Estimating Regional Evapotranspiration Using Remote Sensing: Application to Sone Low Level Canal System, India

Remote sensing-derived spectral data have been used in the past to partition net radiation, soil heat, and sensible heat fluxes for estimating latent heat flux as a residual of surface energy balance, and thus regional evapotranspiration. Attempts to provide a simplified procedure for estimating sensible heat flux at a regional scale have not been successful because of the relatively strong dependence of the heat transfer coefficient on the land–atmosphere boundary condition. This paper presents a remote sensing-based procedure to estimate the sensible heat flux incorporating the local meteorological conditions, and in turn to determine the regional evapotranspiration. The model utilizes satellite-derived surface albedo, surface temperature, and leaf area index along with a very few agrometeorological data as inputs. The proposed procedure has been tested on a part of the Western Yamuna Canal system, India, and is found to be computationally simple as well as stable. For a well-watered wheat crop, the average evapotranspiration by the proposed model is estimated to be 2.05?mm?d?1 on January 30, 1996, whereas it is estimated to be 1.89?mm?d?1 using the Penman-Monteith equation, indicating a difference of less than 10%. The model is subjected to sensitivity analysis for uncertainties in the observed wind velocity and the computed leaf area index (by ±20%) to estimate sensible heat flux. Results reveal that the percentage change in mean sensible heat flux for the image is less than 5% in all cases, thus indicating the acceptability of the model against the uncertainties. Further, the model has been applied to three sets of Landsat-TM data covering the Sone Low Level Canal system, India, to demonstrate its usefulness in evaluating water delivery performance.     

Mathematical Morphology-Based Artificial Technique for Renewable Power Application

This paper suggests a combined novel control strategy for DFIG based wind power systems (WPS) under both nonlinear and unbalanced load conditions. The combined control approach is designed by coordinating the machine side converter (MSC) and the load side converter (LSC) control approaches. The proposed MSC control approach is designed by using a model predictive control (MPC) approach to generate appropriate real and reactive power. The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation. It shows its superiority by eliminating the requirement of transformation, switching table, and the PWM techniques. The proposed MSC reduces the cost, complexity, and computational burden of the WPS. On the other hand, the LSC control approach is designed by using a mathematical morphological technique (MMT) for appropriate DC component extraction. Due to the appropriate DC-component extraction, the WPS can compensate the harmonics during both steady and dynamic states. Further, the LSC controller also provides active power filter operation even under the shutdown of WPS condition. To verify the applicability of coordinated control operation, the WPS-based microgrid system is tested under various test conditions. The proposed WPS is designed by using a MATLAB/Simulink software.     

Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

This paper presents a combined control and modulation technique to enhance the power quality (PQ) and power reliability (PR) of a hybrid energy system (HES) through a single-phase 11-level cascaded H-bridge inverter (11-CHBI). The controller and inverter specifically regulate the HES and meet the load demand. To track optimum power, a Modified Perturb and Observe (MP&O) technique is used for HES. Ultra-capacitor (UCAP) based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell conditions. For an improved PQ and PR, a two-way current control strategy such as the main controller (MC) and auxiliary controller (AC) is suggested for the 11-CHBI operation. MC is used to regulate the active current component through the fuzzy controller (FC), and AC is used to regulate the dc-link voltage of CHBI through a neural network-based PI controller (ANN-PI). By tracking the reference signals from MC and AC, a novel hybrid pulse width modulation (HPWM) technique is proposed for the 11-CHBI operation. To justify and analyze the MATLAB/Simulink software-based designed model, the robust controller performance is tested through numerous steady-state and dynamic state case studies.     

