Mehdi Jamei

University of Prince Edward Island | UPEI · Faculty of Engineering

Water quality (WQ) monitoring in the surface water resources is a crucial concern as it has an impact on human health and ecosystem equilibrium. An accurate simulation of river WQ indicators as a function of available variables with data mining techniques is not much explored by the researchers. In this study, two smart dual-preprocessing hybridize...

Recently, researchers have prioritized the accurate forecasting of the particulate matter (PM) air quality indicators PM2.5 and PM10 in urban and industrial locations due to their importance for the human health. However, accurate short-term forecasting via traditional data mining methods is limited due to the complex nature of these indices on hou...

Forecasting accurately suspended sediment load (SSL) in the basin is one of the most critical issues for river engineering, environment, and water resources management which effectively reduces flood damages. In this study, a new multi-criteria hybrid expert system comprised of empirical wavelet decomposition (EWT) integrated with Encoder-Decoder B...

Significant wave height is an average of the largest ocean waves, which are important for renewable and sustainable energy resource generation. A large significant wave height can cause beach erosion, and marine navigation problems in a storm. A novel data decomposition based deep learning modelling framework has been proposed where Multivariate Va...

The sodium adsorption ratio (SAR) is the most crucial irrigation water quality indicator to diagnose the suitability of agricultural water resources. Due to this reason, accurate forecasting of SAR in the absence of its time series , based on limited input sequences, is recently considered a challenging environmental issue on a monthly scale. This...

Evapotranspiration is one of agricultural water management's most significant and impactful hydrologic processes. A new multi-decomposition deep learning-based technique is proposed in this study to forecast weekly reference evapotranspiration (ET o) in western coastal regions of Australia (Redcliffe and Gold Coast). The time-varying filter-based e...

Reference evapotranspiration (ETo) is a vital factor of hydrological cycle and agricultural water management. ETo is also related to climatic demand conditions which generate large deficits in soil moisture and runoff in different regions and seasons that lead to uncertainties in drought warning systems. A novel multivariate variational mode decomp...

The influence of ultrasound on the rheological behavior of new phase change material (PCM) is investigated. The PCMs are made from natural biological materials containing silicon carbide (SiC) nanoparticles or expanded graphite (EG) powders with weight fractions of 0, 0.05, 0.1, and 0.2 %. The rheological behavior of PCM composites is tested by a r...

Since the building roof acts as hub for atmospheric sediment deposition, the attached microbes can enter rainwater storage tank with ease to cause health issue for rainwater users. This study aims to explore the trend of roof-top deposited microbes in the different areas of Ikorodu local Government Area at Lagos, Nigeria. This paper also tests the...

The total quantity of solar energy falling on a horizontal plane surface is the global solar exposure (GSE, i.e., total solar energy). Precise forecasting of GSE is important in many fields such as renewable energy, agriculture, and public health, particularly by the limited hydro-meteorological time series information. This research aims to develo...

Reference evapotranspiration can cause huge discrepancies in soil moisture and runoff which is responsible for uncertainties in drought warning systems. Reference evapotranspiration (ETo) is one of the major drought elements that leads to soil dryness, vegetation surfaces and transpiration. An innovative strategy is proposed based on Multivariate V...

Using explosive material to fragment rock masses is a common and economical method in surface mines. Nevertheless, this method can lead to some environmental problems in the surrounding regions. Flyrock is one of the most dangerous effects induced by blasting which needs to be estimated to reduce the potential risk of damage. In other words, the mi...

Several bridges failed because of scouring and erosion around the bridge elements. Hence, precise prediction of abutment scour is necessary for the safe design of bridges. In this research, experimental and computational investigations have been devoted based on 45 flume experiments carried out at the NIT Warangal, India. Three innovative ensemble-...

Surface soil moisture (SSM) is an essential variable in the interaction between the atmosphere and land surface. Microwave remote sensing is an efficient technique for providing SSM data on a global scale. The NASA’s Soil Moisture Active Passive (SMAP) mission retrieves high-quality SSM estimates based on L-band microwave observations. However, lim...

