| 1. |
- Asif, Muhammad, et al.
(författare)
-
The Effect of Infrared Laser Irradiation on the Surface Morphology and Electrical Properties of Zinc Metal
- 2023
-
Ingår i: Physchem. - : MDPI AG. - 2673-7167. ; 3:1, s. 22-33
-
Tidskriftsartikel (refereegranskat)abstract
- This study details the irradiation of pure (99.995%) and immaculate metallic Zinc using Nd: YAG laser (1064 nm, 10 mJ, 9–14 ns). The influence and impact of multiple laser shots on the formation of microstructures and crystal structure orientations is assessed. Arrays of ablated craters are machined on the whole surface of the target to probe the electrical and topographical characteristics of laser-treated surfaces. Irradiated samples are examined by multiple characterizing techniques such as scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), and a four-point probe for electrical conductivity measurements. SEM and AFM analysis exhibited the formation of laser-induced ripple structures with periodicity sheerly dependent on laser shots. A comparison of surface topography of the virgin and treated samples disclosed a pronounced modification in surface texture. The XRD patterns of laser shined targets indicate no momentous structural change in the crystal structure, whereas the measurements on the electrical conductivity of the irradiated surfaces exhibit an exponential descending trend with an augmentation in laser shots.
|
|
| 2. |
- Ehsan, Muhsan, et al.
(författare)
-
An integrated study for seismic structural interpretation and reservoir estimation of Sawan gas field, Lower Indus Basin, Pakistan
- 2023
-
Ingår i: Heliyon. - : Elsevier. - 2405-8440. ; 9:5
-
Tidskriftsartikel (refereegranskat)abstract
- The information about the subsurface structure, type of fluids present in the reservoir, and physical properties of the rocks is essential for identifying potential leads. The integrated approach of petrophysical analysis, seismic data interpretation, seismic attributes analysis, lithology, mineralogy identification, and Gassmann fluid substitution were used for this purpose. The structural interpretation with the help of seismic data indicated the extensional regime with horst and graben structures in the study area. The two negative flower structures are cutting the entire Cretaceous deposits. The depth contour map also indicate favorable structures for hydrocarbon accumulation. The four possible reservoir zones in the Sawan-01 well and two zones in the Judge-01 well at B sand and C sand levels are identified based on well data interpretation. The main lithology of the Lower Goru Formation is sandstone with thin beds of shale. The clay types confirm the marine depositional environment for Lower Goru Formation. The water substitution in the reservoir at B sand and C sand levels indicated increased P-wave velocity and density. The water substitution affected the shear wave velocity varies slightly due to density changes. The cross plots of P-impedance versus Vp/Vs ratio differentiate the sandstone with low P-impedance and low Vp/Vs ratio from shaly sandstone with high values in the reservoir area. The P-impedance and S-impedance cross plot indicate increasing gas saturation with a decrease in impedance values. The low values of Lambda-Rho and Mu-Rho indicated the gas sandstone in the cross plot.
|
|
| 3. |
- Khan, Adil, et al.
(författare)
-
Predictive modeling for depth of wear of concrete modified with fly ash : A comparative analysis of genetic programming-based algorithms
- 2024
-
Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 20
-
Tidskriftsartikel (refereegranskat)abstract
- There has been increasing growth in incorporating fly ash as a supplementary cementitious material in concrete mixtures due to its potential to enhance the durability and strength properties of concrete. However, there is a lack of research on predicting the depth of wear of fly ash-based concrete. The laboratory methods available for estimating the depth of wear often involve destructive and expensive tests. Therefore, to avoid costly and laborious tests, this study utilized two machine learning methods, including multi-expression programming (MEP) and gene expression programming (GEP), to predict the depth of wear of fly ash-modified concrete. A comprehensive dataset of 216 experimental records was compiled from published studies for model training and validation. This extensive dataset encompasses the depth of wear as the target variable, along with nine explanatory parameters, namely fly ash, cement content, fine and coarse aggregate, water content, plasticizer, age of concrete, air-entraining agent, and testing time. The models were trained with 70% of the data, and the remaining 30% of data was used for validating the models. The models were developed by a continuous trial-and-error process and iterative refinement of hyperparameters until optimal results were achieved. The efficacy of the models was assessed via multiple statistical indicators. Furthermore, the SHapley Additive exPlanation (SHAP) was utilized for the interpretability of the model prediction from both global and local perspectives. The GEP model exhibited excellent accuracy with a correlation coefficient (R) of 0.989 (training) and 0.992 (validation). Similarly, the MEP model provided prediction accuracy with R values of 0.965 and 0.968 for training and validation sets, respectively. In addition, the MEP and GEP models outperformed the traditional multi-linear regression model. The SHAP interpretation revealed that testing time and age have a higher contribution in determining the depth of wear. The findings of this study can assist practitioners and designers in avoiding costly and laborious tests for durability assessment and promoting sustainable use of fly ash in the construction sector.
|
|
| 4. |
- Khan, Shah Nawaz, et al.