Size and distribution: a comparison of XRD, SAXS and SANS study of II-VI semiconductor nanocrystals

The uniqueness of size dependent functional properties of II-VI semiconductor nanocrystals have led to the development of various techniques for determination of shape, size and distributions, although the accurate measurements of the particle sizes has always been a fundamental task in nanoscience and even become more crucial with the discovery of quantum confinement effect. A comparison of the well established techniques X-ray diffraction (XRD), small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS) with an emphasis on size and distribution of the prepared samples are reported in order to elaborate more precise techniques for the analysis of particles sizes. Modified Scherrer formula for spherical particles has been used to calculate the particle sizes from XRD spectra. Analysis of SAXS data has been reported using Guinier model. Small angle neutron scattering measurements has been performed for ZnO nanocrystals and the scattering data obtained is simulated for polydisperse sphere. The bare ZnO, ZnS and CdS and doped with Mn2+ systems are taken within the framework of our discussion. These materials were synthesized by chemical precipitation route and found to have size distribution from 2 to 6 nm for spherical particles. Sizes determined from various techniques are in good agreement with each other however small angle scattering technique is more reliable than XRD to determine the sizes of the nanoparticles.     

Bioactivities of açaí (Euterpe precatoria Mart.) fruit pulp,superior antioxidant and anti-inflammatory properties to Euterpe oleracea Mart.

There are two predominant palm tree species producing edible fruit known as “açaí” found widely dispersed through the Amazon: Euterpe oleracea Mart. and Euterpe precatoria Mart. They differ from each other in terms of how the plants grow and their phytochemical composition. E. oleracea (EO) has received considerable attention as a “super fruit” because of its high antioxidant capacity, while studies on E. precatoria (EP) remain rare. In this study, the antioxidant and anti-inflammatory activities of EP fruit pulps were evaluated by different assays including a series of oxygen radical absorbance capacity (ORAC) based assays, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, the cell-based antioxidant protection in erythrocyte (CAP-e) assay, as well as the nuclear factor-kappa B (NF-κB) secreted embryonic alkaline phosphatase (SEAP) assay. Total phenolics were also measured as an indication of the total phenol content. For comparative purposes, the EO fruit pulp was included. The antioxidant capacity of the EP fruit pulp was determined to be superior to the EO fruit pulp in every chemical based assay. In the cell-based CAP-e assay, the EP fruit pulp showed a dose-dependent inhibition against oxidative damage with an IC₅₀ of 0.167 g/l. In the SEAP reporter assay, the EP fruit pulp polyphenol-rich extracts inhibited lipopolysaccharide (LPS)-induced NF-κB activation by 23% (p < 0.05) at 20 μg/ml, whereas the extract of the EO fruit pulp did not show a significant inhibitory effect at comparable doses. In addition, carotenoids were quantified for the first time in EP, since EP has high scavenging capacity against singlet oxygen.     

Modeling of multiple characteristics of an arc weld joint

Process parameters modeling have always been one of the key aspects in development of an adaptive control of arc welding process. The welding process parameters are inherently nonlinear, time-delayed, and interdependent, and their on-time adjustment highly influences a sound weld bead formation and process monitoring. During the welding process, parameters control is the primary goal to leads a quality welding. Moreover, the final weld joint behavior, i.e., residual stress, welding strength, and micro-crack formation are generally observed after cooling of the weld product. Thus, it has always been a difficult task to control mechanical properties of a final weld joint. To obtain the best mechanical properties, the final weld joint characteristics needed to be controlled and predicted during the process itself by precise adjustment of the process parameters. The paper presents a neuro-fuzzy modeling approach to provide adaptive control for the automatic process parameter adjustment. Three input parameters wire feed speed, welding gap, and torch speed are modeled with welding current output, providing control over weld bead formation during the welding. The same input process parameters are also modeled to predict final weld joint characteristics, i.e., dilution ratio, hardness of weld bead, hardness of fused zone, and bead width. In order to ascertain the effectiveness of the neuro-fuzzy modeling approach, multiple regression models were also developed to compare the performances.     

