Experimental and FE analysis of submerged arc weld induced residual stress and angular deformation of single and double sided fillet welded joint

Submerged arc welding is well-known for its very high deposition rate and thus the capability to join very high thickness metal pieces in large structural applications. Fillet joints are mostly used in structural applications which can be extensively seen in shipbuilding, bridge construction, house buildings, automobile or any other large structures. Thermal stresses generates in a fusion welded joint due to high temperature gradient, which is the cause of the residual stresses upon cooling followed by the angular deformation and failure of the welded structure. As an effect of the thermal gradient, the induced longitudinal, transverse residual stress & angular distortion can vary in single sided and double sided submerged arc welded fillet joints, during designing & manufacturing welded structures which should be taken into account. The main objective of this paper is to quantify the amount of residual stresses and angular deformation in a fillet welding joint. An elasto-plastic thermomechanical model has been developed for predicting residual stresses. A comparison of the residual stress and angular deformation between single and double sided fillet weld joint has been made. The simulation results reveal that the amount of residual stress present in the single sided fillet weld is more and unbalanced in both side of the center of weld line compared to the double sided fillet weld and the predicted results have been matched with the experiments as well as published literatures.     

Isolation and identification of phosphate‐solubilizing microorganisms and distribution of orthophosphate in different seasons from sewage‐fed East Kolkata Wetland

This study focused on isolation and identification of possible phosphate‐solubilizing bacteria (PSB ) from the sewage‐fed East Kolkata Wetland (EKWL ), a prospective water resource for pisciculture. In addition, different limnological parameters have been correlated with orthophosphate and seasonal variations. PSB have been isolated in Pikovskaya medium and identified morphologically and biochemically and finally analysed by 16S rDNA gene sequence. Limnological studies involving temperature (potentiometric), pH (potentiometric), dissolved oxygen (iodometric), ammonia‐nitrogen (spectrophotometric) and orthophosphate (spectrophotometric) concentrations were conducted. The results of this study established the presence of Bacillus megaterium , a potential PSB in EKWL . The activity of B. megaterium is also supported by the seasonal orthophosphate variations. The changes in concentration of other limnological parameters were also prominent. The water quality parameters of temperature (r  = 0.886), dissolved oxygen (r  = 0.729) and ammonia‐nitrogen (r  = 0.396) concentrations exhibited a positive correlation with orthophosphate and a negative correlation with pH (r  = ?0.699). The B. megaterium obtained in this study, exhibited a significant alteration in regard to orthophosphate content and relationships with other factors. Further experiment on the soluble phosphorus solubilization potential of B. megaterium revealed the biological availability of phosphorus was increased by threefold after 120 hr of incubation, with the decreasing pH value, although the phytase activity was 0.419 U/ml. PSB have a vital function in plant nutrition in supplying phosphate, essential nutrients and its uptake results in appropriate functioning and metabolism of different aquatic plants and organisms. PSB are competent biofertilizer to amplify aquaculture production for sustainable development.     

Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Signal Strengths

Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points. Traditional grid-based radio frequency (RF) fingerprinting (GRFF) suffers from two drawbacks. First it requires costly and non-efficient data collection and updating procedure; secondly the method goes through time-consuming data pre-processing before it outputs user position. This paper proposes Cluster-based RF Fingerprinting (CRFF) to overcome these limitations by using modified Minimization of Drive Tests data which can be autonomously collected by cellular operators from their subscribers. The effect of environmental changes and device variation on positioning accuracy has been carried out. Experimental results show that even under these variations CRFF can improve positioning accuracy by 15.46 and 22.30% in 95 percentile of positioning error as compared to that of GRFF and K-nearest neighbour methods respectively.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

A junctionless tunnel field effect transistor with low subthreshold slope

we demonstrate the design of a triple gate n-channel junctionless transistor that we call a junctionless tunnel field effect transistor (JLTFET). The JLTFET is a heavily doped junctionless transistor which uses the concept of tunneling, by narrowing the barrier between source and channel of the device, to turn the device ON and OFF. Simulation shows significant improvement compared to simple junctionless field effect transistor both in I _ON/I _OFF ratio and subthreshold slope. Here, junctionless tunnel field effect transistors with high-k dielectric and low-k spacers are demonstrated through simulation and shows an ON-current of 0.25 mA/μm for the gate voltage of 2 V and an OFF current of 3 pA/μm (neglecting gate leakage). In addition, our device shows optimized performance with high I _ON/I _OFF (～10⁹). Moreover, a subthreshold slope of 47 mV/decade is obtained for a 50 nm gate length of simulated JLTFET at room temperature which indicates that JLTFET is a promising candidate for switching performance.     

