The Journal of Engineering Research [TJER]

Integrated AHP – TOPSIS Approach for Optimization of Coolant with Nanoparticles in PVT-Based Hydrogen Production System

2024-08-01T08:07:47+04:00

The production of hydrogen using photovoltaic–thermal (PVT) solar collectors with minimal environmental impact is a significant issue that necessitates a methodical approach. The selection of an appropriate nanofluid is essential in a thermal collector to optimize the performance of the photovoltaic-thermal (PVT) system and increase the rate of hydrogen production. This study analyzes several nanofluids in terms of viscosity, thermal conductivity, density, specific heat, pumping power, and fluid cost. This study discovered a nanofluid that may significantly enhance the rate of hydrogen generation. To achieve this objective, the analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods were used to identify the appropriate choice and assess the hydrogen production rate. First, the AHP technique was used to determine the required weights, followed by sorting the alternatives using the TOPSIS technique. The findings indicate that a hybrid nanofluid consisting of a 0.2% volume concentration of Al₂O₃–CuO in water exhibits the most favourable heat transfer characteristics and is considered the best option for improving heat transfer efficiency and boosting the rate of hydrogen generation.

Drag-Reducing Polymers as Energy-Saving Agents in Horizontal Two-Phase Oil-Water Dispersed Flow

2024-08-01T08:19:50+04:00

In this era of scarce and expensive energy, it has become imperative to devise means of reducing energy consumption, particularly in petroleum industries where huge amounts of energy are usually consumed. It is within this context that attempts have been made to reduce the energy consumption during pump-driven fluid transportation by the addition of drag-reducing polymers (DRPs), which mitigate the adverse frictional drag caused by the pipe wall. Hence, this study focused on quantifying the energy savings by the DRPs in dispersed oil-water flow at different Reynolds numbers using twelve DRPs, which possess different combinations of properties such as molecular weight, charge density, and ionic type. The results revealed substantial savings in energy in all cases with the highest saving of about 60.4%. Molecular weight posed a positive and most dominant impact among the three polymer properties investigated. The charge density slightly increased the energy savings at low values while the reverse was the case at high values. Cationic polymers produced slightly better performances than their anionic counterparts of comparable molecular weights and charge densities. Specifically, the energy saving at oil fractions of 0.1 and 0.3 increased from 6.9 to 60.4% and 5 to 51.9%, respectively, indicating the negative impact of the oil fraction. Overall, the use of DRPs has proved to be an efficient and sustainable means of saving substantial amounts of energy required to overcome the frictional drag in pipe flow.

Sustainable building production adopting an optimized BIM phasing system

2024-08-01T09:13:13+04:00

Sustainable building production could be achieved through better economic efficiency, reduced site waste, and a safe working environment. The identification of the creation phase for each element in the building information model (BIM) is manually done by experienced engineers able to integrate technical construction constraints and an appropriate workflow of construction activities. It is a difficult and complex task to be done. Experienced engineers iterate this operation several times until an adequate solution is achieved without real possibility of optimization. The development of an assistance tool to optimize phase identification of BIM elements included in the repetitive floor plan considering varied evaluation criteria and technical construction constraints should lead to significant economic and environmental profits: reduction of needed construction resources and related waste, improvement of construction quality, and better conditions of site safety. The optimization tool presented in this paper provides better solutions for repetitive floor plans specifically through balanced quantities of work hours and a lower quantity of needed formworks. A reduction of around 10% of labour and 25% of non-used formwork is achieved, which significantly improves site safety, productivity, and profitability. The validity of the presented results is substantiated by multiple examples from real construction sites that have been analyzed in this study.

Data Mining for Enhanced Security: A Transformative Framework for Smart Grid Protection

2024-08-13T09:35:13+04:00

Smart grids fall at the intersection of conventional energy systems and modern informatics in the present digitalized energy environment. The growing number of linked devices and sensors in these networks leads to the generation of complex structures and vast quantities of data, presenting benefits and challenges. Safeguarding these complex structures against malicious intrusions and illegal activities is an important problem. The paper's main objective is to enhance smart grid security by utilizing the data mining and Artificial Intelligence (AI) approaches. As huge amounts of data are collected from the smart grids based on tiny and smart internet of things (IoT) devices, this data poses challenges as well as provides opportunities. The challenges come from analyzing this huge data, especially in real-time. At the same time, it provides opportunities to enhance the smart grid services and protection. Therefore, to overcome these challenges, this paper proposes a feedforward deep learning approach for data mining to secure the smart grid from different anomalies and allow the system to adapt to any risk it might face. Deep learning will allow the system to adjust dynamically to emerging risks. The proposed system has been examined using Power System Attack Datasets sourced from the Mississippi State University and Oak Ridge National Laboratory. The results show a detection accuracy of 91% just using 50% of the dataset features. Different percentages of the features are examined as well. However, we concluded that 50% of the features are enough for identifying the smart grid risks based on the given dataset.

