Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Fracture strength evaluation of titanium alloys using modified average stress criterion

Structural integrity procedures were used to demonstrate the fitness for the purpose of engineering components transmitting loads. The prediction of the fracture strength of titanium alloys containing sharp notches through the damage model depends on the un-notched strength and the critical length of the damage zone ahead of the notch. In general, the critical length of the damage zone depends on the material, specimen, and size of the sharp notch. Modifications were made in one of the stress fracture criteria known as the average stress criterion for accurate prediction of notched tensile strength of titanium alloy specimen containing sharp notches. To examine the adequacy of these modifications, fracture data of center-cracked titanium alloys with various thicknesses are considered. The notched （fracture） strength estimates are found to be close to the test results. The modified average stress criterion is very simple to predict the notched tensile strength.

Analysis of vibration signal responses on pre induced tunnel defects in friction stir welding using wavelet transform and empirical mode decomposition

Among many condition-monitoring systems in welding operation,Defect identification is an important method to ensure the precision in finishing operation.Friction stir welding is a solid state welding process used to join two metals without the use of electrode at lower temperatures.The aim of this present work is to identify and localize the tunnel defect in aluminum alloy and measure the distance of the defect zone in the time domain of the vibration signal during Friction stir welding.The vibration signals are captured from the experiments and the burst in the vibration signal is focused in the analysis.A signal-processing scheme is proposed to filter the noise and to measure the dimensional parameters of the defect area.The proposed technique consists of discrete wavelet transform(DWT),which is used to decompose the signal.The enveloping technique is applied on the decomposed zero padded signal.The continuous wavelet transform(CWT) has been implemented on detailed signal followed by a time marginal integration(TMI) of the CWT scalogram.Empirical mode decomposition(EMD) is used to replace the detailing coefficients from DWT with Intrinsic Mode Function(IMF).Statistical parameters such as mean,kurtosis,S.D and crest factor have been extracted from the final filtered signal for validating the defect welds from the control defect free welds.Results produced were found to be that kurtosis is 7.4402 for tunnel defect induced weld and 3.3862 for defect free welds.As the increase in kurtosis value predicts the defect zone impact in the signal.The measurement of the defect zone of the cut 1(voids) and cut 2(tunnel grooves) in correlation with the processed signal is found to produce a much redundant results with an error rate of 0.02.

Fracture strength of centre surface cracked tensile specimens made of 2219-T87 Al alloy welding

Fracture data of both parent metal and weldment metals from surface cracked tensile plates made of 2219-T87 Al alloy at cryogenic temperatures were correlated using a modified inherent flaw model. Fracture parameters to generate the failure assessment diagram were determined for the material. Fracture analysis was carried out considering the ultimate tensile strength value and the fracture data of aluminium base metal and weldment metal generated from center–surface cracked tensile specimens having different thicknesses. The failure assessment diagram of a material generated from tensile fracture plate configuration can be applied to failure pressure estimation of any cracked component, made of the same material.

Defect assessment of welded specimen considering weld induced residual stresses using SINTAP procedure and FEA

The defect assessment in butt-welded joint of ASTM A36 steel plates and 7075-T7351 aluminum alloy plates containing transverse through thickness crack was analyzed using SINTAP procedure and FEA incorporating weld induced residual stresses. Weld induced longitudinal residual stress profile can be obtained through SINTAP procedure, FEA or experimental analysis. This residual stress profile can be fitted with the trapezoidal residual stress profile available in SINTAP. For three different cases, crack length and residual stress intensity factor （SIF） are calculated and its comparison with the results obtained through FEA is plotted with respect to crack length. The stress intensity factor for mechanical loading is also plotted in the same graph. Using this graphical plot, the total SIF, including residual stress and mechanical loading, can be calculated for any particular crack size. The total SIF can be compared with the fracture toughness of the material for damage tolerance analysis. Also a failure assessment diagram is drawn for welded 7075-T7351 aluminum alloy plates with different crack sizes for as-welded （only residual stress） and mechanical loading along with the existing weld induced residual stresses to show the safety level for a particular crack size and mechanical loading.

