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Theoretical and Experimental Analysis of Large Deformation Induced Damaged Composite Structure using Elastic Elastoplastic Properties under High Strain Loading Conditions
No full textThis study examines the geometrically linear/nonlinear analysis of laminated curved shell panels that have damage under mechanical loading. The numerical responses are evaluated computationally via a higher-order finite element (FE) formulation to estimate the responses, i.e., static bending, free vibration, and transient deflection under elastic/elastoplastic conditions at normal and high strain rates. The layered curved shell model is derived mathematically using an equivalent single-layer theory based on the third-order displacement variables. Moreover, the Green Lagrange nonlinear strain terms have been used mathematically to introduce the geometrical nonlinearity within the structure. The nonlinear governing equation of motion utilizes Hamilton's principle for the layered structure having damages. The approximate nonlinear numerical solutions are computed using the isoparametric FE technique utilizing Gauss-Quadrature integration in association with Picard's direct iterative method. The discretization of the curved shell panel is accomplished using the quadrilateral Lagrangian element with nine-node considering ten degrees of freedom per node. A generic computational approach has been adopted in MATLAB using the existing nonlinear mathematical formulation considering all nonlinear higher-order terms to retain the required generalization. Initially, the consistency of the developed numerical model is checked with an adequate number of convergence tests. Similarly, the derived model accuracy is verified further using a comparison test with the available published results (numerical and analytical). The numerical findings are equated with the experimental results for the second stage verification using the available lab-scale test rig. The observed difference between the experimental and numerical values is within an acceptable range of 10%. For a comprehensive understanding of the damaged structural modelling, the impact of damages, including the different geometrical factors, loading conditions, and edge-support conditions, is examined further
Simulating the Scenarios of Surface Water Quality Indicators for Lower Mahanadi River System using Artificial Intelligence
No full textWater quality describes the suitability of water in terms of its physical, chemical, and biological characteristics. To identify these characteristics adequately, one needs to comprehend the variation of the significant parameters affecting the water quality of a particular region. The study area for this work is the lower Mahanadi River basin, comprising of 13 stations located along the river course from which data from 20 different physicochemical parameters are collected for 2001 to 2023. The parameters include temperature, pH, turbidity, dissolved oxygen (DO), biochemical oxygen demand (BOD), total coliform (TC), faecal coliform (FC), conductivity, chloride, total hardness, calcium hardness, magnesium hardness, alkalinity, sulphate, sodium, chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), nitrate-N, and nitrite-N. Multivariate statistical methods are used to determine the seasonal variation of the water quality and to reduce the number of parameters. In particular, principal component analysis (PCA) provided desirable results that have a major impact on the water quality. In the non-monsoon season, the parameters are reduced to 45%. Deep learning and machine learning have gained significant attention for analysing time-series data. However, these methods often suffer from high complexity and significant forecasting errors, primarily due to non-linear datasets and hyperparameter settings. An innovative HDTO-DeepAR approach for predicting water quality indicators has been developed to address these challenges. HDTO-DeepAR outperformed the other methods. The forecasted frequency is expected to fall within a prediction interval of 95% and 98%. Improving surface water monitoring capabilities may result in accurate predictions, which can help policymakers develop a strategy to reduce water pollution. Traditional monitoring techniques are time-consuming and costly, making it difficult to meet the demands of real-time visualisation in current situations. To deal with this challenge, a novel approach (GHPSO-ATLSTM) has been developed to predict water quality indicators in surface water. The optimal features are selected using a genetic algorithm (GA), and the hyperparameters of LSTM are optimized with the hidden particle swarm optimisation (HPSO) technique followed by an attention (AT) layer to enhance the prediction accuracy. The R2 value lies between 0.89 and 0.95 using the proposed method. The novelty of the work lies in determining a specific set of most significant variables using PCA, forecasting the significant variables based on a probabilistic approach using HDTO-DeepAR, and predicting water quality parameters based on point prediction using GHPSO-ATLSTM. The major conclusions drawn from the case study are that DO might fluctuate between 6 mg/l and 10 mg/l in the coming years. All the parameters are found to be lying within the permissible limit. Government intervention and increased public knowledge of environmental degradation’s effects on health risks may be responsible for reducing the amount of water pollution in the Mahanadi River system
Hydrodynamic Studies of the Non-Spherical Particles Settling in Annular and Non-Annular Channels Filled with Newtonian and non-Newtonian Fluids