Dear Colleagues, The application of soft computing methods in engineering sciences, particularly water engineering, has received considerable attention in recent years. With their high capacity, these methods can address complex nonlinear engineering problems in the disciplines of regression and classification, and they have gradually replaced tra...

Electrical conductivity (EC) is a key water quality metric for predicting the salinity and mineralization. In this study, the 10-day-ahead EC of two Australian rivers, Albert River and Barratta Creek, was forecasted using a novel deep learning algorithm, i.e., the convolutional neural network combined with long short-term memory (CNN-LSTM) model. T...

Turbulent forced convective flow of hybrid and single nanofluids in a conical diffuser is investigated numerically. Simulations are conducted for various Reynolds (Re=10000-70000) and different concentrations (ϕ=0-1.5 vol%) at equal ratio of TiO 2 :SiO 2. The impact of using theoretical and experimental correlations for dynamic viscosity and therma...

Accurate estimation of the wetting distribution pattern (WDP) around the emitters of a drip irrigation system in sloping lands can minimize surface runoff losses by determining the placement status of plants and emitters. In this study, both experimental and computational efforts were made to estimate the WDP in sloping lands with drip irrigation....

of the empirical wavelet transform (EWT), discrete wavelet transforms (DWT), extended Kalman filter (EKF), two models of multilayer perceptrons (MLP), and group method of data handling (GMDH) neural networks. Two synoptic stations of Tabriz (semi-arid climate) and Rasht (humid climate) covering data period (1987–2019) were selected for forecasting....

Accurate forecasting of rainfall is extremely important due to its complex nature and enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant concentration levels. In this study, a new multi-decomposition deep learning-based technique was proposed to forecast monthly rainfall in Himalayan region of India (i.e., Har...

A robust short-term significant wave height (Hs) modelling framework based on an ensemble local mean decomposition method integrated with random forest (i.e., En-RLMD-RF) is developed. The robust local mean decomposition (RLMD) decomposed the Hs data series into three subseries; amplitude modulation, frequency modulation and the low-frequency produ...

Solar energy represents one of the most important renewable energy sources contributing to the energy transition process. Considering that the observation of daily global solar radiation (GSR) is not affordable in some parts of the globe, there is an imperative need to develop alternative ways to predict it. Therefore, the main objective of this st...

In recent years, the application of soft computing methods has received considerable attention in engineering sciences, especially in water engineering. With their high capacity, these approaches can solve serious nonlinear engineering problems in regression and classification fields and have gradually replaced the classical mathematical and regres...

Salak is one of the fruits plants in Southeast Asia; there are at least 30 cultivars of salak. The size, shape, skin color, sweetness or even flesh color will be different depending on the cultivar. Thus, classification of salak based on their cultivar become a daily job for the fruit farmers. There are many techniques that can be used for fruit cl...

Iraq is one of the countries in the Middle East that suffers from frequent droughts due to severe weather fluctuations. This study analyzed the precipitation data of 14 meteorological stations located in different climatic regions of Iraq for 50 years (1968-2017) to calculate the Standard Precipitation Index (SPI). Future precipitation projected fo...

Drought is a stochastic and recurring hydrological natural hazard that occurs due to a shortage of precipitation over a period of time. Drought forecasting in water resources systems has an important role in reducing devastating ecological and social impacts. However, due to the fluctuating nature of drought indicator time series, their forecasting...

In this work, Al2O3 and CuO nanoparticles were synthesized by a novel sol‐gel method. Then, water‐based Al2O3 and Al2O3‐CuO (50:50) nanofluids were produced by the two‐step method. The viscosity and thermal conductivity of nanofluids were determined for the concentration and temperature range of 0‐1.0 vol.% and 30‐60°C, respectively. Sodium dodecyl...

