NED University of Engineering & Technology

Polarization impairments caused by environmental disturbances significantly degrade the performance of high-speed optical fiber communication systems by introducing time-varying changes in the state of polarization (SOP). This paper presents a hybrid polarization compensation framework that combines machine learning (ML) with classical deterministic control to achieve fast and robust real-time SOP tracking. The proposed approach employs an ML model to rapidly estimate actuator voltages close to the desired operating point, while a classical feedback controller performs the final fine adjustment within the analytical Mueller-matrix polarization framework. The performance of the proposed method is experimentally and numerically compared with conventional Proportional–Integral–Derivative (PID), Hill-Climbing, and Stochastic Parallel Gradient Descent (SPGD) controllers. Experimental results demonstrate that the proposed hybrid controller achieves the fastest convergence, stabilizing the polarization state in approximately 6s, compared with 17.76s, 29.95s, and 30.58s for SPGD, PID, and Hill-Climbing, respectively. The proposed method also maintains a high Degree of Polarization (DOP) throughout the tracking process while exhibiting improved disturbance rejection, reduced oscillations, and stable optical power delivery. These results demonstrate that integrating machine learning with deterministic polarization control significantly improves convergence speed and robustness, making the proposed framework suitable for next-generation optical communication and polarization-sensitive photonic systems.

Maintaining optimal mud properties during drilling operations is essential for achieving efficient drilling performance. While previous studies were mainly focused on long chain polymer; Partially hydrolyzed polyacrylamide, this study investigates the use of short-chain of Partially hydrolyzed polyacrylamide (commercially known as Clay grabber) obtained from service vendor operating in the Northern Region of Pakistan, along with a biopolymer, sodium alginate. Both polymers were added in the water-based mud at three different volumes (5 mL, 10 mL and 20 mL), and parameters including mud weight, pH, and all the rheological characteristics of studied samples were experimentally evaluated. Results indicate that the mud density for Clay grabber samples increased from 1080 to 1150 kg/m3 and from 1150 to 1170 kg/m3 for sodium alginate samples as volume increases from 5 to 20 mL. The pH values of all the muds under observation ranged between 8 to 10.5, indicating a basic nature that helps to prevent corrosion. Plastic Viscosity for Clay grabber samples increased from 13 to 20 cP with volume, while sodium alginate demonstrated non-linear behavior ranging between 14 to 18 cP. Moreover, yield point of Clay grabber samples increased substantially from 29 lb./100ft2 to 45 lb./100ft2, which indicates stronger intermolecular forces and improved cutting transportation capacity compared to sodium alginate samples. Furthermore, all samples under observation exhibited non-Newtonian shear thinning behavior with flow index less than 1. Additionally, the consistency index for Clay grabber samples were all greater than 1, reflecting higher mud thickness and improved hole-cleaning performance. The result clearly indicates that the short chain clay grabber sample was more effective than sodium alginate in improving the characteristics and performance of water-based drilling mud, making it a better choice for maintaining wellbore integrity and improving drilling efficacy.

Concentrated Solar Power (CSP) technology uses a heliostat field to focus direct normal irradiance onto a central receiver, heating a fluid that generates steam for a conventional turbine-generator set. In this study, we evaluate the technical, economic and environmental performance of a 100 MW solar power tower plant at Islamkot in Pakistan's Thar region, chosen for its high annual Direct Normal Irradiance (DNI) of 1600-1900 kWh/m2, level terrain and proximity to grid and transport infrastructure. Thermodynamic analysis based on the Rankine cycle coupled with NREL's System Advisor Model predicts an annual electricity output of approximately 277.4 million kWh and a levelized cost of electricity of $0.0916 per kWh over a 30-year lifespan. Exergy evaluation indicates an overall efficiency of 22.9 percent, decreasing to 20.6 percent when auxiliary parasitic loads are accounted. Financial metrics show a net present value of $623.7 million, a discounted payback period of 9.4 years and a return on investment of 1.53 times. Replacing an equivalent conventional thermal plant yields an annual reduction of nearly 115,000 tons of CO2, which is approximately 82 % percent decrease in lifecycle emissions, demonstrating substantial environmental benefit.

Liquefied natural gas (LNG) production is an energy-intensive process, and mixed-refrigerant cycles dominate industrial applications. This study proposes and optimises a novel propane-free dual mixed refrigerant (DMR) configuration for LNG liquefaction using Aspen HYSYS v14 with the Peng-Robinson EOS. The system eliminates propane to enhance operational safety while maintaining high thermodynamic efficiency. Energy, exergy, and advanced exergy analyses reveal a specific energy consumption (SEC) of 0.29 kW/kg LNG and an exergy efficiency of 67.27 %. The advanced exergy assessment identifies that 68.40 % of total exergy destruction is avoidable, indicating significant potential for further efficiency gains. Comparative benchmarking confirms that the proposed configuration achieves one of the lowest reported SEC values among both propane-based and propane-free DMR cycles. This research provides a technically validated and safer pathway towards sustainable LNG production.

Global warming and energy crisis have driven the attention of researchers towards conversion of waste materials into valuable products. As compared to the simple pyrolysis, the co-pyrolysis is an environmentally friendly and effective waste conversion process which enhances the yield and properties of the co-pyrolytic fuel. This study explored the effect of temperature (380-450 degrees C, with 10 degrees C difference) on the yield and properties of the copyrolytic oil produced from waste frying oil and waste engine oil mixture with 1:1 ratio by volume. The influence of co-pyrolysis temperature on the fractions and properties of the distillate oil within the boiling range of diesel was also analyzed, which was obtained by ASTM D86 distillation of the co-pyrolytic oil. This co-pyrolysis study was conducted in a stainless-steel semi-batch reactor of 1.856-liters capacity. Most of the samples showed that physiochemical properties resembled to that of the commercial diesel, particularly at temperatures above 420 degrees C. Product fuel was characterized by testing commercially important physiochemical properties including pour point, cetane index, API gravity, kinematic viscosity, calorific value, sulfur content and flash point by using test methods set by ASTM standards. Properties of the product fuel were compared to that of the standard specifications for diesel and biodiesel set by ASTM. The highest yield of co-pyrolytic oil (80.1 wt%) and highest fraction of distillate oil (85 vol%) were obtained at 450 degrees C. By comparing with diesel and biodiesel, co-pyrolytic and distillate oils obtained at 450 degrees C showed physiochemical properties resembling closely to the commercial diesel.