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▶ The highest factors interaction effects exists between the pressure and salt concentration. ▶ The feed flow rate has the smallest non-linear effect on the RO performance index. ▶ ...The effect of pressure is more significant at higher feed temperatures. ▶ The effect of the feed temperature is higher at higher operating pressures. ▶ The optimal conditions offered by ANN are better than those given by RSM.
Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of reverse osmosis (RO) desalination process. Sodium chloride aqueous solutions were employed as model solutions for a RO pilot plant applying polyamide thin film composite membrane, in spiral wound configuration. The input variables were sodium chloride concentration in feed solution, C, feed temperature, T, feed flow-rate, Q, and operating hydrostatic pressure, P. The RO performance index, which is defined as the salt rejection factor times the permeate flux, has been considered as response. Both RSM and ANN models have been developed based on experimental designs. Two empirical polynomial RSM models valid for different ranges of feed salt concentrations were performed. In contrast, the developed ANN model was valid over the whole range of feed salt concentration demonstrating its ability to overcome the limitation of the quadratic polynomial model obtained by RSM and to solve non-linear problems. Analysis of variance (ANOVA) has been employed to test the significance of response surface polynomials and ANN model. To test the significance of ANN model, the estimation of the degree of freedom due to residuals has been detailed. Finally, both modeling methodologies RSM and ANN were compared in terms of predictive abilities by plotting the generalization graphs. The optimum operating conditions were determined by Monte Carlo simulations considering: (i) the four input variables, (ii) for typical brackish water with a fixed concentration of 6g/L and (iii) for typical seawater with a fixed concentration of 30g/L. Under the obtained optimal conditions maximum RO performance indexes have been achieved experimentally.
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► Desalination by air gap membrane distillation and artificial neural network modeling. ► Study of interaction between air gap membrane distillation parameters. ► Air gap thickness, ...condensation temperature, feed inlet temperature, and feed flow rate are the input variables. ► Optimization of air gap membrane distillation process using Monte Carlo stochastic method.
An experimental based artificial neural network (ANN) model is constructed to describe the performance of air gap membrane distillation process for different operating conditions. The air gap thickness, the condensation temperature, the feed inlet temperature, and the feed flow rate of salt aqueous solutions are the input variables of this process, whereas the response is the performance index, which takes into consideration both the permeate flux and the salt rejection factor. The neural network approach was found to be capable for modeling accurately this membrane distillation configuration. The overall agreement between the ANN predictions and experimental data was very good showing a correlation coefficient of 0.992. To test the statistical significance of the developed ANN model the analysis of variance (ANOVA) has been employed. According to ANOVA test, the ANN model is found to be statistically valid and can be used for the prediction of the performance index. Finally, the predictive abilities of the ANN model were ascertained by plotting the 3D generalization graphs. The optimum operating condition was determined by Monte Carlo stochastic method and the obtained optimal conditions are 3.0mm air gap thickness, 13.9°C condensation temperature, 71°C feed inlet temperature and 205L/h feed flow rate with a maximum experimental performance index of 51.075kg/m2h and a residual error less than 1%.
Sweeping gas membrane distillation process (SGMD) has been used for desalination and its performance index, defined as the product of the distillate flux and the salt rejection factor, has been ...modeled using artificial neural network (ANN) methodology. A feed-forward ANN has been developed for prediction of the performance index based on a set of 53 different experimental SGMD tests. A feed solution of 30g/L sodium chloride was used in all experiments and the salt rejection factors were found to be greater than 99.4%. The individual and interaction effects of the input variables, namely the feed inlet temperature, the feed flow rate or the feed circulation velocity, and the air flow rate or the air circulation velocity, on the SGMD performance index have been investigated. The optimum point was determined by means of Monte Carlo simulation. The obtained optimal conditions were a feed inlet temperature of 69°C, an air flow rate of 34.5L/min (i.e. 2.02m/s air circulation velocity) and a feed flow rate of 160L/h (i.e. 0.155m/s liquid circulation velocity). Under these operating conditions a performance index of 1.493×10−3kg/m2.s has been achieved experimentally being the maximal SGMD performance index obtained inside the region of experimentation.
