoning time were 95.87 % and 128 milliseconds, respectively. Both the model’s performance and the classification effect are excellent.
Electricity is being used more directly and artificially than before. Working in a lab with a stronger synthetic emphasis enables the deployment of fresh ideas as well as ones that have been revived from earlier attempts in a wider range of situations. The amount of waste is decreased by using only electrons as reagents. Regenerating stoichiometric reagents in the correct molecular ratio can help electro catalytic catalysis. While minimizing waste is important, doing so also results in quicker and easier processes, gentler transitions, and the availability of more options, such as structural entities and IP space. Regenerative electricity can be used to give a terminal oxidizer or reducing agent that is extremely sustainable, which makes it a very alluring technology. Future electricity will be variable and plentiful, which will be very advantageous for value-added chemicals. The efficient conversion of renewable bio-based feedstocks serves as the first example of how contemporary electro-organic technologies can replace complex conventional processes. A new wave of sustainable chemistry will emerge if these obstacles are removed. This article takes a look at some recent developments in electrochemical synthesis that will undoubtedly affect how the discipline develops in the future.
The microwave-assisted combustion process (MCP) was adapted to prepared Zinc doped Co3O4 spinel nanoparticles. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), diffuse reflectance spectroscopy (DRS), energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD), and vibrating sample magnetometer (VSM) techniques were used to investigate the structural, optical, morphological, magnetic, and catalytic properties. The cubic spinel structure was obtained without impurities in the X-ray diffraction (XRD) patterns of undoped Co3O4 and Zn²⁺ doped Co3O4 (x = 0.1 and 0.3) respectively. However, as the Zn²⁺ concentration increased, at x = 0.5, a new hexagonal phase appeared in addition to the cubic phase, with mean crystallite size of the cubic spinel structure extending from 48.6 to 25.5 nm. It is found that Zn²⁺ doping in Co3O4 matrix can induce a negative shift in the flat-band potential (VFB) and increases the isoelectric point. The Co–O stretching mode of the cubic spinel Co3O4 structure is responsible for the occurrence of FT-IR bands at about 662 and 573 cm⁻¹. Kubelka–Munk (K–M) method is utilized to deduce the direct band gap and decline in the band gap values (1.87–1.72 eV) observed with rise in Zn²⁺ content. TG–DTA analysis confirms the weight loss and exothermic transitions. Scanning and transmission electron microscopy were used to study the morphology and the images depicted with intragranular pores, fused grains with different grain boundaries and homogeneous distributions. The transition from paramagnetic to super-paramagnetic behavior was most likely caused by the exchange of Zn and Co ions, as well as the phase composition of ZnO (hexagonal phase) and Co3O4 (cubic phase). The as-fabricated Zn²⁺ doped Co3O4 nanoparticles were evaluated for the catalytic activity tests carried out in a batch reactor operating under atmospheric conditions. The high doping concentration (about, x = 0.5) sample exhibited excellent catalytic activity and it exhibited better conversion efficiency and selectivity of 97.3% and 95.3%, respectively.
Lanthanum cuprate (La2CuO4) perovskite-type nanoparticles were synthesized by facile microwave-assisted combustion (2.45 GHz/900 W) for 15 min and calcinated at 500, 700, 900, and 1000 °C for 2 h. The effect of calcination temperature on the structural, optical, magnetic, and dielectric properties was investigated. The XRD studies confirmed that the perovskite nanoparticles with different temperatures from 500 to 900 °C possess a single-phase orthorhombic crystal structure of La2CuO4. In contrast, when the temperature increased to 1000 °C, the structure changed from orthorhombic to tetragonal. The average crystallite size of the orthorhombic phase is in the range of 37–47 nm. The presence of tensile strain in La2CuO4 was determined from Williamson–Hall (W–H) analysis. The appearance of FT-IR bands at approximately 634 and 970 cm−1 was correlated to the La–O and Cu–O stretching modes of the orthorhombic La2CuO4 phase. UV–Vis spectroscopy indicates that calcination temperature over the 500–1000 °C temperature range causes the band gap to decrease from 2.15 to 1.63 eV. The lanthanum cuprate system showed the formation of nanosized crystallized grains with pores and pore walls due to fused grains. The Magnetization–Field (M–H) hysteresis curves revealed the appearance of ferromagnetic behavior at room temperature. The dielectric properties of the fabricated La2CuO4 perovskite nanoparticles were evaluated at different temperatures and frequency-dependent dielectric constant, dielectric loss and AC conductivity, respectively.
