Red light crossing violations (RLCV) pose a significant hazard due to various factors influencing driver behavior and traffic signal operations. This study explores the efficacy of Deep Residual Neural Networks (DRNNs) in traffic signal optimization, specifically examining their influence on RLCV frequency. Data was collected from twenty signalized intersections over fifteen-minute intervals during weekdays, focusing on traffic volume, signal timing, geometric characteristics of approaches, and instances of the RLCV. The model successfully managed the well-known deep learning problem of vanishing gradient by exploiting DRNNs’ complex design, distinguished by their residual learning framework and identity mapping, easing the training of extremely deep networks. This enables the precise prediction and measurement of traffic flow and RLCV under changing circumstances, with R² = 0.9 for the testing data. The proposed methodology, which requires up to 48,000 samples, guarantees that the variance-based sensitivity analysis method’s indices converge, offering solid insights into the system’s behavior. The findings showed that the maximum queue length (QLmax) and the green and cycle times (G and C) substantially influence RLCV frequency, with a noticeable rise when QLmax exceeds ten vehicles and the G/C ratio falls below 0.15. This study underlines the urgency of addressing these factors to reduce RLCV frequency. It also emphasizes the potential of DRNNs in traffic management and recommends that future research concentrate on integrating real-time data for dynamic traffic signal modifications, therefore maximizing DRNNs’ potential in this sector.

One of the most important aspects of power quality for a distribution network's operation is the voltage sag issue. Simultaneous starting of irrigation motors fed from a distribution network leads to a voltage drop, which degrades the network's power quality. Mitigation of the voltage sag was carried out before by using superconducting magnetic energy storage (SMES) with a pre-defined capacity. The innovation of the present research work is optimal design of SMES including optimal sizing of SMES and its controller parameters with the consideration of its optimal cost for mitigating voltage sag resulting from simultaneous starting of irrigation motors in a real Egyptian distribution network. This is made by minimizing a multi-objective function formulated by a weighted-sum voltage sag and SMES cost. A new optimization technique called Mountain Gazelle Optimizer (MGO) is used to optimize the sizing of fuzzy logic …

Temperature effect on the performance of a photovoltaic module represents a major concern for expanding the use of solar energy, especially in hot areas. Cooling the PV module is considered an effective method of increasing efficiency by reducing the module cell temperature. An experimental set-up is developed to investigate the effectiveness of different cooling techniques including air cooling, evaporative cooling and water cooling. A comparative study is made among the cooling techniques by simultaneous recording – for the first time – the performance the modules cooled by the different techniques. Experimental measurements dictated that the reduction of the module cell temperature recorded 5 %, 16 %, 17.25, 39.6 % and 44.8 % for passive air cooling, active air cooling, water cooling, evaporative cooling using sprinkler and nozzles, respectively. 

The performance improvement of a PV-module is investigated theoretically and experimentally in a long-term research-plan via module cooling by different approaches including passive, active, and evaporative cooling as well as water cooling for the same module. In the present paper, the investigation is conducted to decide on the suitability of active-cooling of the module in hot-ambient temperatures. A module without cooling is used as a base case for comparison against cooled modules with and without fins attached to the module’s rear-surface and extended down in an air-cooling duct underneath the module. At first, a theoretical study of heat transfer through the module is conducted to investigate how the calculated cell temperature and module output power are influenced by the air velocity from a blower, ambient temperature and solar irradiation. The results showed a decrease of cell temperature by about …

This paper is aimed at assessing by theory and experiment the current–voltage and power-voltage characteristics of a PV module as influenced by dust accumulation. A method is proposed in a computer code to follow-up an incident solar radiation through the module layers considering the reflection and transmission of radiation at the interfaces between the layers to evaluate how the incident radiation is attenuated before reaching the module. Also, absorption of radiation in the dust layer and the glass cover is considered. The evaluation of the reflectance and transmittance calls for analysis of the accumulated dust to identify its constituents using X-ray fluorescence apparatus. The refractive and absorption indices are assessed for dust constituents as well as the corresponding effective values for the sample as a whole. The current–voltage characteristic of the dusty module is calculated using Simulink with …