No full textThe wall factor (f) and drag coefficient (CD) of hollow cylinders, hollow frustum, clusters, solid and hollow disks, and solid cylinder, frustum, hemi-cylinder, and hemi- frustum settling in cylindrical annular and non-annular channels were investigated. Fluid flows through the space between two concentric cylinders in the annular channel. The particles' terminal velocity decreased linearly with the blockage ratio. Terminal velocity was higher for non-annular channels filled with Newtonian fluid, and a reverse trend was observed for non-Newtonian fluids. The wall factor varied with the Reynolds number (Re), blockage ratio (deq/D for non-annular and deq/L, where deq is the equivalent diameter and L = (Do - Di)/2 for the annular channel), and di/do (hollow particle’s inner to outer diameter ratios). It increased initially to reach a constant value at a higher Reynolds number. The wall factor was higher for the non-annular channel. The drag coefficient declined with Re and increased with the blockage ratio. The correlations for the experimental drag coefficient were developed. Moreover, the current drag coefficient data were successfully predicted by the laminar flow model available in Ansys (Fluent 18.1). In the case of the hollow cylindrical particles, f and CD were estimated for 0.2 ≤ di/do ≤ 0.8, 0.08 ≤ deq/D ≤ 0.47, and 0.14 ≤ deq/L ≤ 0.46. The estimated drag coefficient using the Newtonian fluids was 0.782 ≤ CD ≤ 3249.75 and 39.62 ≥ CD ≥ 0.8 for 0.064 ≤ Re ≤ 101.34 and 1.22 ≤ Re ≤ 100.21 for non-annular and annular channels, respectively in Newtonian fluids. The same was estimated in the range of 0.73721 ≤ CD ≤ 125507 and 3104 ≥ CD ≥ 1.27 for 0.0017 ≤ Re ≤ 64.07 and 0.054 ≤ Re ≤ 47.67 for the settling the particle in the non-annular and annular channel in the non-Newtonian fluid. For hollow frustum particles, the experimental f and CD are limited to 0.22 ≤ di/do ≤ 0.77, 0.22 ≤ deq/L ≤ 0.43, and 0.12 ≤ deq/D ≤ 0.44. CD, varied in the range of 0.80 ≤ CD ≤ 15.49 and 0.82 ≤ CD ≤ 7.12 for 2.798 ≤ Re ≤ 90 and 5.29 ≤ Re ≤ 89.97 while settling in Newtonian fluids in the non- nnular and annular channel, respectively. The same was varied over 0.983 ≤ CD ≤ 1292.47 and 1.48 ≤ CD ≤ 191.55 for 0.168 ≤ Re ≤ 50 and 0.1506 ≤ Re ≤ 20 for the non-annular and annular channels, respectively using non-Newtonian fluid as the process fluid. For the cluster particles, f and CD were estimated for 2 ≤ N (number of particles used) ≤ 7, 0.04 ≤ deq/D ≤ 0.24, and 0.10 ≤ deq/L ≤ 0.23. The estimated drag coefficient, CD, was varied in the range of 1.66 ≤ CD ≤ 43.30 and 1.92 ≤ CD ≤ 36.67 for 0.76 ≤ Re ≤ 22.09 and 0.74 ≤ Re ≤ 20.51 while settling in the non-annular and annular channels, respectively filled with Newtonian fluids. The same was varied for non-Newtonian fluids over 2.84 ≤ CD ≤ 4002 and 2.21 ≤ CD ≤ 1638 for 0.028 ≤ Re ≤ 10.14 and 0.052 ≤ Re ≤ 11.6 for the settling of the particles in the non-annular and annular channel, respectively. In the case of the disk/cylinder particles settling in non-annular and annular channels, f and CD were estimated for 0.12 ≤ H/d ≤ 1.09, 0.10 ≤ deq/D ≤ 0.57, and 0.17 ≤ deq/L ≤ 0.55. The wall factor increased with the sphericity. The estimated drag coefficient, CD, appeared in the range of 1.56 ≤ CD ≤ 503.88 and 0.851 ≤ CD ≤ 133.65 for 0.20 ≤ Re ≤ 46.75 and 0.40 ≤ Re ≤ 63.44 for the settling of the disk/cylinder in the non-annular and annular channel, respectively in Newtonian fluids. The same was varied in the range of 1.35 ≤ CD ≤ 31934 and 0.69 ≤ CD ≤ 1203.91 for 0.005 ≤ Re ≤ 30 and 0.05 ≤ Re ≤ 43.02 for the settling the particle in the non-annular and annular channel, respectively in the non- Newtonian fluid. For hollow disk particles, the f and CD were estimated for 0.12 ≤ H/do ≤ 0.27, 0.16 ≤ di/do ≤ 0.58, 0.06 ≤ deq/D ≤ 0.35, and 0.15 ≤ deq/L ≤ 0.34. f increased with H/do (Height/Outer diameter) ratio. The experimental CD varied over 3.061 ≤ CD ≤ 106.29 and 3.11 ≤ CD ≤ 34.41 for 0.463 ≤ Re ≤ 16.30 and 0.81 ≤ Re ≤ 16.16 while settling in the non- annular and annular channels, respectively in Newtonian fluids. The same varied in the range of 6.81 ≤ CD ≤ 57293 and 6.93 ≤ CD ≤ 12952 for 0.0042 ≤ Re ≤ 6.23 and 0.011 ≤ Re ≤ 6.17 while settling in the non-annular and annular channel, respectively in the non- Newtonian fluids. The estimated CD varied over 1.96 ≤ CD ≤ 390.05 and 1.12 ≤ CD ≤ 25.53 for the settling of the cylindrical particles in the Newtonian fluids in non-annular and annular channels for 0.33 ≤ Re ≤ 31.71 and 1.31 ≤ Re ≤ 41.91, respectively and 1.87 ≤ CD ≤ 25961.28 and 1.84 ≤ CD ≤ 1719.75 for 0.0086 ≤ Re ≤ 19.15 and 0.05 ≤ Re ≤ 19.32, respectively while settling in non- Newtonian fluids. For frustum particles the estimated drag coefficient was 1.83 ≤ CD ≤ 350.65 and 1.07 ≤ CD ≤ 24.83 for 0.35 ≤ Re ≤ 32.73 and 1.33 ≤ Re ≤ 42.92 in Newtonian fluids and 1.78 ≤ CD ≤ 24143.72 and 1.75 ≤ CD ≤ 1433.97 for 0.0091 ≤ Re ≤ 19.70 and 0.06 ≤ Re ≤ 19.87 in non-Newtonian fluids in the non-annular and annular channels, respectively. For hemi-cylinder particles, the range of the drag coefficients was 1.65 ≤ CD ≤ 397.24 and 0.93 ≤ CD ≤ 22.52 for 0.37 ≤ Re ≤ 32.80 and 1.35 ≤ Re ≤ 43.65 in Newtonian fluids and 1.56 ≤ CD ≤ 20539.46 and 1.59 ≤ CD ≤ 1097.72 for 0.0096 ≤ Re ≤ 19.95 and 0.07 ≤ Re ≤ 19.78 in non- Newtonian fluids in the non-annular and annular channels, respectively. For hemi-frustum particles, the range was 1.55 ≤ CD ≤ 269.91 and 0.89 ≤ CD ≤ 17.45 for 0.39 ≤ Re ≤ 33.82 and 1.53 ≤ Re ≤ 44.68 in Newtonian fluids and 1.48 ≤ CD ≤ 19209.97 and 1.51 ≤ CD ≤ 943.45 for 0.0101≤ Re ≤ 20.50 and 0.08 ≤ Re ≤ 20.33 while settling in non- Newtonian fluids in the non-annular and annular channels, respectively. The cluster particles experienced a higher wall effect for the Newtonian fluids. The hollow particles showed a higher drag coefficient
Functionalized g-C3N4 Quantum Dots Based Fluorescent Sensors for Detection of Toxic Metal Ions