(författare)
-
Numerical investigation of thermomechanical behavior of Yttrium barium zirconate-coated aluminum alloy piston in an internal combustion engine
- 2024
-
Ingår i: Applied Thermal Engineering. - : Elsevier. - 1359-4311 .- 1873-5606. ; 236:part B
-
Tidskriftsartikel (refereegranskat)abstract
- Increasing engine power to volume density is under investigation and being analysed extensively. Turbocharger, which is used to boost volumetric efficiency, also raises cylinder temperature and pressure, thus resulting in thermal distortions and reducing clearances in tribo-contacts, thereby compromising engine life. Thermal barrier coatings (TBCs) have shown potential to provide remedies to reduce heat losses, hazardous emissions, and heat flow toward the piston skirt in an internal combustion engine. In this study, a detailed thermo-mechanical analysis was performed for a diesel engine piston with a novel yttrium barium zirconate (YBZ) coating and then compared with other TBCs with varying thicknesses. The results revealed a notable decrease in piston substrate surface temperature when coated with various TBCs, with YBZ coating demonstrating superior performance over others. The 0.2 mm coating of YBZ-coated piston exhibited significant reductions of 15% and 10.3% in temperature and thermal stress respectively, thus enhancing piston durability. The better performance of the novel YBZ coating could be attributed to its stable thermal and elastic properties and lower thermal conductivity than other TBC materials. YBZ coating provides a promising solution to improve engine efficiency while extending engine life, making it an attractive option for the automotive industry.
|
|
| 5. |
- Razaq, Muhammad Ahsan, et al.
(författare)
-
Observer-based leader-following consensus of one-sided Lipschitz multi-agent systems over input saturation and directed graphs
- 2023
-
Ingår i: Asian Journal of Control. - : WILEY. - 1561-8625 .- 1934-6093. ; 25:5, s. 4096-4112
-
Tidskriftsartikel (refereegranskat)abstract
- This paper investigates a local observer-based leader-following consensus control of one-sided Lipschitz (OSL) multi-agent systems (MASs) under input saturation. The proposed consensus control scheme has been formulated by using the OSL property, input saturation, directed graphs, estimated states, and quadratic inner-boundedness condition by attaining the regional stability. It is assumed that the graph always includes a (directed) spanning tree with respect to the leader root to develop matrix inequalities for investigating parameters of the proposed observer and consensus protocols. Further, a new observer-based consensus tracking method for MASs with saturation, concerning independent topologies for communicating outputs and estimates over the network, is explored to deal with a more perplexing and realistic situation. In contrast to the traditional methods, the proposed consensus approach considers output feedback and deals with the input saturation for a generalized class of nonlinear systems. The efficiency of the obtained results is illustrated via application to a group of five moving agents in the Cartesian coordinates.
|
|
| 6. |
- Khan, Majid, et al.
(författare)
-
Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms
- 2023
-
Ingår i: Heliyon. - : Cell Press. - 2405-8440. ; 10
-
Tidskriftsartikel (refereegranskat)abstract
- Fiber-reinforced polymers (FRP) are widely utilized to improve the efficiency and durability of concrete structures, either through external bonding or internal reinforcement. However, the response of FRP-strengthened reinforced concrete (RC) members, both in field applications and experimental settings, often deviates from the estimation based on existing code provisions. This discrepancy can be attributed to the limitations of code provisions in fully capturing the nature of FRP-strengthened RC members. Accordingly, machine learning methods, including gene expression programming (GEP) and multi-expression programming (MEP), were utilized in this study to predict the flexural capacity of the FRP-strengthened RC beam. To develop data-driven estimation models, an extensive collection of experimental data on FRP-strengthened RC beams was compiled from the experimental studies. For the assessment of the accuracy of developed models, various statistical indicators were utilized. The machine learning (ML) based models were compared with empirical and conventional linear regression models to substantiate their superiority, providing evidence of enhanced performance. The GEP model demonstrated outstanding predictive performance with a correlation coefficient (R) of 0.98 for both the training and validation phases, accompanied by minimal mean absolute errors (MAE) of 4.08 and 5.39, respectively. In contrast, the MEP model achieved a slightly lower accuracy, with an R of 0.96 in both the training and validation phases. Moreover, the ML-based models exhibited notably superior performances compared to the empirical models. Hence, the ML-based models presented in this study demonstrated promising prospects for practical implementation in engineering applications. Moreover, the SHapley Additive exPlanation (SHAP) method was used to interpret the feature's importance and influence on the flexural capacity. It was observed that beam width, section effective depth, and the tensile longitudinal bars reinforcement ratio significantly contribute to the prediction of the flexural capacity of the FRP-strengthened reinforced concrete beam.
|
|