Influence of rutile(TiO_2) content on wear and microhardness characteristics of aluminium-based hybrid composites synthesized by powder metallurgy

The effect of rutile（TiO_2） content on the wear and microhardness properties of aluminium（Al）-based hybrid composites was explored. The proposed content of TiO_2（0, 4%, 8%, 12%, mass fraction） was blended to Al-15% SiC composites through powder metallurgy（P/M） process. Wear test was conducted using pin-on-disc apparatus under dry sliding conditions. Fabricated preforms were characterized using X-ray diffractometer（XRD）, scanning electron microscope（SEM） and energy-dispersive X-ray spectrometer（EDS）. Optical micrographs of the composite preforms display uniform distribution of TiO_2 throughout the matrix. Quantitative results indicate that wear resistance and microhardness increase with the increase of TiO_2 content. SEM images unveil that high wear resistance is attributed to high dislocation density of deformed planes and high hardness of TiO_2. SEM images of wear debris display gradual reduction in mean size of debris when TiO_2 content increases. EDS spectra confirm the presence of oxide layer which obviously reduces the effective area of contact between the sliding surfaces thereby lowers the wear loss of composites. The observation concludes that delamination and adhesive wear are the predominant mechanisms.

Ultrasonic Studies of 4-Aminobutyric Acid in Aqueous Salbutamol Sulphate Solutions at Different Temperatures

Ultrasonic speeds of 4-aminobutyric acid in 0.0041,0.0125 and 0.0207 mol·kg^-1 aqueous salbutamol sulphate（SBS） solutions are measured at 308.15,313.15 and 318.15 K.Isentropic compressibility kS,change in isentropic compressibility△k S,relative change in isentropic compressibility（ △kS /kS^0） ,apparent molal compressibility kφ,limiting apparent molal compressibility kφ^0 ,transfer limiting apparent molal compressibility k φ^0,hydration number nH,pair and triplet interaction parameters kAS,kASS are estimated.The above parameters are used to interpret the solute-solute and solute-solvent interactions of 4-aminobutyric acid in the aqueous salbutamol sulphate solutions.

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of promi-nently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing(MIMO–OFDM).One among an effective solution for channel estimation in wireless communication system,spe-cifically in different environments is Deep Learning(DL)method.This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder(CNNAE)classifier for MIMO-OFDM systems.A CNNAE classi-fier is one among Deep Learning(DL)algorithm,in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another.Improved performances are achieved by using CNNAE based channel estimation,in which extension is done for channel selection as well as achieve enhanced performances numerically,when compared with conventional estimators in quite a lot of scenar-ios.Considering reduction in number of parameters involved and re-usability of weights,CNNAE based channel estimation is quite suitable and properlyfits to the video signal.CNNAE classifier weights updation are done with minimized Sig-nal to Noise Ratio(SNR),Bit Error Rate(BER)and Mean Square Error(MSE).

Supervision of Milling Tool Inserts Using Conventional and Artificial Intelligence Approach: A Review

Due to continuous cutting tool usage,tool supervision is essential for improving the metal cutting industry.In the metal removal process tool,supervision is carried out either by an operator or online tool supervision.Tool super-vision helps to understand tool condition,dimensional accuracy,and surface superiority.For downtime in the metal cutting industry,the main reasons are tool breakage and excessive wear,so it is necessary to supervise tool which gives better tool life and enhance productivity.This paper presents different conventional and artificial intelligence techniques for tool supervision in the processing procedures that have been depicted in writing.