No full textExposure to toxic metal ions, such as mercury, lead, and cadmium, poses severe threats to human health. These metals have been widely investigated, and their impacts on human health are periodically assessed. The advancement of fluorescent sensors with exquisite sensitivity and selectivity for detection of toxic metal ions has attracted a great deal of recent research. Quantum dots, devoid of heavy metals and possessing excellent photoluminescence properties, are highly anticipated in the field of fluorescence sensing. This has led to the advent of quantum dots-based sensing platforms due to their distinct optical and electronic properties. Being metal-free, the graphitic carbon nitride quantum dots (g-C3N4 QDs) have attracted enormous interest in sensing applications due to their significant quantum confinement and edge effects, blue emission, high quantum yield, resistance against photobleaching and high ionic strength. The main focus of this doctoral research work is to design functionalized g-C3N4 QDs for sensing toxic metal ions in the aqueous phase. The aim was to functionalize g-C3N4 QDs either by doping with heteroatoms or by surface functionalization with organic ligands to target a specific metal ion. Here, various functionalized g-C3N4 QDs were successfully synthesized and were used as fluorescent sensors. Silver nanoparticles embedded sulfur-doped gCN quantum dots (Ag-S-gCN QDs), L-Glutathione (GSH) modified graphitic carbon nitride quantum dots (GSH@g-C3N4 QDs), L-Cysteine (L-Cys) functionalized boron doped gC3N4 QDs (L- Cys/B-gC3N4 QDs) were prepared for detection of Hg2+, Pb2+, and Cd2+ ions, respectively. The comprehensive characterization of the synthesized materials was carried out to understand their structural, morphological, and optical properties. The fluorescence sensing application of the synthesized materials was evaluated for detection of toxic metal ions. The detailed mechanistic study was conducted to understand the interaction between the probe and analyte. Eventually, the sensor system was employed in real water samples to detect the aforementioned toxic metal ions. First, silver nanoparticles embedded sulfur-doped gCN quantum dots (Ag-S-gCN QDs) were synthesized for detection of Hg2+. The as-prepared quantum dots emitted strong blue fluorescence with a relative quantum yield of 36.5%. They exhibited significant stability against photobleaching and high ionic strength. The Ag-S-gCN QDs, under optimal conditions, were employed for fast sensing of Hg2+ ions. The limit of detection (LOD) and limit of quantification (LOQ) were measured to be 0.13 μM and 0.43 μM, respectively, with a linear range of 0.1–0.6 μM. A static quenching mechanism was proposed from the average lifetime calculation accompanied by a redox reaction via electron transfer from metallic Ag to Hg2+ ions. A substantial amount (> 85%) of Hg2+ ions in the real water samples were recovered within a relative standard deviation (RSD) of ≤ 5%. Further, surface functionalization of g-C3N4 QDs was achieved by preparing L-Glutathione modified graphitic carbon nitride quantum dots (GSH@g-C3N4 QDs) for detection of Pb2+. With a relative quantum yield of 27%, the system demonstrated exceptional stability against ionic strength and photobleaching. Additionally, it was discovered that the fluorescence emission of the sensor was selectively quenched in the presence of Pb2+ ions. The limit of detection (LOD) for Pb2+ was measured to be 0.025 μM in a linear range of 0.01 μM-0.1 μM. The average lifetime calculations from the lifetime decay experiment along with UV–vis. absorption studies suggested that the quenching pattern follows a static quenching mechanism. Finally, the system was used in real water samples to detect Pb2+ with a recovery percentage greater than 90%. The functionalization of gC3N4 QDs was further extended by passivating L-Cysteine on Boron doped gC3N4 QDs (L-Cys/B-gC3N4 QDs). The blue-emitting modified quantum dots demonstrated a high quantum yield of 28% with exceptional water solubility, resistance to photobleaching, and ionic strength. Further, they were used as a fluorescent probe for monitoring Cd2+ ions at trace levels in water. They exhibited a responsive behaviour to Cd2+ ions with enhancement in the fluorescence signal. Based on time correlated single-photon counting studies (TCSPC) and UV-vis. absorption studies, the fluorescence enhancement was ascribed to the chelation-enhanced fluorescence (CHEF) mechanism. The fluorescence emission intensity of L-Cys/B-gC3N4 QDs displayed a good linear correlation within Cd2+ concentration from 0.1 to 0.7 μM, with a limit of detection (LOD) of 0.23 μM. The proposed method was effectively employed to monitor Cd2+ in tap and pond water samples, achieving exceptional recovery rates between 95-106%, with a relative standard deviation (RSD) of 2.6-3.4%
Experimental Study of Thermal and Frictional Characteristics of Solar Air Heater using Impinging Jets with Modified Absorber and Jet Plates
No full textThe depletion of fossil fuel and their impact on the environment due to continual usage for our ever-increasing power needs has forced us to look pro-actively towards other renewable forms of clean energy like wind, solar, ocean energy, etc. Amongst all renewable sources of energy, solar energy is abundantly available throughout the world and can meet the energy needs of our planet if appropriately harnessed. Solar thermal collectors are used to collect solar thermal energy, and then it is transferred to the fluid. The fluid may be air, water, oil, etc., depending on the application. Many researchers are working towards the performance enhancement of solar thermal collectors. This study concentrates on solar air heater with impinging jets incorporated with modifications to the absorber and jet plate to improve efficiency. Five objectives were chosen and completed. For the first objective, an experimental setup of an impinging jet solar air heater (IJSAH) was developed to study its thermal and frictional characteristics. Six cases were analysed with the jet holes spanning different lengths across the jet plate. For cases 1 and 2, jet holes spanned 100% and 80% of the length of the jet plate while having jet diameter equal to 3 mm. For cases 3, 4, and 5, jet holes were drilled up to 100%, 80%, and 60% of the whole length, and the diameter was increased to 6 mm. For case 6, jet holes were drilled up to 100% while keeping the jet diameter equal to 9 mm. For each case, variation in Nusselt number, friction factor and temperature rise of the fluid was evaluated for Reynolds number in the range 4913 to 13103. The efficiency and thermo-hydraulic performance factor with each case were compared. It was concluded that IJSAH with reduced length of drilled section (case 5) developed similar performance to IJSAH having completely perforated jet plate (case 1) while developing significantly lower friction factor. The temperature rise of the fluid and the friction factor developed for case 5 were around 10% and 40% lower than case 1, respectively. In the second objective, the thermal performance of the IJSAH was improved by using wire mesh of three different sizes. The wire mesh sizes were 12.7 × 12.7 mm (0.5 × 0.5 inch), 38.1 × 38.1 mm (1.5 × 1.5 inch), 76.2 × 76.2 mm (3 × 3 inch) with nozzle diameter ( ) equal to 3 and 6 mm and Reynolds number () ranging from 4913 to 13103. The variation of Nusselt number (), friction factor (), thermo-hydraulic performance parameter (THPP), and effective efficiency (ηୣ ) were evaluated for varying . Maximum was developed for case 3 and equalled 109.86, which was 7.3% and 246% higher than a smooth IJSAH and flat plate solar air heater (FPSAH), respectively. The minimum friction factor attained equated to 0.031 for case 2 at = 13103. The maximum THPP attained by the setup equalled 1.78 for case 4, having = 6 mm. The THPP attained by case 4 across the range of was on an average 9.15% higher when compared to smooth IJSAH with = 3 mm. Additionally, the system achieved maximum ηୣ of 0.537 at = 4913 for case 4. Finally, it was recommended to use a wire mesh having a mesh size equal to 38.1 × 38.1 mm with = 6 mm for optimum performance. For the third objective, an experimental study was conducted to analyse the thermal and frictional attributes of an IJSAH with an absorber plate having stepped transverse ribs with varying pitch and size. Two ribs of dimension 2×4 cm (R1) and 4×6 cm (R2) were tested. The pitch (p) between ribs was 2, 4, and 8 cm, with varying from 4913 to 13103. The jet hole diameter considered were 3, 6, and 9 mm. The maximum with the recommended R1 rib having p = 4 cm and = 3 and 6 mm equalled 128.784 and 104.5004 at = 13103, respectively, which was 31.22 and 21.76% higher than that generated by smooth IJSAH. The friction factor () generated by the ribbed IJSAH having = 6 mm and p = 4 cm was 57.08% lower than ribbed IJSAH with = 3 mm. The peak THPP achieved was for R1 rib with p = 4 cm and = 6 mm and equalled 1.75, which was 19.49% higher than smooth IJSAH. The R1 rib with p = 4 cm at = 11465 demonstrated better thermal characteristics based on detailed investigation. For the fourth objective, an experimental study on the effect of shortening of jet plate perforation length on the thermal and frictional performance of an impinging jet solar air heater with ribs (RIJSAH) was conducted. The jet span length was shortened to 80% and 60% of the total length, while the considered were 3, 6, and 9 mm. There was an increase in the Nusselt number with a decrease in jet span length (JSL) for = 6 mm. It was found that, at = 11465, the developed by ribbed IJSAH with = 6 mm and JSL = 60% was only 5.06% less than that developed by RIJSAH with = 3 mm while suffering a friction factor 24.13% less than that generated by the latter. The THPP attained generally decreased with a decrease in JSL, but at higher , the THPP attained by RIJSAH with = 6 mm and 60% JSL was higher than that achieved by RIJSAH with = 6 mm and 80% JSL. There was a clear decrease in temperature difference between the fluid and the absorber plate with a decrease in JSL, which enhanced the thermal performance of the system. In conclusion, it is recommended that RIJSAH be fabricated with = 6 mm and 60% JSL to achieve well-optimised thermal performance. The thermal and frictional attributes of RIJSAH having a jet plate modified with protruded circular nozzles (PCN) were estimated. The inside diameter considered for the protruded nozzles were 3, 6, and 8 mm, while the thickness of these nozzles was kept constant at 2 mm. Subsequently, the performance of PCN IJSAH with a reduced span of the jet plate was studied. The jet plate span length (JSL) was modified from 100% ( = 1400 mm) to 80% (1120 mm) and then 60% (840 mm). For = 3 mm, the attained by PCN IJSAH with and without ribs were approximately the same and, as such, were not useful. For = 6 mm, the average attained by PCN IJSAH with ribs was 3.9% higher than that attained by PCN IJSAH without ribs. Any decrease in JSL resulted in an increase in attained. The average attained by PCN RIJSAH with = 6 mm and 60% JSL was 29.72% higher than that achieved by PCN RIJSAH with 100% JSL while generating a lower friction factor. The THPP improved upon the shortening of JSL. The maximum THPP was attained by PCN IJSAH with ribs for = 6 mm and JSL at 60% for = 11465 and was equal to 1.98. It was concluded that PCN RIJSAH, with a reduced span of jet plate length, developed better thermal performance relative to the friction factor generated
Deep Learning Methods to Enhance IoT-based Air Pollution Forecasting