Combining two types of fibers may aid in improving the fundamental properties of organic fiber-reinforced hybrid polymeric materials. Biomaterials created from raw materials are gaining appeal in the industrial sector due to their high quality, as well as sustainability and environmental considerations. Natural fiber-reinforced hybrid nanocomposites were created in this work using a compression moulding technique with wood particles, hemp fiber, polypropylene, and montmorillonite nanoclay. Following that, the impacts of fiber mixture and vermiculite on mechanical and compostable qualities were studied. Both the coir and the hemp fibers were alkali-treated to minimize their hydrophilic nature before even being employed. Using universal tensile testing equipment, the mechanical characteristics of the prepared composites were investigated and found to be improved following fiber blending and nanoparticle inclusion. The maximum strength was occurred at the combinations like 10 wt. % of wood particle, hemp, nanoclay, and 70% of polypropylene matrix. Scanning electron microscopy showed that nanoclay significantly increased the adherence and interoperability between fiber and the polymer matrices. The good biocompatibility and water absorption capabilities of the nanocomposite were increased by mixing fibers, but nanoparticle additions seemed to have the opposite impact.
In order to achieve sustainability goals, biomass is a renewable energy source that lowers emissions of greenhouse gases and other hazardous gases. Biochemical and thermochemical methods are both used to produce bioenergy from biomass. Pyrolysis is an effective thermochemical conversion technique used for the conversion of biomass into energy-rich bio-oil. In this study, the pyrolysis characteristics and bio-oil obtained from the residues of Ricinus communis were investigated. The experimental run was designed to analyze the impact of bed temperature on product yield by varying the process temperature from 350°C to 750°C. In this study, a maximum of 46.5 wt% of bio-oil was produced at 500°C. The maximum conversion was recorded at temperatures ranging from 450°C to 550°C. The bio-oil obtained at maximum yield conditions was analyzed using different analytical techniques. The Fourier transform infrared spectroscopy (FT-IR) and gas chromatography and mass spectroscopy (GC-MS) analyses of the bio-oil revealed that the oil has a significant amount of phenol derivatives, oxygenated chemicals, acids, and esters. The physical properties of the bio-oil showed that it is viscous and has a medium heating value compared with commercial fossil fuel.
A comparative investigation of the structural, optical, and magnetic properties of NiFe2O4 (NFO) and ZnFe2O4 (ZFO) spinel nanoparticles were synthesized by microwave combustion method. X-ray diffraction (XRD) showed that the ZFO spinel nanoparticles formed a cubic structure, but the NFO spinel nanoparticles formed with additional Fe2O3 in them. The average crystallite size was observed to be in the range 16–20 nm. X-ray photoelectron spectroscopy (XPS) peak areas are often used to quantify the elemental compositions and oxidizing states of NFO and ZFO spinel surfaces. The appearance of FT-IR bands at around 548, 514 and 649 cm⁻¹ were correlated to the Fe–O and Zn/Ni–O stretching modes of cubic NFO and ZFO structure. The direct band gap estimated using Kubelka–Munk (K–M) method to obtain by the NFO is 3.35 eV and ZFO is 2.13 eV respectively. The surface morphology revealed nanosized crystalline grains with agglomerate separated particles that are like spherical/non-spherical forms and fused grain boundaries. Magnetic measurements of NFO and ZFO spinel nanoparticles showed ferromagnetic behavior at room temperature.
