The plasma column in a metal inert gas welding process is investigated by optical emission spectroscopy and high-speed imaging. The concentration and repartition of iron vapours are measured and ...correlated with the plasma and electrode geometric configuration. Plasma temperatures and electron densities are also measured for each studied position in the plasma. The temperatures are calculated using two different methods, allowing validation of the local thermodynamic equilibrium state of the plasma. The results show a maximum temperature of 12 500 K in the upper part of the arc, away from the arc axis. The iron concentration reaches a maximum of 0.3% close to the anode and strongly decreases along both the vertical and radial directions.
The plasma thermophysical properties, calculated from this plasma composition, are then discussed regarding the metal transfer mode.
The gas metal arc welding (GMAW) process is strongly influenced by the composition of the shielding gas. In particular, addition of CO2 increases the threshold current for the transition from ...unstable globular to more stable spray transfer mode. We report on the diagnostics-using optical emission spectroscopy-of a GMAW plasma in pure argon and in mixtures of argon, CO2 and N2 while operated in spray and globular transfer modes. The spatially resolved plasma parameters are obtained by applying the Abel transformation to laterally integrated emission data. The Stark widths of some iron lines are used to determine both electron density and temperature, and line intensities yield relative contents of neutral and ionized iron to argon. Our experimental results indicate a temperature drop on the arc axis in the case of spray arc transfer. This drop reduces with addition of N2 and disappears in globular transfer mode when CO2 is added. Despite the temperature increase, the electron density decreases with CO2 concentration. The highest concentration of iron is observed in the plasma column upper part (close to the anode) and for GMAW with CO2. Our results are compared with recently published works where the effect of non-homogeneous metal vapour concentration has been taken into account.
Alzheimer's disease is a chronic neurodegenerative disorder with no curative treatment. The commercially available drugs, which target acetylcholinesterase, are not satisfactory. The aim of this ...study was to investigate the cholinesterase inhibitory activity of Solenostemma argel aerial part. Eight compounds were isolated and identified by NMR: kaempferol-3-O-glucopyranoside (1), kaempferol (2), kaempferol-3-glucopyranosyl($1{\rightarrow}6$)rhamnopyranose (3) p-hydroxybenzoic acid (4), dehydrovomifoliol (5), 14,15-dihydroxypregn-4-ene-3,20-dione (6), 14,15-dihydroxy-pregn-4-ene-3,20-dione-$15{\beta}$-D-glucopyranoside (7) and solargin I (8). Two of them (compounds 2 and 3) could inhibit over 50 % of butyrylcholinesterase activity at $100{\mu}M$. Compound (2) displayed the highest inhibitory effect against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with a slight selectivity towards the latter. Molecular docking studies supported the in vitro results and revealed that (2) had made several hydrogen and ${\pi}-{\pi}$ stacking interactions which could explain the compound potency to inhibit AChE and BChE.
In this paper, a metaheuristic optimized multilayer feed‐forward artificial neural network (ANN) controller is proposed to extract the maximum power from available solar energy for a three-phase ...shunt active power filter (APF) grid connected photovoltaic (PV) system supplying an arc welding machine. Firstly, in order to improve the maximum power point (MPP) delivered by PV arrays and to overcome the drawbacks in the conventional MPPT method under irradiation variation, a hybrid MPPT controller is designed, in which the input parameters include the PV array voltage and current, and the output parameter is the duty cycle of the DC/DC boost converter. The proposed approach abbreviated as ANN-ACO MPPT controller is based on an ant colony optimization (ACO) algorithm which is useful to train the developed ANN and to evolve the connection weights and biases to get the optimal values of duty cycle converter corresponding to the MPP of a PV array. Secondly, aiming to meet the various grid requirements such as power quality improvement, distortion free signals etc., a three-phase shunt APF is utilized, and a direct power control algorithm is designed for distributing the solar energy between the DC-link capacitor, arc welding machine and the AC grid. Finally, the performance of proposed control system is confirmed by simulation tests on a 12.2 kW PV system. Both simulation and experimental results have demonstrated that the deigned ANN-ACO MPPT controller can provide a better MPP tracking with a faster speed and a high robustness with a minimal steady-state oscillation than those obtained with the conventional INC method. Also, with the use of a three-phase shunt APF, all the power fluctuations from the arc welding machine disturbances are damped out and the output active and reactive power become controllable.
This article presents a simple and systematic approach to synthesize a robust adaptive fuzzy fractional-order nonsingular terminal sliding mode controller (AFFO-NTSMC) to improve the output voltage ...tracking control performance of the dc-dc buck converters. The hybrid control method of fractional-order (FO) calculus and NTSMC are combined to create a FO-NTSMC, in which a new FO nonsingular terminal sliding mode surface is established. The idea behind this strategy is the increased flexibility achieved by FO calculation, improving robustness to disturbances and parameters variations provided by the traditional sliding mode controllers as well as finite time convergence properties of the output voltage error to the equilibrium point during the output load changes, simultaneously. In addition, a fuzzy logic system with online adaptive learning algorithm is designed to provide smooth chattering in switching control signal. The stability of the closed-loop system is carefully demonstrated by Lyapunov's theorem. Experimental measurements from a laboratory prototype are presented to demonstrate the effectiveness of the proposed AFFO-NSTSMC algorithm.
•A new Water Quality Index is devised through a DEA-based methodology.•New input variables are defined directly from the observed data.•Water quality can be improved with reference to local water ...source benchmarks.•Water treatment process can be prioritized via slack analysis.•New methodology is applied on 47 dams located in the Tellian region, Algeria.
The present paper aims to develop a new Water Quality Index (WQI) based on Data Envelopment Analysis (DEA). Rather than using subjective weights of a judgmental process as inputs of the DEA model, we propose more objective variables, identified as “optimistic closeness values”, appropriately derived from the observed values of the hydrochemical parameters.
The proposed approach was employed to assess the water quality of 47 dams in Algeria, defined with a dataset of 10 hydrochemical parameters. The results of the DEA-based WQI application revealed that (i) 21.27%, 27.66%, 25.53%, 4.25% and 21.27% of the total dams are categorized as “Poor”, “Marginal”, “Medium”, “Good” and “Excellent” water quality, respectively; (ii) the best water quality is found in “Kissir” and the worst one in “Bougara”; (iii) a priority scale on the hydrochemical parameters can be set for the treatment of water using the notion of slack value.
Collectively, the new methodology has proven its effectiveness not only for categorizing or ranking sites based on water quality but also as an alternative tool to be used to assist decision-makers in allocating funds and managing water resources.
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