No full textThe research endeavor on utilizing deep learning for air pollution forecasting is escalating, driven by the availability of Internet of Things (IoT) based devices, the advent of deep learning, statistical modeling, and growing emphasis on climate change. An insight into the challenges in predicting pollution levels necessitates development and adoption of innovative approaches based on deep learning models. This thesis aims to develop new deep learning algorithm models enabling early information pertaining to pollutant concentration detection in specific locations. However, task of pollution forecasting is fraught with challenges due to the complex multivariate pollutants, weather conditions, and intricate spatial-temporal dynamics of nearby areas. To address the aforementioned challenges, this research proposes an array of strategies leveraging IoT devices and deep learning algorithms to enhance air quality monitoring, aligning with sustainable development goals related to clean air, sustainable cities, and climate action. Novel deep learning frameworks showcased in this thesis aim to streamline the computational processes while effectively extracting spatiotemporal characteristics, resulting in improved pollution prediction accuracy. Use of optimized algorithms, hyperparameter tuning, and application of computational methods to real-time environment issues to solve complex air quality prediction problems enriches the contribution of this research. Firstly, an attention-based AQI forecasting model has been developed with a combination of bidirectional-gated recurrent unit (Bi-GRU) and bidirectional-long short term memory model (Bi-LSTM) networks. A gate attention mechanism and a denoising mechanism are incorporated into this model in order to minimize error rates, optimize attention weights, and improve prediction accuracy. It has a linear activation function, a dropout layer to create a 1D array, and a time-distributed layer with sigmoid and (rectified linear unit) ReLU activation functions. With the Adam optimizer and mean square loss function, optimization is accomplished. Secondly, a novel Dense Residual GRU-CNN Network with Attention Mechanism (DRAGCN) is developed, featuring Global Max Pooling and a 1D convolutional layer. This model performs well in both univariate and multivariate scenarios, preventing overfitting and disappearing gradients. Performance is enhanced, and training is stabilized through normalization using min-max scaling. It combines GRU’s gating mechanism with convolutional layers, Adam optimizer, and ReLU activation to capture long-term dependencies in sequential data, results in a non-negative scalar output to represent expected pollution levels. Furthermore, a deep learning-based metaheuristic optimization algorithm, the Xavier Reptile Switan-h-based LSTM model (XRSTH-LSTM), has been developed, which expounds the versatility of different frameworks used for air pollution prediction. It addresses the vanishing gradient problem by combining the Xavier Reptile Search Algorithm (XRSA) and LSTM networks with the Swish-Tanh (Switan-h) activation function. The dataset was expanded to evaluate the robustness of the model, and normalization was applied using the Min-Max method along with hidden layer optimization. Finally, a step forward has been taken with the successful implementation of a hardware design and product prototype application using a three-layered IoT architecture. This includes sensor calibration, PCB design, and GUI implementation, along with an Android application featuring alert notifications. The system utilizes Raspberry Pi for real-time monitoring of harmful pollutants, directing sensor data to a cloud database like Firebase. This IoT-based system can be practically applied and tailored further according to specific needs in air quality monitoring. The developed models were evaluated, and a comparative analysis was carried out based on prediction parameters to provide for timely decision-making and preemptive action. The proposed approaches in this research work collectively aim to improve the accuracy and efficacy of air pollution forecasting. Through rigorous testing, along with the comparative results obtained from the evaluation, these models demonstrate their efficiency and potential as valuable tools for decision-making processes in policy-making, environment, and biodiversity domains
Various Ordering Results between Two Finite Mixtures Arising from Some Families of Distributions
No full textFinite mixture models are useful for modeling heterogeneous data sets. It is mainly applicable for the reliability analysis of a system with multiple components. It also combines a finitely many subpopulations, when they have infinitely many elements. The stochastic comparison of two finite mixtures is an interesting topic which could be useful to compare two systems with multiple components, heterogeneous in nature. This thesis focuses on the study of various stochastic comparisons of finite mixture random variables. The main goal of the thesis is to establish several ordering results between two finite mixture random variables with respect to the usual stochastic order, hazard rate order, reversed hazard rate order, likelihood ratio order, ageing faster order in terms of reversed hazard rate, dispersive order, star order, Lorenz order, and right-spread order. When random variables of the subpopulations of a mixture model are chosen from general and specific distributions, such as the general parametric, location-scale, exponentiated location-scale, generalized Weibull, and inverted-Kumaraswamy, several sufficient conditions are proposed to compare two finite mixture random observations. In particular, we consider a general parametric family of distributions with cumulative distribution function FX (x) = F (x; ), x > 0, where > 0 is a model parameter. Here, the usual stochastic and hazard rate orders are established when the model parameter vectors are connected by p-larger and reciprocally majorization orders. Sufficient conditions