A dynamic two-level artificial neural network for estimation of parameters in combined mode conduction-radiation heat transfer in porous medium: An application to handle huge dataset with noise

A dynamic two-level artificial neural network (DTLANN) approach is used for the estimation of parameters in combined mode conduction–radiation heat transfer in a porous medium. Four commonly used neural networks: feed forward, cascade forward, fitnet, and radial basis are used in mapping artificial neural network (ANN), and their performance is compared under noisy big data (10,302 × 1300 matrix size). Governing equations for heat transfer in the porous medium through conduction and radiation modes are solved by finite volume method and discrete transfer method. This numerical model is called a direct model. A large amount of data is generated by using the direct model for different values of extinction coefficient β and convective coupling P₂. These data were divided into different groups (class) based on the temperature difference between the gas and solid phase. In the inverse analysis, a new pair of temperature profiles for the solid and gas phase is taken as input and classified with the help of a pattern net artificial neural network model. On the basis of classification, data from that particular class and its neighbor class are used for training the mapping ANN model. After the training of the mapping ANN model, corresponding values of β and P₂ are obtained as output for any new input. This DTLANN model has a high regression coefficient (R) of .99131 and can predict highly accurate values of parameters under a huge dataset with noise, within much less CPU time.     

Analysis of equilibrium CO2 solubility in aqueous APDA and its potential blends with AMP/MDEA for postcombustion CO2 capture

The utility of polyamine-based solvent-activators for the possible application in postcombustion CO₂ capture technology has drawn considerable attention recently owing to its higher loading capacity as well as superior kinetics. The current work involves a comprehensive experimental cum theoretical investigation on the equilibrium solubility of CO₂ pertaining to aqueous N-(3-aminopropyl)-1,3-propanediamine and its blends with N-methyldiethanolamine and 2-amino-2-methyl-1-propanol. The analysis was conducted within the operating temperature and CO₂ partial pressure range of 303.2-323.2 K and 2-200 kPa, respectively. Two different mathematical models based on nonrigorous approaches such as equilibrium based modified Kent-Eisenberg (KE) model and a multilayer feedforward neural network model have been developed to correlate the CO₂ solubility data over a wide range of experimental conditions. Both the model predictions are well-validated with the experimental results. The reaction scheme as well as the prevalence of important reaction products was further confirmed with qualitative ¹³C NMR as well as ATR-FTIR analysis. Apart from these some of the important thermally induced transport properties viz, density, viscosity, and surface tension of the aqueous single and blended systems were measured and correlated with various consistent empirical models such as Redlich-Kister and Grunberg-Nissan model while surface tension data are modeled using temperature-based multiple linear regression technique.     

Measurement of yarn hairiness by digital image processing

In their effort to measure yarn hairiness at high speed, the commercially available yarn hairiness testers resort to indirect techniques. Measurement of true length of all hairs can only be done by observing the yarn under a microscope and obtaining a trace of hairs. An attempt was made in this work to automate this task using digital image processing. The challenges were two-fold. The first was development of an algorithm capable of analysing yarn images taken under varying lighting conditions and varying yarn positions. The second was determination of minimum requirement of the image-capturing instrument. Both of these have been reported in this work. A new hairiness index has been proposed and suggested as a better indicator of hairiness than the traditional definition.     

Enhanced Channel Division Method for Estimation of Discharge in Meandering Compound Channel

Accurate prediction of shear force distribution along the boundary in open channels is a key to the solution of numerous hydraulic problems. The problem becomes more complicated for meandering compound channels. A model is developed for predicting the percentage of shear force at the floodplain (%S_fp) of two-stage meandering channels using gene-expression programming (GEP) by considering five dimensionless parameters viz. the width ratio, relative depth, sinuosity, bed slope, and meander belt width ratio as the inputs in the model. Basing on the %S_fp, the apparent shear force along the division lines of separation in compound channels is selected for discharge calculation using the conventional channel division methods. An Enhanced Channel Division Method (ECDM) is introduced to calculate discharge by assuming interface line at main channel and floodplain junction. A modified variable-inclined (MVI) interface is suggested having zero apparent shear determined from flow contribution in the main channel and floodplain. The MVI interface is further used to calculate discharge in the meandering compound channels. Performance of the GEP model is tested against other analytical methods of calculating %S_fp. Error between the observed and calculated discharges using the MVI interface is found to be the minimum when compared to other interface methods. The enhance channel division method is successfully applied for validating the two available overbank discharge values for the river Baitarani at Anandapur (drainage area of 8570 sq. km), giving the minimum errors of 0.31% and 1.02% for flow depths of 7.5 m and 8.63 m, respectively.

     

Arsenic removal from groundwater and its safe containment in a rural environment: validation of a sustainable approach

Of all the naturally occurring groundwater contaminants, arsenic is by far the most toxic. Any large-scale treatment strategy to remove arsenic from groundwater must take into consideration safe containment of the arsenic removed with no adverse ecological impact. Currently, 175 well-head community-based arsenic removal units are in operation in remote villages of the Indian subcontinent. Approximately 150,000 villagers collect arsenic-safe potable water everyday from these units. The continued safe operation of these units has amply demonstrated that use of regenerable arsenic-selective adsorbents is quite viable in remote locations. Upon exhaustion, the adsorbents are regenerated in a central facility by a few trained villagers and reused. The process of regeneration reduces the volume of disposable arsenic-laden solids by nearly 2 orders of magnitude. Finally, the arsenic-laden solids are contained on well-aerated coarse-sand filters with minimum arsenic leaching. This disposal technique is scientifically more appropriate than dumping arsenic-loaded adsorbents in the reducing environment of landfills as currently practiced in developed countries including the United States.     

