scholarly journals Improving Membrane Filtration Performance Through Time Series Analysis

2021 ◽  
Author(s):  
Jun Jie Wu
Keyword(s):  
Time Series ◽  
Membrane Filtration ◽  
Empirical Method ◽  
Integral Approach ◽  
Main Mode ◽  
General Applicability ◽  
Clear Cut ◽  
Filtration Performance ◽  
Overall Resistance ◽  
Volumetric Flux

Abstract For ultrafiltration, and membrane filtration more generally, the quantitative determination of the modes of fouling remains a subject of great interest. Herein a clear method for determining the modes from a time series of volumetric flux J(t) is given and illustrated with previously published filtration data of bergamot juice (Journal of Membrane Science 524 (2017) 108-116). The emphasis is upon the robust methodology which is of general applicability and offers a straightforward approach to the modelling of flux decline. The method is best viewed as being an empirical method that determines the point at which there is a switch from one mode to another is determined in a clear-cut manner and it yields excellent equations for J(t). For the example chosen, the initial 4 L/m2 generates some pore blocking after which the main mode of fouling is cake build-up. The variation of overall resistance with time is also informative and analysis of this series was used to check the result for the initial phase of fouling as determined from the time series of volumetric flux. A strength of the integral approach is that it enables one to establish whether the initial fouling is different in character from the subsequent fouling. Having this information can improve membrane selection and overall membrane filtration performance.

scholarly journals Improving membrane filtration performance through time series analysis

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Jun Jie Wu
Keyword(s):  
Time Series ◽  
Integral Method ◽  
Membrane Filtration ◽  
Moving Average ◽  
Empirical Method ◽  
Main Mode ◽  
Clear Cut ◽  
Filtration Performance ◽  
Overall Resistance ◽  
Volumetric Flux

AbstractFor ultrafiltration, and membrane filtration more generally, the quantitative determination of the modes of fouling remains a subject of great interest. Herein an integral method for determining the modes from a time series of volumetric flux $$J\left(t\right)$$ J t is given and illustrated with previously published filtration data of bergamot juice (Ruby-Figueroa et al (J Membr Sci 524:108-116, 2017)). The integral method of fouling analysis has the potential to become the cornerstone of a robust empirical process. In addition to determining, in a clear-cut manner, the point at which there is a switch from one mode to another, the robust methodology yields characteristic $$J\left(t\right)$$ J t equation for each mode that are an excellent fit to the data. The emphasis is upon the creation of a robust methodology which is best viewed as being a semi-empirical method that is indicative of the modes of fouling. For the example chosen, the initial 4 L/m2 generates some pore blocking after which the main mode of fouling is cake build-up. The variation of overall resistance with time is also informative and analysis of this series was used to check the result for the initial phase of fouling as determined from the time series of volumetric flux. A comparison against the ARIMA (Autoregressive integrated moving average) method, which has never been previously undertaken, is given herein. The integral method of fouling analysis was found to be superior, in part because of the quality of fit to the data and in part because it enables one to establish whether the initial fouling is different in character from the subsequent fouling. Having this information can improve membrane selection and overall membrane filtration performance.

scholarly journals The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters

2018 ◽  
Vol 7 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Adekunlé Akim Salami ◽  
Ayité Sénah Akoda Ajavon ◽  
Mawugno Koffi Kodjo ◽  
Seydou Ouedraogo ◽  
Koffi-Sa Bédja
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Time Series Data ◽  
Empirical Method ◽  
Likelihood Method ◽  
Series Data ◽  
New Approach ◽  
Weibull Parameters ◽  
Distribution Histogram ◽  
Mean Wind Speed

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150

Don’t “Waste” Your Time! The Effects of Time Series Errors in Management Research: The Case of Ownership Concentration and Research and Development Spending

1993 ◽  
Vol 19 (4) ◽  
pp. 897-914 ◽  
Author(s):  
Donald D. Bergh
Keyword(s):  
Time Series ◽  
Research And Development ◽  
Longitudinal Analysis ◽  
Fortune 500 ◽  
Ownership Concentration ◽  
Management Research ◽  
Clear Cut ◽  
Longitudinal Effects ◽  
Development Spending ◽  
The Relationship

The potential effects of “time series errors” in longitudinal analysis are examined empirically. Using a common hypothesis (the relationship between ownership concentration and research and development (R&D) spending) and a panel of 183 Fortune 500 firms (I 985-l 988) several time series errors are calculated. These analyses are then contrasted with the results of a procedure protected from time series errors. Comparisons show that (I) results may depend upon how researchers define and measure longitudinal effects; (2) time series errors can have significant effects on empirical findings; and (3) the linkage between ownership concentration and R&D may not be as clear-cut as previous studies have suggested. Recommendations for how researchers should account, save, and tell their time are offered.

scholarly journals Organic Solvent Nanofiltration of Water-in-Oil Pickering Emulsions—What Influences Permeability?