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► Sweeping gas membrane distillation is modeled and optimized by artificial neural network. ► The input parameters are the feed temperature, the feed flow rate and the air flow rate. ► The response is the sweeping gas membrane distillation performance index. ► Study of interaction between Sweeping Gas Membrane Distillation parameters. ► The optimal response determined by Monte Carlo simulation was confirmed experimentally.
Response surface methodology has been applied for modeling and optimization of air gap membrane distillation process used in desalination. Regression models have been developed to predict the ...performance index and the specific performance index that takes into consideration the energy consumption as function of different variables. The developed models have been statistically validated by analysis of variance. The rejection factors were found to be greater than 99.9%. Two optimal operating conditions have been determined for each response. For the performance index the optimal solution was a cooling inlet temperature of 13.9°C, a feed inlet temperature of 71°C and a feed flow rate of 183L/h. Under these conditions the experimental performance index, 47.189kg/m2.h, was found to be the greatest value among all performed experiments. For the specific performance index, the optimal solution was also 13.9°C cooling inlet temperature, 59°C feed inlet temperature and 205L/h feed flow rate. When applying these last optimum conditions, the obtained experimental specific performance index, 188.7kg/kWh, was also found to be the highest value. This corresponds to a specific energy consumption of 5.3kWh/m3. In all cases, the experimental results are in good agreement with the predicted ones by the developed models.
Performance index and specific performance index in AGMD Display omitted
► Air gap membrane distillation process is optimized by response surface methodology. ► Regression models are developed to predict the specific performance index. ► The optimal responses determined by Monte Carlo method are confirmed experimentally. ► Distilled water is produced from 30g/L salt aqueous solution with 5.3kWh/m3.
The nonlinear relationship between the input process parameters and in-flight particle characteristics of the atmospheric plasma spray (APS) is of paramount importance for coating properties design ...and quality. It is also known that the ageing of torch electrodes affects this relationship. In recent years, machine learning algorithms have proven to be able to take into account such complex nonlinear interactions. This work illustrates the application of ensemble methods to predict the in-flight particle temperature and velocity during an APS process considering torch electrodes ageing. Experiments were performed to record simultaneously the input process parameters, the in-flight powder particle characteristics and the electrodes usage time. Random Forest (RF) and Gradient Boosting (GB) were used to rank and select the features for the APS process data recorded as the electrodes aged and the corresponding predictive models were compared. The time series aspect of the multivariate APS in-flight particle characteristics data is explored. Two strategies of time series embedding are considered. The first one simply embeds the attributes and the targets from the previous
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time segments considered without any modification; whereas the second strategy first performs differencing to make the time series stationary before embedding. For the present application, RF is found to be more suitable than GB since RF can predict both the in-flight particle velocity and temperature simultaneously, properly considering the interactions between the two targets. On the other hand, GB can only predict these two targets one at a time. The superior performance of both embedded predictive models and the feature rankings of them suggest that it is better to consider the APS data as time series for the in-flight particle characteristic prediction. In particular, it is demonstrated that it is advantageous to first make the time series stationary using the traditional differencing technique, even when modeling using RF.
Frequent premature ventricular contractions (PVCs) associated left ventricular systolic dysfunction (LVSD) is a well-known clinical scenario and numerous predictors for cardiomyopathy (CMP) ...development have been already thoroughly described. It may present as a "pure" form of dissynchrony-induced cardiomyopathy or it may be an aggravating component of a multifactorial structural heart disease. However, the precise risk to develop PVC-induced CMP (which would allow for tailored-patient monitoring and/or early treatment) and the degree of CMP reversibility after PVC suppression/elimination (which may permit appropriate candidate selection for therapy) are unclear. Moreover, there is limited data regarding the time course of CMP development and resolution after arrhythmia suppression. Even less known are the other components of PVC-induced CMP, such as right ventricular (RV) and atrial myopathies. This review targets to synthetize the most recent information in this regard and bring a deeper understanding of this heart failure scenario. The mechanisms, time course (both in experimental models and clinical experiences) and predictors of reverse-remodelling after arrhythmia suppression are described. The novel experience hereby presented may aid everyday clinical practice, promoting a new paradigm involving more complex, multi-level and multi-modality evaluation and possible earlier intervention at least in some patient subsets.