In this paper, a built-up column of novel cold-formed cross-section that composed of four elements is investigated. The proposed built-up column is suitable for carrying axial, uni-axial, and bi-axial loading. The web of the new cross-section is composed of back-to-back track sections while the flanges of the cross-section are two lipped channels connected to the web using interconnectors. Elements comprising the cross-section are assembled and connected by enough interconnector bolts depending on the column built-up configurations. The interconnector spacing is varied among specimen cross-section and column length. In the present study, series of axially, uni-axially, and bi-axially compression columns were tested experimentally. Eleven specimens with various cross-section aspect ratios as well as different overall slenderness ratios were tested. Numerical finite element model that accounts for both material and geometrical nonlinearities was developed using ‘ABAQUS’ software to analyze the tested columns. A good agreement was achieved between the experimental test and the finite element model results. Experimental test results revealed that for axially loaded columns with small, medium, and high slenderness ratios, the failure modes were local buckling, local-flexural buckling, and flexural-distortional buckling; respectively. On the other hand, for uni-axially loaded columns having small, medium, and high slenderness ratios, the failure modes were local buckling, interaction between local and lateral-torsional buckling as well as lateral-torsional buckling; respectively. Furthermore, for bi-axially loaded columns, the failure mode was lateral-torsional buckling.
In the recent decade, the use of geogrid to improve the settlement behaviour of granular soil has become a major topic. So, applying geogrid for shallow foundation soil reinforcement is an important technique for improving the granular loose sand soil. In this study, the performance of a circular footing based on a reinforced granular soil bed was evaluated using comprehensive experimental work on thirteen (13) soil models. Comparison between reinforced and unreinforced condition under circular footing was carried. The depth of geogrid and the number of layers under circular footings was chosen as the various parameters in this study. The results revealed that, the soil's bearing capacity increase with 15.29%, 23.61%, 36.78%, and 42.14% using one, two, three, and four geogrid layers at (u/B) of 0.5, respectively. At (u/B = 0.8), sand's load-carrying capacity improves by 11.15%, 17.76%, 30.66%, and 38.55% for one, two, three, four layer of reinforcement using Geogrid, respectively. For one, two, three, four layer of reinforcement using Geogrid at (u/B = 1.0), the load carrying capacity of sand increases by 8.53%, 12.38%, 22.88% and 32.43%, respectively. In addition, to model and verify the experimental models, and to check the validity of the chosen computational processes, both a 2-D Finite Element Program GeoStudio 2018 and PLAXIS (2D) software were used. The results show that PLAXIS (2D) and GeoStudio 2018 can be used to simulate the settlement of loose sand soil under circular footing.
We report the synthesis of multiferroic BiFeO3 perovskite nanoparticles using the microwave combustion technique. Phase evolution is investigated by XRD, which confirms that the formation of a secondary α-Bi2O3 phase with a monoclinic structure along with the existing rhombohedral (BiFeO3) structure. The average crystalline size has been found at 50 nm. The optical band gap was calculated from the Tauc’s plot it has been found 2.18 eV. The appearances of FT-IR spectra revealed bands at 550 and 444 cm⁻¹ were correlated to the rhombohedral stretching modes of BiFeO3 nanostructure. The surface morphology showed the formation of nanosized grains with pores. The magnetization-Field (M-H) hysteresis curves revealed the appearance of ferrimagnetic behavior at room temperature. The BET surface area of BiFeO3 perovskite nanoparticles was found 44.86 m²/g. The as-fabricated BiFeO3 perovskite nanoparticles were investigated for their superior catalytic activity in two applications, which include (i) Glycerol to formic acid oxidation in the liquid phase with a high efficiency of over 98 percent, (ii) Under visible light, the photocatalytic breakdown of rhodamine B achieved maximal efficiency (almost 99 percent). Finally, we concluded that the BiFeO3 perovskite nanoparticles exhibit high performance in future multifunctional devices is demonstrated by the simultaneous enhancement of catalytic and photocatalytic activities.
The goal of this research is to increase the performance of AA 7150 reinforced with TiO2 microparticles by optimizing the stir casting parameters. The response surface method's central composite design technique was used to optimize the three stir casting factors of stirring temperature (A), stirring speed (B), and stirring time (C). The ultimate tensile strength, hardness, impact strength, elastic modulus, and compressive strength were all tested. With the aid of analysis of variance, it was discovered that it had a substantial influence on the test samples' characteristics responses. 5 quadratic experiments were linked using factors' characteristics. At a level of 95% confidence, the models were found to be statistically important, and the variations were found to be less than 5%. The response surface was used to assess the parameter interaction profile. Each interaction's contour plots provided a range of stirring settings within which each property may be maximized.
