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Aluminum is a highly valuable structural metal utilized in various industrial sectors; particularly, it is utilized in considerable quantities in the nautical, aeronautical, and automotive industries. Aluminum is additionally utilized in small amounts in several other industrial sectors. The composite materials are now extensively utilized in various applications after their introduction. In this research, they prepared composite samples of aluminum with adding hematite nanoparticles with different ratio (2, 4, 6, and 8) wt% by powder metallurgy technology, and the sample preparation conditions was (mixing time reach to 2 h for every sample; the compaction loads is 6 tons and sintering temperature equal to 600°C). The tests conducted were XRD, SEM, EDS, green density, green porosity, microhardness, compression, and wear. The results illustrate that the hardness and wear values increase when increasing the hematite percentage.

Because it is essential to avoid toxicity and corrosion in order to enhance the steel components and their aesthetic magnitude used in our everyday life, there has been an increased interest in the electroless field, particularly with regard to the application of nickel-phosphor on steel substrates. In this work, electroless process by nickel low phosphor solution and added titania particles (10–30  µm) to amount of coating solution (0, 5, and 10  g/L) with different coating times (30 and 60 min). Then, many tests were conducted, involving coating thickness, surfaces roughness, hardness, energy-dispersive X-ray spectroscopy, scanning electron microscopy, and linear polarization tests in salt solution that were carried out for substrate and coating layers. Hardness indicates that the mechanical characteristics of the applied coatings with incorporated (TiO2) reinforcement were far more superior to its own matrix as well as noncomposite nickel coating. The polarization curves conducted by potentiodynamic technique for different coating layers with 3.5% NaCl a medium and find all data by computerize, which shows that the addition of TiO2 extract improved the corrosion rate (67.58%) than uncoating specimen.

The present investigation adopts a new method to recycle the oils. The used and recycled lubricants were compared to fresh oil. Accordingly, an investigation was carried out to evaluate the viscous shear of different oil grades at each certain temperature using the Walther formula of the viscosity–temperature relationship. The investigation indicates acceptable and fair results in front of a technical point of view and environmental improvement by reducing pollution. The results show lower viscosity of the recycling oil than the used oil, which affects the viscous shear as it is directly proportional to the velocity gradient and the fluid’s viscosity at ascertaining temperature. In the present investigation, alum (Al2(SO4)3(H2O)18) was used, which gives good precipitation according to the practical results mentioned in this work. The used oils of grades 5w20, 5w30, and 10w30 under consideration are collected from the local internal combustion engines. Both kinematic viscosity and viscous shear for 10w30 oil grade record the highest values, and 5w20 records the lowest values for all oil types (fresh, recycled, and used oil).

River sedimentation is an important indicator for ecological and geomorphological assessments of soil erosion within any watershed region. Sediment transport in a river basin is therefore a multifaceted field yet being a dynamic task in nature. It is characterized by high stochasticity, non-linearity, non-stationarity, and feature redundancy. Various artificial intelligence (AI) modeling frameworks have been introduced to solve river sediment problems. The present survey is designed to provide an updated account of the latest and most relevant AI-based applications for modeling the sediment transport in river basin systems. The review is established to capture the subsequent developments in the advanced AI models applied for river sediment transport prediction. Also, several hydrological and environmental aspects are identified and analyzed according to the results produced in those studies. The merits and constraints of the well-established AI models are further discussed in much detail, particularly considering state-of-the art, modeling frameworks and their application-specific appraisal, and some of the key proposed future research directions. Together with the synthesis of such information to drive a new understanding of models and methodologies related to suspended river sediment prediction, this review provides a future research vision for hydrologists, water scientists, water resource engineers, oceanography and environmental planners.

Scholars have spent much time studying metal deposition procedures involving the deposition of electroless nickel, alloy, and composite coatings on various surfaces; the most current uses were feasible advantages of the coatings’ many good properties for achieving the final product innovation. Lately, these coatings have demonstrated intriguing wear and corrosion resistance features, resulting in several innovative macro-level developments. The notion of composite coating by co-deposition coating has been presented in this article. The characteristics of Ni–Pb alloy coatings were examined by inserting ZrO 2 particles into the electroless deposited solution. The stainless steel (SS) specimens have been electroless coated with Ni–Pb and ZrO 2 nanoparticles (size = 30–70 nm) at 0, 10, and 20 g/L amounts. The materials have been examined using scanning electron microscope and atomic force microscope, followed by wear-resistant and microhardness testing. According to the investigation findings, including inert particles improved the hardness magnitude and wearing resistance considerably. The base metal exhibited the highest wear rate at 10 N, while the wear rate decreased in the Ni–Pb– ZrO 2 -coated SS316L by 34%. The Vickers hardness magnitudes of the Ni–Pb– ZrO 2 -coated samples at different ZrO 2 contents (0, 10, and 20 g/L) were 19, 50, and 81%, respectively.