Background: The unprecedented exodus in the history of the European Union of more than 6 million Ukrainian refugees (May 13, 2022) is a cause for concern and could lead to a new difficult situation ...in terms of infectious disease control. Following the SARS-CoV-2 pandemic, Europe is facing a new challenge that could lead to a new wave of COVID-19 and an increase in the number of cases of tuberculosis or eradicated diseases, such as polio. Aim: The purpose of this analysis was to provide an overview of lung diseases and health risks that could be encountered in refugees from Ukraine and translated to European Union'countries. Methods: A systematic review was conducted in PubMed, World Health Organization, the UN Refugee Agency and the government's websites. Selected publications investigated the health problems arising from Ukrainian population migration from conflict areas and their impact on the public health system in the adoptive countries. The main potentially contagious diseases in Ukraine have also been reviewed. Results: The population of Ukraine has serious public health problems such as SARS-CoV-2 infection, multidrug-resistant tuberculosis, high levels of drug resistance and difficulties with an effective vaccination program, so there are significant risks of developing epidemics in transit or host countries. The current crisis has major peculiarities because the migrants were not concentrated in the camps but there was a dispersion of them on large territories of European countries. Conclusion: In order to meet the health needs of refugees, it is necessary to adapt health systems culturally and linguistically, to train health workers on the particularities of existing diseases in the countries of refugee origin, and to facilitate collection of medical data on migrants' health. Keywords: migrants, Ukraine, COVID-19, tuberculosis, polio, public health
The ongoing development of environmental barrier coatings (EBCs) offers the prospect to implement the full potential of silicon-based ceramic matrix composites (CMCs) for high temperature structural ...applications, more specifically the hot zones of gas turbine engines. The current state-of-the-art EBC system comprises a Si bond coat, a mullite (Al6Si2O13) interlayer and a barium–strontium aluminosilicate (BSAS) (Ba1−xSrxAl2Si2O8; 0<x<1) crack-resistant and water vapor attack resistant top coat. In this study, fully crystalline air plasma sprayed Si/mullite/BSAS-celsian EBCs were engineered under controlled conditions on SiC substrates. The influence of water vapor corrosion on the structural and mechanical properties of a Si/Mullite/BSAS EBC architecture was assessed by furnace thermal cycle testing (i.e.; 50 and 100cycles, 2h/cycles at 1300°C in water vapor atmosphere). The elastic modulus values of the as-sprayed BSAS top coat (~75±6GPa as determined via indentation) did not exhibit major changes after thermal exposure (~78±8GPa). In addition, the BSAS layer exhibited crack healing at high temperatures, the density of cracks decreasing from 15cracks/cm in the as-sprayed state to 2cracks/cm after thermal cycling. These characteristics of the BSAS top coat were related to its glass-ceramic nature, the phase/chemical stabilities of the BSAS-celsian at high temperatures and the engineered deposition conditions at which it was deposited. The overall performance at high-temperature of this functionally graded EBC architecture is discussed and correlated to its microstructural characteristics.
► Fully crystalline Si/mullite/BSAS-celsian EBCs were air plasma sprayed on SiC. ► The EBCs were thermally cycled at 1300°C in a H2O vapor flow up to 200h. ► Through-thickness cracking or debonding was not detected after thermal cycling. ► The hardness and elastic modulus values of thermally cycled EBCs were determined. ► The crack healing activity of the BSAS top coat was quantified.
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