Density functional B3LYP method has been used to study the molecular properties of the tuftsin tetrapeptide (threonine-lysine-proline-arginine) and its retro form (arginine-proline-lysine-threonine). The influence of single water molecule on the conformations and relative stabilities of solvated tuftsin complexes has been studied by placing the water molecule at the individual amino acid residues of both the tuftsin complexes. The contribution of four water molecules to the system energetics of tuftsin complexes has also been analyzed. The conformational changes occurred in the solvated tuftsin complexes have been explored through their dihedral angles. The tuftsin is found to be sensitive to structural changes, and our results indicate that water-tuftsin hydrogen bonds (H-bonds), in addition to intramolecular H-bonds, stabilize the β-turn structure with H-bonds between threonine and arginine residues of tuftsin. Difference in the stability of the hydrated complexes is confined to the amino acid residues at which the water molecule is attached to tuftsin. The interaction energy calculations have been used to investigate the strength of the intermolecular H-bond interactions. The AIM theory and NBO analysis were employed to survey the H-bonding patterns in hydrated tuftsin complexes. The maximum ellipticity value (0.129) is noted for the Cα-H (Arg)…O (W) interaction in Tuftsin…4W complex which indicates the higher chance of structural deformation under external perturbations. The interactions between oxygen lone pairs in water and C-H antibond orbitals of tuftsin and retro tuftsin complexes exist with E 2 in the range of 4.03-5.7 and 3.59-4.14 kcal/mol, respectively.
Magnesium doped nickel ferrite spinel nanostructured were prepared using a microwave combustion method. The structural characterization by XRD analyses confirmed that undoped NiFe2O4 showed a single phase cubic spinel structure. However, with increasing Mg²⁺ concentration in the range 0.1 to 0.5 induced the crystallization of secondary α-Fe2O3 phase. The cubic nanostructured exhibited an average crystallite size between 20–35 nm. The presence of tensile/compressive strain in Mg²⁺ doped NiFe2O4 was determined from Williamson–Hall (W–H) method. The appearance of FT-IR bands at around 435, 459, and 581 cm⁻¹, characteristics of spinel cubic and rhombohedral stretching modes. The optical band gap as determined by diffuse reflectance spectroscopy (DRS) decreases with increasing Mg²⁺ content due to the quantum confinement effect. Surface morphology showed nanosized crystalline grains agglomerated with spherical shapes and energy dispersive X-ray analyses was used to examine the elemental composition of the Mg²⁺ doped NiFe2O4 spinel nanoparticles and confirmed the presence of nickel, magnesium, iron and oxygen elements. Magnetization–Field (M−H) hysteresis curves revealed the appearance of ferromagnetic behavior at room temperature. The as-fabricated Mg²⁺ doped NiFe2O4 spinel nanostructures were evaluated for the photocatalytic degradation of rhodamine B under visible light irradiation for atmospheric conditions. When a small amount of H2O2 was added during photocatalysis, indicating the samples possessed photo-Fenton like catalytic activity. This type of spinel nanoparticles behaves as an efficient catalyst with high efficiency around above 99%.
Glass Fibre Reinforced Polymer (GFRP) composites have found new applications in variety of fields. Better combinations of light weight, superior wear resistance and amazing mechanical properties have ascribed to their employments in divergent engineering segments. Dry sliding wear characteristic of GFRP composite with various weight rate of silicon carbide (SiC) filler have been examined with this display work. The impact of sliding velocity and load applied on dry sliding wear characteristics has been examined in this work. The results shows that specific wear rate of silicon carbide loaded GFRP composites increases with respect to increase in velocity of sliding and the load applied. This helps us to create composite materials with progressed tribological properties.