Spatial variability of soil hydraulic and physical properties in erosive sloping agricultural fields

It is essential to minimize soil quality degradation in sloping agricultural fields through stabilization and improvement of soil hydraulic properties using sustainable soil management. This study aimed to analyze the impact of different tillage practices, including conventional tillage (CT), minimum tillage (MT), and zero tillage (ZT), on soil hydraulic conductivity in a sloping agricultural field under maize–wheat rotation. The results showed that the highest runoff volume (257.40 m³), runoff coefficient (42.84%), and soil loss (11.3 t) were observed when the CT treatment was applied. In contrast, the lowest runoff volume (67.95 m³), runoff coefficient (11.35%), and soil loss (1.05 t) were observed when the ZT treatment was adopted. The soil organic carbon and aggregate mean weight diameter were found to be significantly greater (with mean values of 0.79% and 1.19 mm, respectively) with the ZT treatment than with the CT treatment. With the tilled treatments (CT and MT), substantial changes in the saturated soil hydraulic conductivity (k_s), near-saturated soil hydraulic conductivity (k), and water-conducting porosity (ε) were observed between two crop seasons. These three soil parameters were significantly higher in the period after maize harvesting than in the wheat growing period. In contrast, no significant difference in these soil parameters was found when the untilled treatment (ZT) was carried out. With regard to the slope positions, k_s, k, and ε showed different behaviors under different treatments. The toe slope position showed significantly lower k_s and ε values than the summit and middle slope positions. Of the evaluated tillage practices, ZT was found to be the most promising means to improve the soil hydro-physical properties and effectively reduce surface runoff and soil erosion.     

On Predictability of Groundwater Level in Shallow Wells Using Satellite Observations

Management of groundwater resources needs continuous and efficient monitoring networks. Sparsity of in situ measurements both spatially and temporally creates hindrance in framing groundwater management policies. Remotely sensed data can be a possible alternative. GRACE satellites can trace groundwater changes globally. Moreover, gridded rainfall (RF) and soil moisture (SM) data can shed some light on the hydrologic system. The present study attempts to use GRACE, RF and SM data at a local scale to predict groundwater level. Ground referencing of satellite data were done by using three machine learning techniques- Support Vector Regression (SVR), Random Forest Method (RFM) and Gradient Boosting Mechanism (GBM). The performance of the developed methodology was tested on a part of the Indo-Gangetic basin. The analyses were carried out for nine GRACE pixels to identify relationship between individual well measurements and satellite-derived data. These nine pixels are classified on the basis of presence or absence of hydrological features. Pixels with the presence of perennial streams showed reasonably good results. However, pixels with wells located mostly near the stream gave relatively poorer predictions. These results help in identifying wells which can reasonably represent the regional shallow groundwater dynamics.     

Trimming process and temperature variation in second-order bandgap voltage reference circuits

This paper presents the design and experimental performance of a second-order bandgap voltage reference integrated circuit (IC). Experimentally observed nominal reference voltage at room temperature is 1.150 V with best temperature performance of 3 mV variation over −40 to 120 °C. A 5-bit resistor trimming is used to compensate the variation of reference voltage due to layout mismatch and process variation. A trimming methodology is described in this paper to optimize both the temperature performance and reduce the variation of the room temperature voltage over different samples. Even with best temperature performance trim-code, the absolute variation in reference voltage over 20 samples is 85 mV which is trimmed to ±11 mV (1.3%) using the proposed trimming methodology. The second-order bandgap circuit is designed in a 0.5 μm BiCMOS process with less than 50 μA current consumption.     

Hybrid crosstalk aware Q-Factor analysis for selection of optical virtual private network connection

The presence of physical layer impairments (PLIs) in high-speed optical virtual private network (OVPN) over wavelength-division multiplexing/ dense-wavelength division multiplexing network degrades the connection quality (CQ). The quality can be numerically expressed as the quality factor (Q-Factor) of the connection. The CQ can be further affected by the increasing demand of connections and data speed. It is important to have an efficient OVPN control manager (OVPNCM) to maintain the CQ. OVPNCM can ensure better quality of transmission to the OVPN clients. Traditional routing and wavelength assignment (RWA) algorithms have less regards to the PLIs and cannot provide guaranteed OVPN connection (OVPNC) quality. In order to achieve a guaranteed CQ, we proposed a wavelength assignment (WA) scheme and a hybrid crosstalk model based on linear in-band and nonlinear four-wave mixing crosstalk. The performance of the proposed WA scheme with the hybrid crosstalk model is demonstrated. The results show that the proposed hybrid crosstalk model with WA scheme not only provides a guaranteed OVPNC, but also improves the OVPN performance in terms of blocking probability.     

Design of a Right-Handed Circularly Polarized Printed Antenna for Vehicular Communication

Wireless Personal Communications - In this paper, the authors presented a new fractal microstrip patch antenna for Dedicated Short Range Communication (DSRC) (5.850–5.925 GHz) (IEEE 802.11p)...