Climatic condition is triggering human health emergencies and earth’s surface changes. Anthropogenic activities, such as built-up expansion, transportation development, industrial works, and some extreme phases, are the main reason for climate change and global warming. Air pollutants are increased gradually due to anthropogenic activities and triggering the earth’s health. Nitrogen Dioxide (NO 2 ), Carbon Monoxide (CO), and Aerosol Optical Depth (AOD) are truthfully important for air quality measurement because those air pollutants are more harmful to the environment and human’s health. Earth observational Sentinel-5P is applied for monitoring the air pollutant and chemical conditions in the atmosphere from 2018 to 2021. The cloud computing-based Google Earth Engine (GEE) platform is applied for monitoring those air pollutants and chemical components in the atmosphere. The NO 2 variation indicates high during the time because of the anthropogenic activities. Carbon Monoxide (CO) is also located high between two 1-month different maps. The 2020 and 2021 results indicate AQI change is high where 2018 and 2019 indicates low AQI throughout the year. The Kolkata have seven AQI monitoring station where high nitrogen dioxide recorded 102 (2018), 48 (2019), 26 (2020) and 98 (2021), where Delhi AQI stations recorded 99 (2018), 49 (2019), 37 (2020), and 107 (2021). Delhi, Kolkata, Mumbai, Pune, and Chennai recorded huge fluctuations of air pollutants during the study periods, where ~ 50–60% NO 2 was recorded as high in the recent time. The AOD was noticed high in Uttar Pradesh in 2020. These results indicate that air pollutant investigation is much necessary for future planning and management otherwise; our planet earth is mostly affected by the anthropogenic and climatic conditions where maybe life does not exist.

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R2) during the testing phase (R2 = 0.95), whereas the other comparable models generated relatively lower values of R2 ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

This research signifies an attempt to apply composite coating by co-deposition coating and assessing, enhancement the Nickel coatings features, by adding the particles of silicon-carbide to solution of electrodeposited. Stainless steel specimens have been subject to electroplating coating utilizing Nickel and nanosilicon carbide particles (70-100 nm) with various amounts (16, 24, 32 and 40) g/L. After coating, the specimens were tested by SEM, AFM, impeded in a solution with 3.5 percent NaCl to investigate the corrosion performance. Then testing the microhardness, and wear resistance. Results obtained from this work showed a great reduction in corrosion currents caused by adding of inert nanoparticles. These enhancements had been detected on all conducted tests for corrosion and wear.

To comply with the new net zero greenhouse gas emissions (GHGs) target set by the United Kingdom government by 2050, different sectors including the industrial sector are required to take action to achieve this target. Improving the building envelope and production of clean energy on site are among the activities that should be considered by businesses to reduce their carbon emissions. This research analysis the current energy performance and carbon dioxide (CO2) emissions of an industrial building in Liverpool, UK utilizing the Integrated Environmental Solutions Virtual Environment (IESVE) software modeling. Then it has proposed some methods for improving the current performance and reduce the carbon footprint of the building. The results indicated that the installation of wall and floor insulation could decrease the energy usage and CO2 emissions of the building by about 56.39%. Additionally, the production of clean energy on site using solar photovoltaic (PV) panels could reduce the annual CO2 emissions by up to 16%. Furthermore, this research provided some figures about offsetting the rest of CO2 emissions using different international offsetting schemes to achieve carbon neutrality of the building.

The increase in cement production as a result of growing demand in the construction sector means an increase in energy consumption and CO2 emissions. These emissions are estimated at 7% of the global production of CO2. Ultra-high-performance concrete (UHPC) has excellent mechanical and durability characteristics. Nevertheless, it is costly and affects the environment due to its high amount of cement, which may reach 800–1000 kg/m3. In order to reduce the cement content, silica fume (SF) was utilized as a partial alternative to cement in the production of UHPC. Nevertheless, SF is very expensive. Therefore, the researchers investigated the use of supplementary cementitious materials cheaper than SF. Very limited review investigates addressed the impact of such materials on different properties of UHPC in comparison to that of SF. Thus, this study aims to summarize the effectiveness of using some common supplementary cementitious materials, including fly ashes (FA), ground granulated blast furnace slag (GGBS), metakaolin (MK) and rice husk ashes (RHA) in the manufacturing of UHPC, and comparing the performance of each material with that of SF. The comparison among these substances was also discussed. It has been found that RHA is considered a successful alternative to SF to produce UHPC with similar or even higher properties than SF. Moreover, FA, GGBS and MK can be utilized in combination with SF (as a partial substitute of SF) as a result of having less pozzolanic activity than SF.