Dual material gate junctionless tunnel field effect transistor

This paper proposes a junctionless tunnel field effect transistor (JLTFET) with dual material gate (DMG) structure and the performance was studied on the basis of energy band profile modulation. The two-dimensional simulation was carried out to show the effect of conduction band minima on the abruptness of transition between the ON and OFF states, which results in low subthreshold slope (SS). Appropriate selection of work function for source and drain side gate metal of a double metal gate JLTFET can also significantly reduce the subthreshold slope (SS), OFF state leakage and hence gives improved I _ON/I _OFF.     

A neural-network-based space-vector PWM controller for athree-level voltage-fed inverter induction motor drive

A neural-network-based implementation of space-vector modulation (SVM) of a three-level voltage-fed inverter is proposed in this paper that fully covers the linear undermodulation region. A neural network has the advantage of very fast implementation of an SVM algorithm, particularly when a dedicated application-specific IC chip is used instead of a digital signal processor (DSP). A three-level inverter has a large number of switching states compared to a two-level inverter and, therefore, the SVM algorithm to be implemented in a neural network is considerably more complex. In the proposed scheme, a three-layer feedforward neural network receives the command voltage and angle information at the input and generates symmetrical pulsewidth modulation waves for the three phases with the help of a single timer and simple logic circuits. The artificial-neural-network (ANN)-based modulator distributes switching states such that neutral-point voltage is balanced in an open-loop manner. The frequency and voltage can be varied from zero to full value in the whole undermodulation range. A simulated DSP-based modulator generates the data which are used to train the network by a backpropagation algorithm in the MATLAB Neural Network Toolbox. The performance of an open-loop volts/Hz speed-controlled induction motor drive has been evaluated with the ANN-based modulator and compared with that of a conventional DSP-based modulator, and shows excellent performance. The modulator can be easily applied to a vector-controlled drive, and its performance can be extended to the overmodulation region     

Design and performance study of phase‐locked loop using fractional‐order loop filter

The present work reports the realization of an analog fractional‐order phase‐locked loop (FPLL) using a fractional capacitor. The expressions for bandwidth, capture range, and lock range of the FPLL have been derived analytically and then compared with the experimental observations using LM565 IC. It has been observed that bandwidth and capture range can be extended by using FPLL. It has also been found that FPLL can provide faster response and lower phase error at the time of switching compared to its integer‐order counterpart. Copyright © 2014 John Wiley & Sons, Ltd.     

High-Valent Iron-Oxo and -Nitrido Complexes: Bonding and Reactivity

Multiple-bonded iron-oxo and -nitrido species have been identified or proposed as key intermediates in a range of important chemical transformations. The reported model complexes feature various coordination geometries and distinct electronic structures, and therefore exhibit diverse reactivity. The present contribution highlights the synergy from both experimental and theoretical standpoints to elucidate their different bonding situations and delineate their common mechanistic features in hydrogen-atom abstraction processes. Our analysis reveals that a radical centered on the abstracting atom E (E=O, N), which is generated via homolysis of covalent Fe−E bonds upon approaching the transition state, is an intrinsic C−H cleaving agent. The iron-oxo species is predicted to be more reactive than its nitride congener, in general, because the O−H bond formed in the H-atom transfer process is often stronger than the corresponding N−H bond.     

Efficient Host-Guest Complexation of a Bisporphyrin Host with Electron Deficient Guests: Synthesis,Structure, and Photoinduced Electron Transfer

The encapsulation of 1,8-naphthalic anhydride (NAN), 9-dicyanomethylenefluorene (9-DCF), acenaphthenequinone (ANQ), and 4-chloro-7-nitrobenzofurazan (NBD-Cl) by diethylpyrrole-bridged bisporphyrin (H₄DEP) and its dizinc(II) analogue (Zn₂DEP) are employed to investigate the structural and spectroscopic changes within the bisporphyrin cavity upon substrate binding. Synthesis and X-ray structures of all four encapsulated host-guest complexes (H₄DEP⋅NAN, H₄DEP⋅9-DCF, Zn₂DEP⋅ANQ, and Zn₂DEP⋅NBD-Cl) are reported here. The binding constant calculations show strong 1 : 1 binding between the hosts (H₄DEP and Zn₂DEP) and the guests (NAN/9-DCF/ANQ/NBD-Cl). ¹H-NMR spectra also support the retention of the host-guest assemblies in solution. Negative and positive shifts of the reduction and oxidation potentials, respectively, indicate that it is difficult to reduce/oxidize the encapsulated complexes. The emission intensities of the bisporphyrins (H₄DEP and Zn₂DEP) are substantially quenched in all the complexes, owing to photoinduced electron transfer from the excited state of the bisporphyrins to guest molecules. All the experimental evidence is further substantiated by DFT calculations. Such an efficient electron transfer is only possible when the donor and the acceptor moieties are in close propinquity to each other, which eventually lowers the reorganization energy.