The education industry is completely locked down for their traditional setup since April 2020. The growth of the online learning and E learning had been hiked up nowadays as this supports students with no geographical borders. The ICT enabled tools are the most technology mediated techniques for the students and teachers of all segments from schools to Higher education institutions. As the world battles COVID-19 pandemic, everyone are continuously facing new challenges. The paradigm shift from traditional teaching classroom to online teaching has put a majority of the teachers in dismay due to the changes in the behavior of the students during the online classes. The movement from classroom instructing to online classes amid the Covid-19 pandemic has turn out to be a nightmare for teachers. The reason behind pushing many teachers into depression are Internet tormenting, scurrilous visits, provocation, and individual assaults on tutors by students have multiplied during online classes. The study aims to assess the impact of the teachers‟ performance and the behavioral change of the students attending the online classes and also to identify the various challenges faced by the teachers during online classes. The survey was carried out with responses from 234 teachers varying from schools to colleges in Chennai city of Tamilnadu. The questionnaire consisted of various dependant and independent variables supporting the understanding of the behavioral change among the students during online classes and the data collected was analyzed and tested statistically with tools like Pearson Correlation through the SPSS software. The major results of the studies were discussed and recommendations were given.
Recently, a mix of traditional and modern approaches have been proposed to detect brain abnormalities using bio‐signal/bio‐image‐assisted methods. In hospitals, most of the initial/scheduled assessments consider the bio‐signal‐based appraisal, due to its non‐invasive nature and low cost. Further, brain bio‐signal scans can be recorded using a single/multi‐channel electrode setup, which is further evaluated by an experienced doctor, as well as computer software, to identify the nature and severity of abnormality. In this paper, we describe the development of a system for computer supported detection (CSD) of schizophrenia using the electroencephalogram (EEG) signal collected with a 19‐channel electrode array. Schizophrenia is a mental illness that interferes with the way an individual thinks and behaves. It is characterised by psychotic symptoms such as hallucinations or delusions, negative symptoms such as decreased motivation or a lack of interest in daily activities and cognitive symptoms such challenges in processing information to make informed decisions or staying focused. This research has utilized 1142 EEGs (516 normal and 626 schizophrenia) with a frame length of 25 s (6250 samples) for investigation. The work initially converts the EEG signals to images using a spectrogram. Local configuration pattern features were extracted from the images thereafter, and 10‐fold validation technique was used wherein Student's t‐test and z‐score standardization were computed per fold. The highest accuracy of 97.20% was achieved with the K‐nearest neighbour (KNN) classifier. The results obtained confirm that the KNN classifier is helpful in the rapid detection of schizophrenia. This work is one of the first studies to extract local configuration pattern features from spectrogram images, yielding a high accuracy of 97.20%, with reduced computational complexity.
Natural fiber-reinforced composites are the most cost-effective and environmentally friendly alternative to industrial applications. Composite materials reinforced with Sansevieria cylindrica (SC) fibers were developed in this research work. These fibers were chosen for their outstanding mechanical qualities. Compression moulding was used to create composite materials. Each leaf on a Sansevieria cylindrica plant is 20 to 30 mm thick, with a height of 1000 to 2000 mm. The Sansevieria cylindrica (SC) fibers were used as chemically treated fibers and untreated fibers to produce the composites. The tensile strength, hardness, and impact strength of various fiber weight% of composites (20%, 30%, 40%, and 50%) were calculated. From the tested results, the maximum tensile strength achieved in 40 wt% of treated SC fiber composites is 85.7 MPa. The maximum hardness is found in 40 wt% of composites in both treated and untreated fiber composites. The 40 wt% of composites gives a better impact energy of 9.4 J/cm².The SC fiber polyester composites have superior interfacial bonding and give maximal strength in treated SC fiber composites. The fiber treatment delivers greater strength than the untreated fiber, according to this study. The treated SC fibers have better strength and good bonding between the fiber and matrix to produce the composite materials.
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90 members
Pathalamuthu Pitchaimuthu
  • Mechanical Engineering
Dr Sankara Malliga G
  • Department of Electronics and Communication Engineering
P. Rajalakshmi
  • communication system
Robert J Theivadas
  • Department of Electronics & Communication Engineering
Chennai, India