The cooling performance of biological water-silver nanofluid (NF) in three double-pipe heat exchangers with converging sinusoidal inner wall (SCDHX), converging inner wall (CDHX), and plain inner wall (PDHX) was examined numerically using the first and second laws of thermodynamics. The two-phase mixture model is employed to conduct the simulations...

One of the most important parameters in the design and implementation of drip irrigation systems is the accurate prediction of the wetting dimensions pattern around the emitters, which leads to the precise determination of the distance between the emitters and the drippers. This search provides a comprehensive experimental and computational investi...

Major emphasis presently being made is on using and optimizing more sustainable and renewable energy resources to tackle the upcoming energy demand challenges and probable scarcity induced by several socioeconomic variables. In this research a new hybrid model: combination of empirical wavelet transform (EWT) and Auto Encoder Decoder Bidirectional...

Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression...

Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash particles are expelled from coal-burning power plants. Coal combustion is an extremely prevalent source of air pollution, and resulting PM has substantial impacts on human health, especially in industrial zones. This paper aims to design a novel hybrid deep...

Accurate forecasting of the wave energy is crucial and has significant potential because every wave meter possesses an energy amount ranging from 30 to 40 kW along the shore. By harnessing, it does not produce toxic gases, which is a better alternative to the energies that use fossil fuels. In this research, a multi-stage Multivariate Variational M...

Rock mass deformation modulus (Em) is a key parameter that is needed to be determined when designing surface or underground rock engineering constructions. It is not easy to determine the deformability level of jointed rock mass at the laboratory; thus, researchers have suggested different in-situ test methods. Today, they are the best methods; tho...

Air overpressure (AOp) is a hazardous effect induced by the blasting method in surface mines. Therefore, it needs to be predicted to reduce the potential risk of damage. The aim of this study is to offer an efficient method to predict AOp using a cascaded forward neural network (CFNN) trained by Levenberg–Marquardt (LM) algorithm, called the CFNN-L...

Accurate water level forecasting is important to understand and provide an early warning of flood risk and discharge. It is also crucial for many plants and animal species that needs specific ranges of water level. This research focused on long term multi-step ahead forecasting of daily flood water level in duration of (2005-2021) at two stations (...

Accurate ahead forecasting of reference evapotranspiration (ET o) is crucial for effective irrigation scheduling and management of water resources on a regional scale. A variety of methods are available for ET o simulation, but the most trending is complementary artificial intelligence (AI) paradigms. In this research, a novel Multivariate Variatio...

Brittleness plays an important role in assessing the stability of the surrounding rock mass in deep underground projects. To this end, the present study deals with developing a robust evolutionary programming paradigm known as linear genetic programming (LGP) for estimating the brittleness index (BI). In addition, the bootstrap aggregate (Bagged) r...

The present paper deals with 3D numerical analysis of a battery thermal management system (TMS) including the Phase Change Material (PCM). The TSM comprises three annular fins located around the battery considering the tip clearance (TC) space between the fin tips and the alumina enclosure. The calculations were performed for four cases with differ...

The rising salinity trend in the country’s coastal groundwater has reached an alarming rate due to the unplanned use of groundwater in agriculture and seawater seeping into the underground due to sea-level rise caused by global warming. Therefore, assessing salinity is crucial for the status of safe groundwater in coastal aquifers. In this research...

Solar energy represents one of the most important renewable energy sources contributing to the energy transition process. Considering that the observation of daily global solar radiation (GSR) is not affordable in some parts of the globe, there is an imperative need to develop alternative ways to predict it. Therefore, the main objective of this st...

The development of an accurate soft computing method for groundwater level (GWL) forecasting is essential for enhancing the planning and management of water resources. Over the past two decades, significant progress has been made in GWL prediction using machine learning (ML) models. Several review articles have been published, reporting the advanc...

Reference evapotranspiration (ET o) is one of the most important and influential components in optimizing agricultural water consumption and water resources management. In the present study, an efficient deep learning model, Auto Encoder Decoder Bidirectional Long Short-Term Memory (AED-BiLSTM), was applied for the first time in forecasting 1-3 wee...