are also obtained, under which the reversed hazard rate order holds between two mixture random variables. Further, the usual stochastic, hazard rate, reversed hazard rate, and dispersive orders are established between two mixture random variables, when a matrix of mixing proportions and model parameters changes to another matrix in a certain mathematical sense. Next, we consider the location-scale family of distributions with cumulative distribution function FX (x) = F (x ), x > , where > 0 and > 0 are the location and scale parameters, respectively. Here, we have established the usual stochastic order, hazard rate order, reversed hazard rate order, and likelihood ratio order by taking heterogeneity in one parameter. Further, ordering results have been established by considering heterogeneity in two parameters with respect to the usual stochastic order and hazard rate order. We consider finite mixture models with subpopulations having exponentiated location-scale family of distributions with cumulative distribution function FX (x) = F (x ), x > , where > 0, > 0, and > 0 are the location, shape, and scale parameters, respectively. Here, we establish several ordering results in stochastic sense, and sufficient conditions are derived to compare two finite mixture models with respect to the usual stochastic order. The conditions depend on the weak supermajorization and reciprocally majorization orders. In order to validate some of the results, we have carried out a numerical simulation study. Next, we consider the generalized Weibull family of distributions with cumulative distribution function FX (x) = 1 e (!( x))β , x > 0, > 0, > 0, > 0, where !( x) = F ( x)/1 F ( x). Here, we present sufficient conditions under which the usual stochastic ordering, hazard rate ordering, and likelihood ratio ordering hold between the two finite mixture random variables. The sufficient conditions are based on the majorization and weak supermajorization orders between the associated model parameters. We also develop sufficient conditions based on unordered majorization order, under which two finite mixture models are comparable with respect to the usual stochastic order. We assume the inverted Kumaraswamy distribution with cumulative distribution function FX (x) = (1 (1 + x) ) , x > 0, > 0, > 0 as the components of the mixture random variables, and then find some ordering results between them. Here, we establish the usual stochastic order between two finite mixture random variables based on the concepts of weak supermajorization and weak submajorization orders. Also, we obtain comparison results with respect to the usual stochastic order and ageing faster order in terms of the reversed hazard rate when there is heterogeneity in two parameters. Further, we examine ordering results between the finite mixture models with respect to the reversed hazard rate and likelihood ratio orders. In addition, we have studied stochastic comparison results between two finite -mixture models with a general parametric family of distributions and generalized Weibull family of distributions in the sense of the usual stochastic ordering. In developing the usual stochastic order, we have proposed sufficient conditions which depend on the p-larger, reciprocally majorization, majorization, and weak supermajorization orders. In addition, we have also proposed sufficient conditions to compare two finite -mixture models based on the concept of unordered majorization order. we also derive sufficient conditions, under which the mixture random variables constructed by generalized Weibull family of distributions satisfy usual stochastic order for the case of -mixture models. Furthermore, we consider ordering results between two finite mixture models with multiple-outlier components. Here, we study two different problems: (i) finite arithmetic (classical) mixtures in multiple-outlier model with location-scale distributed components and (ii) finite -mixtures in multiple-outlier with general family distributed components, and the obtain some ordering results. In addition, multiple numerical examples and counterexamples are shown to demonstrate the efficacy of the established theoretical findings. Furthermore, a simulation study is carried out to estimate the model parameters of LSF of distributions in Chapter 9. Finally, the conclusion of the thesis with some new problems are presented
Innovative Method for Efficiency Improvement in IPMSM Drive through Sensor Reduction
No full textAn innovative approach to enhance the performance and efficiency of interior permanent magnet synchronous motor (IPMSM) drives is introduced, focusing on two key aspects: maximizing torque per ampere (MTPA) control and addressing sensor reduction challenges in three-phase motor drives. A simple and computationally efficient MTPA control method for IPMSM drives is developed to enhance overall drive efficiency. To calculate MTPA current references accurately, a self-correction of parameters equivalent base current is developed for IPMSMs, which exhibit significant variation in flux linkage and quadrature axis inductance due to temperature and magnetic saturation, but show negligible variation in direct axis inductance during normal operating conditions. In addition, this novel MTPA control law helps to avoid the formation of memory-intensive look-up tables (LUTs), complex computation of actual motor parameters, and several types of MTPA indicators, which are widely used to deal with parameter variations for MTPA operation. Consequently, the proposed method can provide accurate MTPA current references readily and in real time, enabling rapid MTPA control with less computational burden compared to conventional MTPA methods. Simulation and experimental results validate the simplicity, efficacy, and robustness of the proposed MTPA technique which proves to be a great