Engineering Reports

The utilization of waste-based, thermal energy-storing building materials in construction may help reduce the environmental impact of human activities. However, most studies on phase change materials (PCM) tend to concentrate on the basic properties of these materials, and thus fail to provide a comprehensive perspective on sustainability. This review aims to present both the advantages and blind spots of waste utilization.

Thermal performance analysis of solar-driven vapor absorption cooling systems using TRNSYS reveals evacuated tube collectors outperform flat plate collectors in urban Pakistan, achieving higher solar fractions and primary energy savings. Optimal performance is recorded in Peshawar, emphasizing the potential for significant fossil fuel reduction.

Motivated by artificial neural networks, this paper develops the NNA to optimize a Fractional-Order PID controller for LFC in multi-area interconnected power systems. It improves frequency regulating capabilities and reduces overshoots/undershoots. It achieves a 27.66%–93.78% improvement in Integral of Time Absolute Error compared to other techniques.

Solar energy is the most practical and benevolent of renewable sources of energy; it can be utilized to power almost all electrical appliances and has a significant solution to the lack of energy and global warming. Since the beginning of the 20th century, the automobile industry has relied on natural resources like coal and petroleum that are finite and take longer to replenish. The utilization of these resources not only diminishes the available energy, but also directly affects the global environmental change. The gases that are omitted by the vehicles are the cause of the depletion of the ozone layer and the increase in temperature of the air that is inhaled. The most effective approach is to transition the automobile industry to a more electric-based industry, instead of a more exhaustible one, and the drawbacks would be eliminated. The electric energy storage capacity is limited for the cars, and a short distance needs to be traveled after which the vehicle will need to be recharged; this suggests the utilization of additional resources in order to increase the time of recharge with the help of solar energy. This article offers a solution to the finite resources and effective utilization of renewable solar energy in the automobile industry as an add-on to battery-powered vehicles.

Machine learning–based solar power generation monitoring.

A comparative analysis of traditional and ensemble machine learning models with advanced feature selection to detect polycystic ovary syndrome.

This paper proposes a deep aggregation seq2seq network with time feature fusion for air pollutant concentration prediction, which integrates temporal feature encoding with historical air pollutant concentration data through a cross attention network, and then excavates hidden features through deep aggregation seq2seq network.

In this paper, the carbon emission flow factor is used to accurately guide the demand response of electric vehicles on load side, and then the system is optimized and adjusted. The results show that EV participation in system interaction can reduce the overall carbon emission level.

This study optimizes basalt/glass fiber composites with hybrid MWCNT/SiO₂ nanofillers. Key factors—filler weight, pressure, and sonication—are analyzed via RSM. A tensile strength of 267 MPa is achieved with 1% filler, 15 MPa, and 30 min sonication. SEM analysis confirms enhanced bonding, validating accurate predictive models.

Aiming at the practical situation of new energy power system which contains a large amount of measurement data and variable operation status, a false data injection attack localization detection method based on associative feature-multi-label cascade augmented forest is proposed with higher accuracy, detection rate, and sensitivity.

The investigation of the effects of the building's orientation, window-to-wall ratio, and shading coefficient (SC) on the operational carbon reduction and peak cooling total load (PCTL) of the Plaza commercial building in Lahore, Pakistan (ASHRAE zone 1B).

An evacuated tube solar collector integrated with a PEM electrolyzer and hybrid nanofluids significantly enhances hydrogen production efficiency. Using Al₂O₃-SiO₂ hybrid nanofluids boosted system efficiency to 71.3%, achieving a maximum hydrogen yield of 3105.6 g, demonstrating the potential of advanced nanotechnology for sustainable energy solutions.

Graphical abstract showing glass powder's impact on properties and microstructure, optimizing 10–20% substitution for sustainability and cost-effectiveness.

New way of formalizing hybrid systems in models for managing the process of vessel unloading gives an ability to improve in sea ports container unloading technology and allow obtaining maximum results in terms of cargo processing speed. Concept of a hybrid control system makes possible to consider those features of the vessels unload process that have not been considered before.

Simulation model of proposed system.

The carbon flow of the integrated energy system is calculated, the carbon emission model and the carbon flow tracing model of the integrated energy system are established, and the optimization model aiming at low-carbon operation of the integrated energy system is constructed based on the master–slave game model.

A broad simulation model of the HVDC transmission system is developed using MATLAB software to evaluate the effectiveness of the proposed controllers such as Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), and optimization of Proportional-Integral-Derivative (PID) controller using Particle Swarm Optimization (PSO) based control strategy for addressing the frequency instability problems.

This framework illustrates a machine learning pipeline incorporating data preprocessing techniques (e.g., SMOTE-Tomek and data augmentation), the proposed EBM model alongside other boosting algorithms (XGBoost, LightGBM), and hybrid methods (LDA + DT + AdaBoost). The workflow emphasizes performance evaluation using metrics like accuracy and F1-score and interprets model predictions through explainable AI techniques such as SHAP and LIME.

Renewable energy contributes to Sudan's electricity grid with 54.6% from hydropower, 0.53% from biomass, 0.23% from solar, and 0.02% from wind, while significant potential remains untapped in geothermal, nuclear, and tidal energy.