TBDDoSA-MD:Trust-Based DDoS Misbehave Detection Approach in Software-defined Vehicular Network(SDVN)

Reliable vehicles are essential in vehicular networks for effective communication.Since vehicles in the network are dynamic,even a short span of misbehavior by a vehicle can disrupt the whole network which may lead to catastrophic consequences.In this paper,a Trust-Based Distributed DoS Misbehave Detection Approach(TBDDoSA-MD)is proposed to secure the Software-Defined Vehicular Network(SDVN).A malicious vehicle in this network performs DDoS misbehavior by attacking other vehicles in its neighborhood.It uses the jamming technique by sending unnecessary signals in the network,as a result,the network performance degrades.Attacked vehicles in that network will no longer meet the service requests from other vehicles.Therefore,in this paper,we proposed an approach to detect the DDoS misbehavior by using the trust values of the vehicles.Trust values are calculated based on direct trust and recommendations(indirect trust).These trust values help to decide whether a vehicle is legitimate or malicious.We simply discard the messages from malicious vehicles whereas the authenticity of the messages from legitimate vehicles is checked further before taking any action based on those messages.The performance of TBDDoSA-MD is evaluated in the Veins hybrid simulator,which uses OMNeT++and Simulation of Urban Mobility(SUMO).We compared the performance of TBDDoSA-MD with the recently proposed Trust-Based Framework(TBF)scheme using the following performance parameters such as detection accuracy,packet delivery ratio,detection time,and energy consumption.Simulation results show that the proposed work has a high detection accuracy of more than 90%while keeping the detection time as low as 30 s.

PZT Based Smart Aggregate for Unified Health Monitoring of RC Structures

The most familiar civil engineering structure is reinforced concrete (RC) structure. Performance of structure undergoes changes during their service life with time. Thus, it is of great concern to monitor the health of RC structure. Structural health monitoring (SHM) is the art of detecting the changes in structure that influences its performance. Various techniques to monitor the health of structure are broadly studied worldwide. PZT based smart aggregate can play an effective role as an advanced tool in the development of structural health monitoring. This research work contributes for proposing a more generous Non-Destructive Evaluation (NDE) technique for structural health monitoring by using smart materials. If performance of a structure deviates from the design parameters with time, appropriate and effective maintenance is required. Considering the relevant need of RC structures, a more sensitive and cost-effective approach by using Electro-Mechanical Impedance (EMI) technique has been proposed for implementation in real-life situations. In general, surface bonded PZT transducer is used for SHM. Since PZT transducers are of very small dimension and brittle in nature, for consistent characteristics, they should be protected from severe environmental condition and other external interruptions. For this reason, PZT transducer is embedded in structure at the time of construction and manufacturing of the embedded transducer is simple. The proposed EMI technique assesses the health of RC structures more rationally by embedding PZT transducer in the structure, whose health is to be monitored over the user specified preset frequency range. The conductance and susceptance signatures are acquired by using LCR meter. At any future point of time, when it is desired to assess the health of structure, the conductance and susceptance signatures are acquired and further utilized for damage detection and quantification. The Root Mean Square Deviation (RMSD) is used to specify damage severity.

Effect of Temperature on Volumetric and Viscometric Properties of Homologous Amino Acids in Aqueous Solutions of Metformin Hydrochloride

Density（ρ）and viscosity（η）are measured for glycine,DL-α-alanine DL-α-valine,and DL-α-leucine in 0.05,0.10,0.15 and 0.20 mol·L^-1aqueous metformin hydrochloride at 308.15,313.15 and 318.15 K.The measured values are used to estimate some important parameters,such as partial molal volume Vφ,standard partial molal volume Vφ^0,transfer volume ΔVφ^0,hydration number nH,the second derivative of infinite dilution of partial molal volume with respect to temperature,viz., ^2 Vφ^0 /T^2,viscosity B-coefficient,variation of B with temperature,viz., dB/dT,free energy of activation per mole of solvent Δμ1^＊0 and solute Δμ2^0＊ of the amino acids.These parameters are interpreted in terms of solute-solute and solute-solvent interactions and structure making/breaking ability of solutes in the given solution.In addition,Vφ^0,0 ΔVφ^0,viscosity B-coefficient,ΔB and Δμ2 ^0＊ are split into group contributions（NH3^＋ COO ^-）and -CH2 of the amino acids using their linear correlation and their behavior is discussed.