alternative for implementation in low-cost industrial IPMSM drives for numerous applications. Secondly, the study addresses issues inherent in current sensor reduction, particularly in single current sensor (SCS)-based IPMSM drives with MTPA control, focusing on current sampling delay errors that can lead to reduction of efficiency due to speed fluctuations and high torque ripple during IPMSM's wide range of operations. Due to their reduced efficiency, SCS-based three-phase drives are not attracting significant interest despite their potential for addressing sensitivity mismatch issues and reducing costs in various industry applications. In this study, a computationally efficient and accurate model-based current sampling delay error compensation (SEC) scheme based on a new SCS position with a double branch current sampling technique is proposed for an IPMSM drive. In order to improve current reconstruction precision, the compensation strategy includes rotor angle compensation of IPMSM and dead time effect mitigation for the reduction of non-ideal behavior of the inverter, which does not require major computation. Also, dc-link voltage utilization is improved significantly without any external dc-link control. By reducing current reconstruction errors, this scheme enhances drive performance without imposing significant computational burden on the controller. Furthermore, the study explores SCS-based quasi-Z-source inverter (qZSI) drives to remove inherent current measurement dead zones in conjunction with IPMSM instead of putting an additional dc-dc converter. Also, a comprehensive analysis of SCS-based qZSI drive with IPMSM is carried out considering elevated inductor current ripple in conventional qZSI-IPMSM during removal of outer sector boundary dead zone. A new dead zone compensation technique is proposed based on overlapping of active states with ZSVMs pulse width modulation (PWM) strategy. Both current sampling and qZSI operation with ZSVMs are investigated to test the feasibility of three-phase current reconstruction in current measurement dead zones in order to improve the operating range of the IPMSM drive. The practical implementation of ZSVMs-based current sampling also covers single dc-link branch SCS topology, which not only enables variable dc-link voltage control for efficiency enhancement along with MTPA control, but also guarantees inductor size, overall cost, and volume reduction. The proposed SCS-based qZSI-IPMSM drives with MTPA control is verified with experimental results, demonstrating their potential for low-cost, reliable, and efficient motor drives for electric vehicles and industrial applications, while maintaining high computational efficiency
Design and Evaluation of a Kinesthetic Digital Game for English Alphabet Training
No full textAlphabet training of primary school students is an essential, but challenging activity. Alphabet knowledge is an important fundamental literacy skill which has been found to directly impact the future academic success of students. Game-based learning and the use of multimodal engagement activities have been found to be effective intervention strategies in successful alphabet training programmes. In this study, a Kinect based digital Catcher Game - I was developed for English alphabet training of primary school students in government primary schools in Rourkela, Odisha. For a duration of 4-weeks, a control group (CG) consisting of 41 class-III students received traditional classroom training for 60-minutes each day. During the same period, an intervention group (IG) consisting of 45 class-III students was trained for 30-minutes in the traditional class and using a Catcher Game – I session for another 30-minutes. The alphabet knowledge performances of the two groups were compared before and after the game-based training intervention. During the pre-test, no statistically significant differences were observed in the alphabet knowledge performance of the CG and IG. In the post-intervention evaluation, the IG students performed significantly better than the CG. During their post-intervention feedback, most of the IG students and teachers talked favorably about the use of Catcher Game – I intervention and attributed the significant improvement in IG performance to this intervention. Post-intervention, the teachers also reported a significant improvement in the motivation and engagement among the IG students during regular classroom sessions. Later, the Catcher Game - I was further updated to train the players using a multisensory training approach. This involved the use of visual picture mnemonics (using the first letter of the object spelling) as well as the sound of the letter name. This updated version was named Catcher Game - II. Again, the impact of the new kinesthetic digital game on the alphabet knowledge performance was assessed. Also, the classroom engagement of primary school students was assessed. 111-Primary school students were randomly assigned to one of the two treatment groups (CG and IG) and received English alphabet training at the primary school for 6-weeks. In the CG, the students received English alphabet training using the traditional teaching methods for 60-minutes daily. In the IG, the students were daily trained using the traditional method as well as a kinesthetic digital game for 30-minutes each. The student alphabet knowledge performances were measured using - (1) letter name accuracy in isolation, (2) letter name fluency in isolation, (3) letter name accuracy in word context, and (4) paired associate learning. The extent of student engagement was recorded and compared during training. Within-group comparisons were made for the pre-test and post-test data. Also, between-group comparisons were made between the CG and IG. It was found that the students from both the groups achieved improvements in their performances from the pre to the post test phase. Improvements were also observed in the session engagement from the pre-test stage to the post-test stage. However, the IG students demonstrated a statistically significant higher mean score gain than CG students in their alphabet knowledge performance as well as in the session engagement