The aim of this study is to determine the effect of nanoparticle concentration (φ) and temperature on the thermal conductivity of polyethylene glycol (PEG)-carbon dot nanofluid (NF). The considered range for temperature and φ is 20–60 °C and 0–7%, respectively. The results indicated an ascending trend of NF thermal conductivity with boosting both t...

Prediction of soil temperature (ST) at multiple depths is of great importance for maintaining the physical, chemical, and biological activities in soil for various scientific aspects. The present study was conducted in a semi-arid region of Punjab to predict the daily ST at 5 (ST5), 15 (ST15), and 30 (ST30) depths by employing the three-hybrid mach...

One of the critical factors in the optimal design of drip-fertigation systems is determining the distribution of nitrate in the soil. Handling such a complex non-linear process is challenging. The main goal of this study is to develop an accurate hybrid Boruta Random Forest (BRF)-Whale Optimization Algorithm (WOA) integrated with an Artificial Neur...

The root zone soil moisture (RZSM) is essential for monitoring and forecasting agricultural, hydrological, and meteorological systems. Accordingly, researchers are determined to improve robust machine learning (ML) models to increase the accuracy of the RZSM predictions. This paper designed new complementary forecasting paradigms hybridizing Empiri...

In the present study, the application of six engine oil-based Nano fluids (NFs) in a solar concentrating photovoltaic thermal (CPVT) collector is investigated. The calculations were performed for different values of nanoparticle volume concentration, receiver tube diameter, concentrator surface area, receiver length, receiver actual to the maximum...

A 3-D numerical investigation is performed to evaluate the effect of variable twist pitch on the hydrothermal behavior and entropy generation features of non-Newtonian water-CMC/CuO nanofluid (NF) flow inside a twisted tube with a square cross-section. Three twisted tubes with a length of 500 mm, each of which has 3 twists, are considered. The firs...

Accurate estimation of the thermal conductivity of nanofluids plays a key role in industrial heat transfer applications. Currently available experimental and empirical relationships can be used to estimate thermal conductivity. However, since the environmental conditions and properties of the nanofluids constituents are not considered these models...

In the present study, the polyethylene glycol 200 (PEG200)-based nanofluid containing carbon dot (CD) nanoparticles was synthesized, and its rheological behavior at different temperatures and nanoparticle concentrations (φ) was investigated. The values considered for φ were 0%, 1% and 3% and 7% the values considered for temperature were 20, 30, 40,...

Abstract Solar energy is becoming more popular as it is a clean source of electricity. The design of photovoltaic (PV) cells has therefore captivated experts worldwide. The two key issues are the lack of an excellent model to define solar cells and the lack of data regarding PV cells. This scenario even impacts solar module performance (panels). Th...

Predictions of Earth skin temperature (EST) can provide essential information for diverse engineering applications such as energy harvesting and agriculture activities. Several synoptic climate parameters influence EST, and its prediction and quantification is highly complex and challenging. The current research uses three different machine learnin...

Two-phase flow modeling has a crucial role in detecting pollution in aquifers and/or immiscible flow simulation through porous media. In this research, a new hybrid numerical method based on the lower order non-conforming finite element method (NCFEM) and interior penalty discontinuous Galerkin (DG) method is proposed to simulate two-phase incompre...

Solar energy is one of the most important renewable energy sources. Assessing the solar potential of area needs analyzed information about the dataset of the measured global solar radiation (GSR). Recently, researches detected the high potential of state-of-the-art artificial intelligence (AI) methods in estimating the GSR successfully. In this stu...

Exploration of incipient motion study is significantly important for the river hydraulics community. The present study, along with experimental investigation, considered a new multi-level ensemble machine learning (ML) to determine critical shear stress (CSS) of gravel particles in a cohesive mixture of clay-silt-gravel, clay-silt-sand-gravel, and...

