Coal seam gas-associated water (CSGAW), which is a by-product of coal seam gas (CSG) production typically contains significant amounts of salts and has potential environmental issues. In this study, we optimized a bench-scale vacuum membrane distillation (VMD) process with flat-sheet hydrophobic polytetrafluoroethylene (PTFE) membranes for the treatment of synthetic CSGAW (conductivity = 15 mS/cm). To study performance of the VMD process, we explored the effects of feed temperature (T(f) = 60, 70, and 80°C), feed flow rate (V(f) = 60, 120, and 240 mL/min), and vacuum pressure (P(v) = 3, 6, and 9 kPa) on water permeability through the PTFE membrane in the VMD process. Under the optimum conditions (i.e. T(f) = 80°C, V(f) = 240 mL/min, P(v) = 3 kPa), water permeability and rejection efficiency of salts by the VMD process were found to be 5.5 L/m(2)/h (LMH) and 99.9%, respectively, after 2 h filtration. However, after 8 h operation, the water permeability decreased by 70% compared with the initial flux due to the formation of fouling layer of calcium, chloride, sodium, magnesium, and potassium on the membrane surface.
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http://dx.doi.org/10.2166/wst.2015.229 | DOI Listing |
Sci Rep
January 2025
School of Civil Engineering, Qingdao University of Technology, Qingdao, 266525, China.
In the field of Structural Health Monitoring (SHM), complete datasets are fundamental for modal identification analysis and risk prediction. However, data loss due to sensor failures, transmission interruptions, or hardware issues is a common problem. To address this challenge, this study develops a method combining Variational Mode Decomposition (VMD) and Sparrow Search Algorithm (SSA)-optimized Gate Recurrent Unit (GRU) for recovering structural response data.
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January 2025
Department of Fruit, Vegetable and Plant Nutraceutical Technology, The Faculty of Biotechnology and Food Science, Wrocław University of Environmental and Life Sciences, 37 Chełmońskiego Str, 51-630, Wrocław, Poland.
Drying plant raw materials using modern techniques or combined methods is currently one of the main trends in food technology, which combines process optimization in line with the principles of sustainable development while maintaining high product quality. Therefore, this study aims to be innovative, assessing the possibility of using sublimation techniques, convective drying (CD) at different temperatures (50 °C, 60 °C, 70 °C), vaccum microwave drying (VMD) at different power levels (120 W, 240 W, 360 W, and 360/120 W), and combining these two techniques- CD-VMD (50 °C/120 W, 60 °C/120 W, 70 °C/120 W) in the production of peach snacks. The qualitative analysis of the tested dried peaches showed that the content of polyphenols was dominated by polymers of procyanidins (82.
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January 2025
College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, Gansu, China.
Heart disease is a significant global health issue. Traditional methods for heart rate monitoring typically require close physical contact, which limits the continuity and convenience of monitoring. To achieve real-time, non-contact heartbeat monitoring, researchers have introduced millimeter-wave radar technology.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
School of Artificial Intelligence, North China University of Science and Technology, 063210 Tangshan, China.
In response to the problem of noise interference in the knock detection signal received by the pickup in the ceramic sheet knock non-destructive testing, a noise removal method is proposed based on the improved secretary bird optimization algorithm (ISBOA) optimized variational mode decomposition (VMD) combined with wavelet thresholding. First, the secretary bird optimization algorithm is improved by using the Newton-Raphson search rule and smooth exploitation variation strategy. Second, the ISBOA is used to select the key parameters in the VMD.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Mechanical and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China.
Accurately predicting tool wear during the machining process not only saves machining time and improves efficiency but also ensures the production of good-quality parts and automation. This paper proposes a combined variational mode decomposition (VMD) and back propagation (BP) neural network model (VMD-BP), which maps spindle power to tool wear. The model is trained using both historical and real-time data.
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