Development of a Low-Cost Adsorbent for Removal of Excess Fluoride from Water in Mining Areas
No full textFluoride is an essential mineral for the body as it helps strengthen the bones and teeth, but high amounts of fluoride exposure can have dangerous health effects. Along with the scarcity of water, fluoride contamination is recognized as a major problem worldwide. The World Health Organization has set the maximum permissible limit for fluoride at 1.5 mg/L. However, long-term exposure to excess fluoride has several side effects on human health, water bodies, environment, and agricultural fields. The source of fluoridation may include naturally occurring minerals, coal mines, or anthropogenic action. Several materials (biomass, rice husk ash, bone char, shale, and low-grade coal) and methods (adsorption, membrane separation, and column studies) have been in use for the defluoridation of water. Recent reports from the Central Ground Water Board (CGWB), Govt. of India, indicate an increase in the concentration of fluoride in both surface and ground waters in many industrial areas including mining locations. The mining areas such as Jharia and Bokaro (Jharkhand), Korba (Chhattisgarh), Jharsuguda and Talcher (Odisha), Nagpur (Maharashtra), Ledo (Assam), Neyveli (Tamil Nādu) are among the prominent places affected by a high concentration of fluoride in water. As per the records of CGWB, people in 27 out of the 30 districts of Odisha are affected by fluoride contamination. Drinking water in many villages of Angul, Khurda, Puri, Nayagarh, Boudh, Kandhamal, Bolangir, Bargarh, and Nuapada districts is contaminated with excessive quantities of fluoride. This attracts researchers to carry out further research in the field of fluoride contamination and mitigation of high fluoride content in water. There are various studies that used a variety of adsorbents for the removal of fluoride from contaminated water, but none of them were targeted to the huge quantities of water that are generated in coal mining areas. In this research, shale, which is a common coal mine waste, has been used as an adsorbent for fluoride removal from aqueous solution. Along with the defluoridation property of shale, the effect of weathering on the adsorption property of shale was also analyzed using different characterization tests, such as Proximate analysis, XRD, SEM- EDS, FTIR, BET,and TGA. Two types of shale samples were collected, crushed, and used in the adsorption process in the laboratory using a synthetic fluoride solution. Key parameters such as particle size of shale, contact time, adsorbent dose, initial fluoride concentration, and pH were taken into consideration. The maximum efficiency of removal for type I (weathered) shale was 47.05% compared to type II (fresh) shale i.e. 40.02% for 3 ppm initial fluoride solution within 60 min in pH range 5–7 using batch adsorption process. The fluoride removal efficiency of the adsorbents was increased by using heat activation (100oC, 500oC, and 800oC) and chemical activation using different chemicals, viz. KOH, NaOH, H2SO4, and ZnCl2. Maximum removal of fluoride obtained was 85.01% with typeI heat activated 800oC and 90.2% using type I chemically activated KOH. The change in pH and total suspended solid present before and after the adsorption process were also taken into consideration. The efficiency of carbonaceous shale (CS I) collected from the Samleshwari opencast project was also compared with other carbonaceous shales (CS II) collected from the Basundhara opencast project and ferruginous shales collected from Guali (FS I) and Barsuan iron ore mines (FS II). Both Carbonaceous shale and Ferruginous shale have the potential to be used as an adsorbent for F- removal but a suitable adsorbent should not only have high F- adsorption capacity and cost-effectiveness but also be amenable to easy desorption of the adsorbed F- and capable of efficient regeneration for reuse. The desorption capacity obtained for carbonaceous shale 2M NaOH (24 h.) was obtained as 98.1%, whereas ferruginous shale desorption capacity was found to be 69%. The regeneration study was carried out up to five cycles using 1M HNO3 solution, kept for 2 h. In the fifth cycle, carbonaceous shale was able to remove 15.64% F- whereas ferruginous shale removed only 11.5% F- from the aqueous solution. The desorption and regeneration of ferruginous shale is less than carbonaceous shale making carbonaceous shale a better and suitable adsorbent for F- removal. The adsorption followed pseudo-second order kinetics and Freundlich isotherm with an adsorption capacity of 23.66 mg/g, and 21.33 mg/g for weathered and fresh shale respectively. The characterization tests showed more clayey content in the weathered shale compared to fresh shale, making it more porous and suitable as a fluoride adsorbent. XRD analysis showed the F− containing minerals such as Villiaumite (5.1%) and Fluorite (4.3%) in F− loaded weathered shale, confirming the F− adsorption onto the shale surface. The major advantage of shale over other existing adsorbents is that the fluoride is removed without significant change in pH, and there are no or very less suspended ions that can be found in treated water. This means the water may not need any secondary treatment after the adsorption process. Shale is a very common and readily available mine waste, that is used for the ceramic industry, building materials, and road construction, making it an economical material to be used as an adsorbent for fluoride removal