Sunshine duration is an important atmospheric indicator used in many agricultural, architectural, and solar energy applications (photovoltaics, thermal systems, and passive building design). Hence, it should be estimated accurately for areas with low-quality data or unavailable precise measurements. This paper aimed to obtain a sunshine duration me...

Many researchers have considered the data-driven methods (DDM) in recent decades to solve complex and nonlinear engineering problems: finance, marketing, management, and environmental sciences. These methods can establish a connection between the independent and dependent parameters of a system with significant accuracy without the need for the phy...

Drought is a common environmental disaster strongly influenced by the potential production of agricultural products, lack of water resources, and yields destructive effects on the economy. In this study, the prediction of a novel monthly combined terrestrial evapotranspiration index (CTEI) was considered as a measure of all three types of drought (...

The hybrid nanofluids were used as absorber fluids in solar energy applications, which could further increase the efficiency of solar devices. The use of nanofluids in solar devices with the laminar and turbulent flow has received much attention. Presently, the effect of temperature and concentration on thermal conductivity and viscosity of fly ash...

Drought forecasting plays a vital role in managing drought and reducing its effects on agricultural systems and water resources. In the present study, three machine learning models including, Gaussian Process Regression (GPR), Cascade Neural Network (Cascade-NN), and Multilayer Perceptron (MLP) neural network and their combination with the discrete...

In the current study, three machine learning (ML) models, i.e. Gaussian process regression (GPR), generalized regression neural network (GRNN), and multigene genetic programming (MGGP), were developed for predicting the discharge coefficient (Cd) of a radial gate under two different flow conditions, i.e. free and submerged. The modeling development...

The purpose of the current research work is to investigate the various properties like thermal conductivity, stability and viscosity of copper and a mixture of fly ash-Copper (FA:Cu) nanoparticles (NP) suspended in water. The research experiments were conducted for a concentration of 1.0 vol% of FA:Cu hybrid nanofluid (HNF) with various mixture rat...

Spur dike has been widely used as one of the river training structures to increase the stability of riverbanks and embankments. Scour around spur dikes affects their hydraulic performance and stability. Hence, the precise calculation of scour depth variation with time at spur dikes is essential to the design of safe and economical spur dikes. This...

Soil moisture content (SMC) prediction can contribute to diverse geo-science engineering applications such as plantation, crops production, and several irrigation activities. Although, there have been several methodologies introduced for the SMS estimation, methods are still associated with challenges and limitations (e.g., time-consuming, high cos...

There is no doubt that density is one of the most crucial thermophysical properties of hybrid nanofluids in thermal energy applications. Various research papers have been devoted to thermophysical properties of various hybrid nanofluids. However, a few of them focused on the simultaneous effects of nanoparticles, base fluids, and other factors on t...

In the present study, two kernel-based data-intelligence paradigms, namely, Gaussian Process Regression (GPR) and Kernel Extreme Learning Machine (KELM) along with Generalized Regression Neural Network (GRNN) and Response Surface Methodology (RSM), as the validated schemes, employed to precisely estimate the elliptical side orifice discharge coeffi...

This paper aims to study the thermophysical properties of water, water and ethylene glycol mixture-based nanodiamond+Fe3O4 hybrid nanofluids experimentally and numerically using two data-driven approaches, namely, Multivariate linear regression (MLR) and Multivariate linear regression with interaction (MLRI) models. Three types of base fluids, such...

The concentration of soluble salts in surface water and rivers such as sodium, sulfate, chloride, magnesium ions, etc., plays an important role in the water salinity. Therefore, accurate determination of the distribution pattern of these ions can improve better management of drinking water resources and human health. The main goal of this research...

The main goal of this research is to develop a 3D groundwater (GW) model using MODFLOW software to assess the potential effect of increasing pumping discharges on GW level in the Nile Delta Aquifer (NDA). In this study, the current state of the irrigation canals and GW recharge are considered in the GW model. The simulated GW level was compared wit...