Improvement in Fluid Loss Control and Viscosity of Water-based drilling Mud under High Temperature and Sodium Chloride Salt Conditions using Nanohydroxyapatite

2024-08-13T10:08:23+04:00

It is difficult to drill efficiently with bentonite (BN)-based mud (BN-WBM) or water-based muds (WBMs) in high-salt electrolytes and deep wells. This is because the fluid's rheological parameters and filtration properties change in undesirable ways, affecting the well's production efficiency. To fix this, a high-salt and high-temperature-resistant nanohydroxyapatite (nanoHAp) additive was designed using sodium dodecyl sulphate (SDS). 0.1 to 0.5 wt% nanoHAp was added to WBMs, and a salt-resistant BN-WBM with nanoHAp was formulated with 4.8 wt% BN, 5.0 wt% sodium chloride (NaCl), and 0.5 wt% nanoHAp. At 25, 150, 180, and 210° C, the filtration and rheological characteristics of the drilling muds were evaluated. The findings revealed that between 25 and 210° C, nanoHAp increased the viscosity of the WBM by 15–139% at a 1021 s^-1 shear rate. It also controlled the fluid loss of the WBM from 12.1-44.6 mL to 6.7-21.8 mL at all temperatures. It serves as an anti-salt agent by decreasing the NaCl-contaminated BN's viscosity by 57% compared to the reference value of 20.8 mPa. s at a shear rate of 1021 s^-1. Further, it reduced the fluid loss by 56.8%, from 169 mL to 73 mL at 210° C. The nanoHAp surface has anionic sulphate head groups of SDS that efficiently attach to the BN surface. This keeps the Na⁺ ions from attacking the plate-like structure of the BN. This study reveals that nanoHAp has the capacity to inhibit BN coalescence and flocculation under saturated Na⁺ solutions and at high temperatures.

Effect of Nanoparticles in Drilling Fluids on the Transportation of Different Cutting Sizes in a Rotating Horizontal Pipe

2024-08-13T13:07:10+04:00

: Cutting transport is difficult in horizontal borehole regions due to the limited axial velocity distribution. This causes transported cuttings to gravitate to the bottom, generating cutting beds and leading to drilling mishaps. Water-based mud (WBM) that includes nanoparticles (NPs) to determine the cutting transport ratio (CTR) performance using copper II oxide (CuO), aluminium oxide (Al₂O₃), magnesium oxide (MgO), and silicon dioxide (SiO₂) in a horizontal borehole needs further investigation. These NPs ability to transport 0.80–3.60 mm cutting sizes was tested using concentrations of 1.0 and 2.0 g circulated through a horizontal annulus at 3.5 m/s and 120 rpm. With 2.0 g, MgO lowered the viscosity by 60%, whereas SiO₂, CuO, and Al₂O₃increased it by 49%, 10%, and 87%, respectively. CuO NP decreased the fluid loss (FLAPI) the best, followed by MgO, SiO₂, and Al₂O₃. The FLAPI of the WBM, which was 9.4 mL, dropped to 4.8, 5.1, 7.4, and 8.2 mL with CuO, MgO, SiO₂, and Al₂O₃ NPs, respectively. The CTR performance of the NPs increased with concentration and decreased with increasing cutting size. CuO, having less viscosity than Al₂O₃ and SiO₂, carried the most cutting at all concentrations and sizes. It increased the CTR by 28.8–31.1%, whereas Al₂O₃ and SiO₂ increased it by 22.7–26.7% and 16.7–22.2%, respectively. The lowest increase was 13.6–17.8% for MgO NP. This study demonstrates the favourable impact of NP concentrations on the performance of drilling fluids while presenting many choices for the selection of NPs.

Impact of Selected Adsorbent Functional Groups on Chromium Sorption Capacities In An Effluent Treatment: A DFT Study

2024-08-14T07:59:58+04:00

Communities are often exposed to high health risks via the presence of most heavy metals in water bodies used by their residents. Chromium, an abundant heavy metal in industrial effluents, contaminates our environment and water sources, endangering human and animal consumption. Designing materials for Cr removal from potential effluent discharges is crucial. Bio-based sorbents have been explored, but the role of functional groups remains unclear. This research investigates the influence of functional groups in removing dissolved chromium heavy metals to enhance water quality. In this study, we look at how well functional groups like carboxylate, carbonyl, nitrile, aldehyde, alcohol, and carboxylic acid bind to Cr (III) metal. We look at stable Cr metal cluster configurations using Spartan software and density functional theory (DFT) for quantum chemical calculations. We measure energies and thermodynamic properties during interactions. Our findings demonstrate that sorbents with carbonyl and carboxylate groups exhibit high sensitivity to Cr, making them effective for removal. The relative adsorption energies align with experimental results. This study confirms the potential of computational methods to predict sorbents' selectivity in removing various heavy metals from water, offering a promising avenue for water treatment and environmental protection.

Energy Auditing of HVAC Systems for the Enhancement of Efficiency and Sustainability

2024-08-14T08:03:04+04:00

Energy audits are crucial for identifying opportunities to enhance efficiency and promote sustainability in the energy sector. In Oman, air conditioning systems account for about 50% of the nation's electricity use, reaching up to 70% in summer due to temperatures as high as 50°C. This study aimed to analyze energy consumption, focusing on air conditioning and refrigeration systems, using an academic building as a case study to improve energy efficiency and sustainability. A series of energy audits identified opportunities for energy conservation in the building's systems. The audit revealed that implementing various low-cost, high-cost, and zero-cost strategies could enhance energy efficiency and sustainability, resulting in an annual energy savings of 37.6%. Zero-cost initiatives, such as turning off HVAC systems when unoccupied, closing main doors, and setting thermostat temperatures to 24ºC, reduced energy consumption by 10%. Low-cost measures, including installing occupancy sensors for lighting and ensuring proper HVAC maintenance, led to a 20.8% reduction. High-cost measures, such as installing windows with lower Solar Heat Gain Coefficient (SHGC) values, resulted in approximately 6.8% energy savings.