Impact of metal oxides on thermal response of zirconia coated diesel engines fueled by Momordica biodiesel machine learning insights.

Biodiesel presents a favourable economic outlook and environmental benefits, yet it faces limitations such as diminished calorific value and suboptimal combustion characteristics. Recent research focuses on enhancing biodiesel performance using nanoparticles and thermal barrier coatings. This study investigates non-edible biodiesel from Momordica seed oil, tested on a single-cylinder diesel engine.

ML techniques increasing the power factor of a compression ignition engine that is powered by Annona biodiesel using SATACOM.

The global production of biodiesel in 2023 amounted to 34 billion liters because compression ignition engines need environmentally friendly fuel alternatives. The research investigates Annona biodiesel in combination with machine learning (ML) and STATCOM (Static Synchronous Compensator) technology to enhance power quality along with noise and vibration control in CI engines. Engine performance testing of diesel and B20-20% Annona biodiesel occurs under controlled conditions at rpm from 1200 to 2400 at which point STATCOM implemented both power factor improvement and current harmonic reduction for enhanced power quality.

Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning.

Monitoring and predicting ground vibration levels during blasting operations is essential to safeguard mining sites and surrounding communities. This study introduces an IoT-based ground vibration monitoring device specifically designed for limestone mining operations, combined with machine learning algorithms to predict ground vibration intensity. The primary aim is to provide an efficient predictive tool for anticipating hazardous vibration levels, enabling proactive safety measures.

Performance assessment of solar PV panels under varying environmental conditions: a laboratory and field-based approach for sustainable energy in mining operations.

This study provides a novel and comprehensive assessment of solar photovoltaic (PV) panel performance under varying environmental conditions, integrating laboratory experiments with real-world field studies to address challenges specific to mining operations. The research uniquely explores the combined effects of shading, temperature, humidity, dust deposition, and tilt angle, delivering actionable insights for optimizing PV systems in harsh conditions. Laboratory experiments demonstrated that a parallel configuration significantly minimizes power losses under partial shading, while a rise in temperature from 35 to 75 °C resulted in a notable 21.

Integrated smart dust monitoring and prediction system for surface mine sites using IoT and machine learning techniques.

The mining industry confronts significant challenges in mitigating airborne particulate matter (PM) pollution, necessitating innovative approaches for effective monitoring and prediction. This research focuses on the design and development of an Internet of Things (IoT)-based real-time monitoring system tailored for PM pollutants in surface mines, specifically PM 1.0, PM 2.

Multidisiplinary design optimization of a power generation system based on waste energy recovery from an internal combustion engine using organic Rankine cycle and thermoelectric generator.

The research paper mainly deals with waste heat recovery from internal combustion engines (ICE) using the organic Rankine cycle (ORC) and Thermoelectric generator (TEG). Simultaneously recovering the wasted heat of both exhaust gases and coolant, a novel configuration named two-stage is proposed. Then a comprehensive thermo-economic analysis and optimization are conducted.

Multiobjective optimization and performance assessment of a PEM fuel cell-based energy system for multiple products.

In this article, the optimal design of a novel multi-generation system for the production of electricity, cooling, heat and freshwater is discussed. In this system, a Proton exchange membrane fuel cell (PEM FC) is used to generate electricity, and the heat produced by it is absorbed by the Ejector Refrigeration Cycle (ERC) and used to provide cooling and heating capacity. A reverse osmosis (RO) desalination system is also used to supply freshwater.

Multiobjective optimization of a hybrid electricity generation system based on waste energy of internal combustion engine and solar system for sustainable environment.

In recent years, the interest in generating power through hybrid power generation systems has increased. In this study, a hybrid power generation system including an internal combustion engine (ICE) and a solar system based on flat plate collectors to generate electricity is investigated. To benefit from the thermal energy absorbed by solar collectors, an organic Rankine cycle (ORC) is considered.

Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches.

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m on the panel surface.

A study on enhancing the quantum yield and antimicrobial activity of Pr(iii) by varying the coordination environment.

Praseodymium forms complexes easily with nitrogen and oxygen donor pyrazolines and also forms mixed ligand complexes with these pyrazolines and sulfur donor thio ligands such as dithiocarbamates and xanthates. These newly synthesized complexes have been characterized using elemental analysis, FTIR, TGA, SEM, TEM, PXRD and UV-visible spectral measurements. The isotopic studies were performed using DART mass spectrometry.