Membranes ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 864
Author(s):  
Maresa Vivien Kempin ◽  
Anja Drews
Keyword(s):  
Organic Solvent ◽  
Membrane Filtration ◽  
Significant Loss ◽  
Parameter Study ◽  
Pickering Emulsions ◽  
Catalyst Recycling ◽  
Filtration Performance ◽  
Multiphase Reactions ◽  
3D Network ◽  
Organic Solvent Nanofiltration

Pickering emulsions (PEs) have received increasing interest for their application in catalytic multiphase reactions. Organic solvent nanofiltration of PEs was shown to be a promising procedure for efficient and effective catalyst recycling. In this work, a systematic parameter study to identify the main influencing parameters on PE filtration was conducted for a large variety of PE compositions for the first time. In addition to temperature, only the type of organic solvent significantly influenced the filtration performance, which could be mathematically modeled via a combination of the solution–diffusion and the resistance in the series model. Particle type and concentration, dispersed phase fraction and the presence of reaction (by-)products did not show any significant impact on the permeability. The stirrer speed only became important when emulsions stabilized by particles without the tendency to form 3D network structures were filtered in long-term filtration experiments. These results pave the way towards the application of PE membrane filtration for catalyst recovery in continuous liquid/liquid multiphase reactions and enable broad operation windows. As the mechanical separation of PEs was shown to be a very robust process, the emulsion composition can now be tuned to meet the needs of the reaction without any (significant) loss in filtration performance.

scholarly journals Effects of Particles Diffusion on Membrane Filters Performance

Fluids ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 121
Author(s):  
Shi Yue Liu ◽  
Zhengyi Chen ◽  
Pejman Sanaei
Keyword(s):  
Pore Structure ◽  
Flow Rate ◽  
Membrane Filtration ◽  
Membrane Filter ◽  
Membrane Properties ◽  
Filtration Process ◽  
Membrane Pore ◽  
Filtration Performance ◽  
Structure Flow ◽  
Slow Filtration

Membrane filtration fouling is a very complex process and is determined by many properties such as the membrane internal morphology, membrane pore structure, flow rate and contaminant properties. In a very slow filtration process or during the late stage of filtration, when the flow rate is naturally low and Péclet number is small, particle diffusion is essential and cannot be neglected, while in typical filtration models, especially in moderate and fast filtration process, the main contribution stems from the particle advection. The objectives of this study is to formulate mathematical models that can (i) investigate how filtration process varies under possible effects of particles diffusion; and (ii) describe how membrane morphology evolves and investigate the filtration performance during the filtration process. We also compare the results with the case that diffusion is less important and make a prediction about what kind of membrane filter pore structure should be employed to achieve a particular optimum filtration performance. According to our results, the filtrate and efficiency of particle separation are found to be under the trade-off relationship, and the selection of the membrane properties depends on the requirement of the filtration.

Membrane filtration performance enhancement and biofouling mitigation using symmetric spacers with helical filaments

Desalination ◽  
2020 ◽  
Vol 484 ◽  
pp. 114454 ◽  
Author(s):  
Sarah Kerdi ◽  
Adnan Qamar ◽  
Alla Alpatova ◽  
Johannes S. Vrouwenvelder ◽  
Noreddine Ghaffour
Keyword(s):  
Membrane Filtration ◽  
Performance Enhancement ◽  
Filtration Performance

scholarly journals Indication of Electromagnetic Field Exposure via RBF-SVM Using Time-Series Features of Zebrafish Locomotion

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4818
Author(s):  
Yaqing He ◽  
Kim Fung Tsang ◽  
Richard Yuen-Chong Kong ◽  
Yuk-Tak Chow
Keyword(s):  
Time Series ◽  
Environmental Parameters ◽  
Empirical Method ◽  
Support Vector ◽  
The Novel ◽  
Adult Zebrafish ◽  
Field Exposure ◽  
Magnetic Exposure ◽  
Tank Test ◽  
The Impact

This paper introduces a novel model based on support vector machine with radial basis function kernel (RBF-SVM) using time-series features of zebrafish (Danio rerio) locomotion exposed to different electromagnetic fields (EMFs) to indicate the corresponding EMF exposure. A group of 14 adult zebrafish was randomly divided into two groups, 7 in each group; the fish of each group have the novel tank test under a sham or real magnetic exposure of 6.78 MHz and about 1 A/m. Their locomotion in the tests was videotaped to convert into the x, y coordinate time-series of the trajectories for reforming time-series matrices according to different time-series lengths. The time-series features of zebrafish locomotion were calculated by the comparative time-series analyzing framework highly comparative time-series analysis (HCTSA), and a limited number of the time-series features that were most relevant to the EMF exposure conditions were selected using the minimum redundancy maximum relevance (mRMR) algorithm for RBF-SVM classification training. Before this, ambient environmental parameters (AEPs) had little effect on the locomotion performance of zebrafish processed by the empirical method, which had been quantitatively verified by regression using another group of 14 adult zebrafish. The results have demonstrated that the purposed model is capable of accurately indicating different EMF exposures. All classification accuracies can be 100%, and the classification precision of several classifiers based on specific parameters and feature sets with specific dimensions can reach higher than 95%. The speculative reason for this result is that the specified EMF has affected the zebrafish neural aspect, which is then reflected in their behaviors. The outcomes of this study have provided a new indication model for EMF exposures and provided a reference for the investigation of the impact of EMF exposure.

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