Irrigation Planning with Conjunctive Use of Surface and Groundwater Using Fuzzy Resources

Surface and groundwater are related systems. They can be used conjunctively to maximize the efficient use of available resources. Groundwater may be used to supplement surface water to cope with the irrigation demands to meet the deficits in low rainfall periods. The parameters involved in the present study are groundwater availability, surface water availability, water requirement of crops and crop area. The inclusion of such uncertain parameters leads to accept the decision making process beyond the consideration of economic benefits. In the present study, an irrigation planning model is formulated by considering the conjunctive use of surface and groundwater. The resources in the present model, i.e. the area, surface water and groundwater availability are represented by fuzzy set. The linear membership function is used to fuzzify the objective function and resources. The model is applied to a case study of Jayakwadi project and solved for maximization of the degree of satisfaction (l) which is 0.546.

Optimal Operation of Multipurpose Reservoir for Irrigation Planning with Conjunctive Use of Surface and Groundwater

In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of the present study is to maximize the net benefit from the command area under consideration. The constraints imposed on the objective function are maximum and minimum irrigation demands, reservoir storages and canal capacity. The model takes into account the continuity constraint which includes inflows in to the reservoir, releases for irrigation, releases for hydro-power generation, evaporation losses, feeder canal releases, initial and final storages in the reservoir in each time period. The developed model is applied to the case study of Jayakwadi reservoir stage-I, built across river Godavari, Maharashtra, India. Initially the model is solved for the availability of surface water which results in net benefit of 3373.45 million rupees with irrigation intensity is 57.07%. Next the model solved by considering the availability of surface water and available potential of groundwater in the area, which results in net benefits of 3590.02 million rupees with an intensity of irrigation 58.48%. The present model takes in to account the socio-economic requirement of growing the essential crops to meet the requirement of the society. The model has also generated the canal wise optimal releases for irrigation and power, monthly utilization of groundwater, storages in the reservoir at the end of every month and corresponding head over the turbine.

Design of Six Element MIMO Antenna with Enhanced Gain for 28/38 GHz mm-Wave 5G Wireless Application

The fifth-generation(5G)wireless technology is the most recent standardization in communication services of interest across the globe.The concept of Multiple-Input-Multiple-Output antenna(MIMO)systems has recently been incorporated to operate at higher frequencies without limitations.This paper addresses,design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz,respectively for 5G millimeter(mm)-wave applications.The proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53×7.85×0.8 mm^(3).The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance microstrip line.It also has an I-shaped slot and two electromagnetically coupled parasitic slotted components.This design is initially constructed as a single-element structure and proceeded to a six-element MIMO antenna configuration with overall dimensions of 50×35×0.8 mm^(3).The simulated prototype is fabricated and measured for analyzing its performance characteristics,along with MIMO antenna diversity performance factors making the proposed antenna suitable for 5G mm-wave and 5G-operated handheld devices.

Effects of Harmonics on Power Loss in XLPE Cables

Harmonics in power systems is increasingly at high level. Also, there has been an incredible growth in the use of cross linked polyethylene (XLPE) cables in distribution systems. Harmonics cause additional power loss/temperature rise;causing premature failure of cables. Catastrophic failure of power cables leads to great inconvenience to consumers and loss of system reliability and money. To avoid the overheating of power cables;the additional power loss due to harmonics should be accurately calculated and properly accommodated by derating the cable. The present method of calculating the power loss in cables in harmonics rich environment is very arduous. The aim of this paper is to present the reasonably accurate method for evaluating effects of harmonics on the power loss in XLPE cables. Computational model is developed in MATLAB for power loss calculation using conventional method. Using this model, calculations are performed for aluminium and copper conductor XLPE cables of different size and type;for three different types of harmonics spectrums having total harmonics distortion (THD) of 30.68%, including all odd harmonics components up to 49th order. Using these results;a mathematical model in the form of simple empirical formula is developed by curve fitting technique. The results obtained by various models are presented and compared with error justification.