A method is proposed for calculating the I-V and P–V curves of a PV array composed of series-, parallel- and series–parallel connected-cells or modules or strings exposed to uniform and non-uniform radiation with and without bypass diodes (BpDs). The P–V curve of the array exposed to uniform radiation has one power peak irrespective of the presence or absence of BpDs. In non-uniform radiation, the curve has a number of power peaks equal to that of the radiation levels in presence of BpDs irrespective of the number of diodes against one peak in absence of BpDs. The proposed method is based on combining Lambert-based simultaneous-solutions of the describing-equations V = g (I) and I = f (V) to obtain a global voltage equation V in terms of current I over all current range. The method is extended to locate the global maximum power point (GMPP) of the array by locating a point close to the GMPP

Reflective cracking poses a significant challenge to the performance and durability of Hot-Mix Asphalt (HMA) overlays, particularly when applied over deteriorated Joint Plain Concrete (JPC) pavements. This study explores the effects of reflective cracking on overlay pavements through Finite Element Analysis (FEA) using ABAQUS, integrating the Cohesive Zone Model (CZM) to simulate crack initiation and propagation. Key factors analysed include overlay thickness, modulus of elasticity, JPC joint width, and fracture areas within the pavement structure. The results indicate that increasing overlay thickness from 30 mm to 100 mm reduces tensile strain by up to 68.8%, significantly improving stress dissipation. Variations in the modulus of elasticity (ranging from 1500 Mpa to 6000 Mpa) were found to reduce tensile strain by approximately 37.5%. Additionally, the number of load repetitions required to cause reflective cracking increases with overlay thickness: 11,220 repetitions for 30 mm, 226,458 repetitions for 60 mm, and 458,835 repetitions for 100 mm. Wider JPC joints (from 6 mm to 20 mm) increased stress concentrations and crack severity. The study also quantified fracture behavior using the Representative Fracture Area (RFA), with RFA increasing by up to 99% under higher load repetitions. These findings provide practical recommendations for pavement design, particularly in selecting optimal overlay thicknesses and material properties to extend the lifespan of rehabilitated pavements and mitigate reflective cracking.

This comprehensive review analyzes research on enhancing steam boiler performance through energy and exergy analysis, emphasizing their importance in promoting sustainability and competitiveness in thermal power plants. The review identifies the combustion zone and heat exchanger surfaces as primary sources of irreversibility across diverse boiler designs. Higher pressure designs, particularly ultra-supercritical units, exhibit significant reductions in exergy destruction. Optimization strategies, such as combustion air preheating, excess air ratios, fuel properties, main steam conditions, and feedwater temperatures, play a vital role in improving efficiency. The study highlights the need for dynamic modeling and transient load evaluations, advocating for integrated co-optimization methodologies and exploring advanced materials, combustion techniques, waste heat recovery, and emerging technologies. Energy-exergy analysis emerges as a guiding framework for the sustainable evolution of steam boiler infrastructure and power generation. This review contributes to the literature by establishing performance benchmarks, identifying opportunities for improvement, and highlighting advancements in heat transfer and combustion processes, providing valuable guidance for enhancing thermal power plant efficiency and reducing environmental impact.

This paper presents an injection locked digitally controlled ring oscillator (IL-DCRO). To reduce jitter variations, minimize oscillator spurious signals, and eliminate periodical phase error, a double edge-injection (window injection) scheme with synchronized edge directions is proposed. A combinational edge generator is utilized to substitute the sequential edge generators for injection timing requirements relaxation. By biasing devices in deep triode, digitally controlled delay cells currents are adopted for frequency tuning. This helps reducing the devices flicker (1/f) noise and minimize the DCRO overall phase noise. At 1 MHz offset of frequency, the proposed oscillator has a measured phase noise of −125.95 dBc/Hz and −115.6 dBc/Hz at oscillation frequencies of 913.4 MHz and 432.6 MHz, respectively. Fabricated in 350 nm CMOS process, with a maximum power consumption of 3.3 mW, and oscillating at 913.4 MHz, this DCRO achieves a tuned oscillator figure of merit (FoM) of −197.35 dBc/Hz. The core area of this edge-injection-based DRCO is only 0.08 mm².