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609 results on '"Mahmood, Rashid"'

14. Biochar for Sustainable Phosphorus Management in Agroecosystems

Author

Jehangir, Komel, Riaz, Muhammad, Mahmood, Rashid, Arif, Muhammad, Lichtfouse, Eric, Series Editor, Ranjan, Shivendu, Advisory Editor, Dasgupta, Nandita, Advisory Editor, Iqbal, Asif, editor, Iqbal, Mazhar, editor, Alamzeb, Madeeha, editor, Meizhen, Song, editor, Xiling, Zhang, editor, Arif, Muhammad, editor, and Du, Xiongming, editor

Published
2023
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27. Predicting the passive control of fluid forces over circular cylinder in a time dependent flow using neuro-computing.

Author

Asghar, Atif, Mahmood, Rashid, Majeed, Afraz Hussain, Alotaibi, Hammad, and Refaie Ali, Ahmed

Abstract

The objective of this research is to combine Artificial Neural Networks (ANNs) and Computational Fluid Dynamics (CFD) approaches to leverage the advantages of both methods. To achieve this goal, we introduce a new artificial neural network architecture designed specifically for predicting fluid forces within the CFD framework, aiming to reduce computational costs. Initially, time-dependent simulations around a rigid cylinder and a passive device (attached and detached) were conducted, followed by a thorough analysis of the hydrodynamic drag and lift forces encountered by the cylinder and passive device with various length L = 0.1 , 0.2 , 0.3 and gap spacing G i = 0.1 , 0.2 , 0.3 . The inhibition of vortex shedding is noted for gap separations of 0.1 and 0.2. However, a splitter plate of insufficient length or placed at an unsuitable distance from an obstacle yields no significant benefits. The finite element method is employed as a computational technique to address complex nonlinear governing equations. The nonlinear partial differential equations are spatially discretized with the finite element method, while temporal derivatives are addressed using a backward implicit Euler scheme. Velocity and pressure plots are provided to illustrate the physical aspects of the problem. The results indicate that the introduction of a splitter plate has reduced vortex shedding, leading to a steady flow regime, as evidenced by the stable drag and lift coefficients. The data obtained from simulations were utilized to train a neural network architecture based on the feed-forward backpropagation algorithm of Levenberg–Marquardt. Following training and validation stages, predictions for drag and lift coefficients were made without the need for additional CFD simulations. These results show that the mean square error values are very close to zero, indicating a strong correlation between the fluid force coefficients obtained from CFD and those predicted by the ANN. Additionally, a significant reduction in computational time was achieved without sacrificing the accuracy of the drag and lift coefficient predictions. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Alternative and Non-conventional Soil and Crop Management Strategies for Increasing Water Use Efficiency

Author

Riaz, Farah, Riaz, Muhammad, Arif, Muhammad Saleem, Yasmeen, Tahira, Ashraf, Muhammad Arslan, Adil, Maryam, Ali, Shafaqat, Mahmood, Rashid, Rizwan, Muhammad, Hussain, Qaiser, Zia, Afia, Ali, Muhammad Arif, Arif, Muhammad, Fahad, Shah, Fahad, Shah, editor, Hasanuzzaman, Mirza, editor, Alam, Mukhtar, editor, Ullah, Hidayat, editor, Saeed, Muhammad, editor, Ali Khan, Imtiaz, editor, and Adnan, Muhammad, editor

Published
2020
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40. Optimizing Nitrogen Sources in Top Dressing for Wheat: Field Study on Growth, Yield, and Ammonia Volatilization.

Author

Farooq, Muhammad Sajid, Mahmood, Rashid, Hameed, Aaqib, Ali, Sajid, Nadeem, Faisal, Awan, Tahir Hussain, Fatima, Ammara, Ahmad, Zaira, and Rahimi, Mehdi

Subjects
*WHEAT straw, *CALCAREOUS soils, *DIAMMONIUM phosphate, *SODIC soils, *GRAIN yields
Abstract

In alkaline calcareous soils, ammonia volatilization is the primary nitrogen (N) loss process, resulting in the reduced N use efficiency of crops. This study aimed at assessing the impact of different N sources for top dressing on ammonia volatilization, as well as their effects on wheat growth and yield over two years. In each year, half of the recommended N was applied as a basal dose using diammonium phosphate (DAP) and urea. The remaining half was top‐dressed 35 days after sowing with various sources: prilled urea (PU), granular urea (GU), ammonium sulfate (AS), and calcium ammonium nitrate (CAN) in the first year; PU, urea coated with a urease inhibitor from 20 g (VnU‐20) and 40 g (VnU‐40) leaves of Vachellia nilotica, biochar‐coated urea (BU), and urease inhibitor paraphenylenediamine‐coated urea (PPDU) in the second year. Ammonia volatilization losses were tracked for up to 12 weeks from sowing. Ammonia losses from basal‐applied N remained consistent in both years, comprising around 4% of the applied N. In the first year, top‐dressed AS resulted in the highest losses, followed by GU, while losses from urea and CAN were statistically similar. In the second year, coated fertilizers showed lower ammonia losses compared to PU, with VnU‐40 displaying the least losses, 48% less than PU. Nitrogen concentration in wheat grain and straw exhibited a negative correlation with ammonia losses. The choice of top‐dressed N source influenced tillering, biological, straw, and grain yields of wheat. In the first year, CAN provided maximum yield benefits, and in the second year, VnU‐20 exhibited 27% more grain yield than PU. These findings suggest that top dressing with coated urea, especially VnU‐20, has the potential to reduce ammonia losses, improve crop nitrogen status, and enhance economic yield compared to other nitrogen sources. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Corrigendum: Comparative efficacy of non-electric cooling techniques to reduce nutrient solution temperature for the sustainable cultivation of summer vegetables in open-air hydroponics

Author

Nisar, Muhammad Mohsin, primary, Mahmood, Rashid, additional, Tayyab, Salman, additional, Anees, Moazzam, additional, Nadeem, Faisal, additional, Bibi, Sadia, additional, Waseem, Faiza, additional, Ahmed, Nazir, additional, Li, Jing, additional, and Song, Zhao, additional

Published
2024
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