Grid Interconnection of Wind Energy System at Distribu-tion Level Using Intelligence Controller

Wind generation is being increasingly connected at distribution level due to increasing load demand. Permanent magnet synchronous generator (PMSG) is connected to?the wind turbine directly. Through the full power control of AC-DC-AC converters, the electrical power is then connected to the power grid. The power conversion circuits are made up of generator-side three phase diode rectifiers, boost converter and the grid-side three bridges and four wire inverters. A boost converter is controlled through an intelligence controller to maintained DC power constant despite of Variable output of PMSG, the grid-connected operation is constructed using the hysteresis current control method. The inverter is controlled to perform following function 1) power converter to inject power generated from RES to the grid, and 2) shunt APF to compensate current unbalance, load current harmonics, load reactive power demand and load neutral current. The model is implemented in MATLAB/ Simulink using sim power system.

Prediction of Suitable Crops Using Stacked Scaling Conjugant Neural Classifier

Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were following ancestral patterns,which could sometimes lead to the wrong selection of crops.In this research work,the feature selection method is adopted to improve the performance of the classification.The most relevant features from the dataset are obtained using a Probabilistic Feature Selection(PFS)approach,and classifi-cation is done using a Neural Fuzzy Classifier(NFC).Scaling Conjugate Gradient(SCG)optimization method is used to update the weights.The data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and rainfall.The proposed method recommends suitable crops for cultivation based on site-specific para-meters.Experimental result shows that the proposed method provides high accu-racy and efficiency as compared to existing methodologies.

Qualitative Abnormalities of Peripheral Blood Smear Images Using Deep Learning Techniques

In recent years,Peripheral blood smear is a generic analysis to assess the person’s health status.Manual testing of Peripheral blood smear images are difficult,time-consuming and is subject to human intervention and visual error.This method encouraged for researchers to present algorithms and techniques to perform the peripheral blood smear analysis with the help of computer-assisted and decision-making techniques.Existing CAD based methods are lacks in attaining the accurate detection of abnormalities present in the images.In order to mitigate this issue Deep Convolution Neural Network(DCNN)based automatic classification technique is introduced with the classification of eight groups of peripheral blood cells such as basophil,eosinophil,lymphocyte,monocyte,neutrophil,erythroblast,platelet,myocyte,promyocyte and metamyocyte.The proposed DCNN model employs transfer learning approach and additionally it carries three stages such as pre-processing,feature extraction and classification.Initially the pre-processing steps are incorporated to eliminate noisy contents present in the image by using Histogram Equalization(HE).It is enclosed to improve an image contrast.In order to distinguish the dissimilar class and segmentation approach is carried out with the help of Fuzzy C-Means(FCM)model whereas its centroid point optimality method with Slap Swarm based optimization strategy.Moreover some specific set of Gray Level Co-occurrence Matrix(GLCM)features of the segmented images are extracted to augment the performance of proposed detection algorithm.Finally the extracted features are recorded by DCNN and the proposed classifier has the capability to extract their own features.Based on this the diverse set of classes are classified and distinguished from qualitative abnormalities found in the image.

On the Selection of a Composite Material for Two-Wheeler Foot Bracket Failure Prevention through Simulation and Mathematical Modeling

A foot bracket is a metal panel bracket used to mount and support the footrest in two-wheeler systems.It holds the footrest in place while rigidly supporting it.In working conditions,this element has often been observed to fail when specific load-fluctuation conditions are established at its rear end.Appropriate materials therefore need to be identified to overcome such a recurring failure.To address these issues,the present study has been implemented with the specific objective to determine the response of selected Al6061-T6 and Al7075-T6 Hybrid Metal Matrix Composites(HMMC).The results,obtained using the ANSYS Software,show that the selected composites can withstand 636,962 N/m^(2)of maximum stress and 8.88×10^(−6)m of minimum displacement.These results are also compared with relevant mathematical models and it is concluded that the identified material combination provides the required improvement of structural stability that can withstand the load fluctuation on the foot bracket.