Development of a re‐aeration equation for the simulation of dissolved oxygen in degraded streams

Discharge of domestic and industrial wastewater into the water bodies is the prime source of degradation of the freshwater ecosystem. Re‐aeration of the river allows the rejuvenation of river water quality by absorbing oxygen from the atmosphere at the air‐water interface. An accurate estimation of the re‐aeration coefficient helps to determine the assimilative capacity of streams and wastewater management also. This paper aims to develop the re‐aeration equation and its validation by modelling dissolved oxygen of the Yamuna River. Predictive re‐aeration equations are used to identify their applicability to the study area and the new equation is designed using multivariate statistical regression techniques. QUAL2Kw model is used to validate the equation by modelling dissolved oxygen. Results indicate that the developed equation performs better than the predictive re‐aeration equations for the prediction of water quality.     

Influence of organic polymers as capping agent on structural and optical properties of ZnS:Mn2+ and CdS nanocrystals

We have synthesized the luminescent ZnS:Mn2+ and bare CdS nanocrystals by employing polyvinyl alcohol (PVA), citric acid (CA) and biotin as organic capping agents by chemical co-precipitation route. The synthesized materials were characterized by X-ray diffraction, small angle X-ray scattering and transmission electron microscopy for the structural analysis, while UV-Visible spectroscopy and photoluminescence (PL) for optical properties. The results show that all the three organic polymers have the same effect and are capable of controlling the growth of the nanoclusters. From UV-Visible absorption spectra, it was observed that different capping agents do not affect the band gap of ZnS:Mn2+ system as well, while capping effect clearly observed on PL properties of ZnS:Mn2+ system. We have observed a novel result that capping with biotin show excellent photoluminescence as compared to capping of PVA and CA on ZnS:Mn2+ -systems. On the other hand, the annealing of these systems leads to degradation of luminescence intensity.     

Numerical Study of Solid State Hydrogen Storage System with Finned Tube Heat Exchanger

Abstract

Absorption of hydrogen gas inside the metal hydride (MH)-based hydrogen storage system generates significant amount of heat. This heat must be removed rapidly to improve the performance of the system which can be accomplished by embedding a heat exchanger inside the MH bed. In this article, a tubular shape MH system, equipped with a heat exchanger consisting of copper tube and pin fin is presented. A detailed 3D mathematical model is developed using COMSOL Multiphysics 4.3b for the numerical study of absorption and desorption processes inside the storage system. Impact of various operating and geometric parameters on the charging time of the storage system has been examined. It is observed that these geometric and operating parameters influence the charging time of the storage system. In the last, the impact of heat exchanger material on the performance of the storage system is explored. It is found that aluminum made heat exchanger is the best for the storage systems. The absorption process is accomplished in 1152?s at the operating parameters of 15?bar, 298 K, and 6.75 lit/min. This numerical work suggests that the efficient design of storage system is very important for rapid absorption and desorption of hydrogen.     

A novel sensorless current shaping control approach for SVPWM inverter with voltage disturbance rejection in a dc grid–based wind power generation system

A novel sensorless current shaping (CS) control strategy is proposed to avail better power quality (PQ) of a dc grid–based wind power generation system (WPGS) used on a poultry farm by generating an appropriate reference current for space vector pulse width modulation (SVPWM) inverter. The proposed CS strategy also offers adequate control for parallel operation of multiple generators and inverter applications, without requiring voltage and frequency synchronization. Further, to control the poultry farm–based WPGS, a two‐stage control loop is implemented such as energy flow control loop (EFCL) and harmonic control loop (HCL). The first loop is used to regulate the power flow, and the second loop is used to compensate harmonics. A mathematical current decomposition technique is suggested for an appropriate resistance emulation to realize a better power flow, higher harmonic rejection, and better inverter operation. In this planned approach for attaining constant wind speed, an electric ventilation fan in the poultry farm is used. A combined hybrid dc and ac grid approaches are suggested for facilitating variable load integration in a poultry farm–based microgrid system. Moreover, for achieving better power management during the islanded mode of operation, the battery energy storage (BES) device is integrated with the dc grid through a bidirectional converter. The proposed WPGS design and control approach has been simulated through MATLAB/Simulink software under various test conditions, to demonstrate the operational capability, to achieve better PQ, and to increase the flexibility and reliability in the microgrid operation.