mahdi keyhanpour

This study develops and validates a simplified testing methodology aligned with UNECE Regulation No. 49 to quantify particle number (PN) emissions from diesel vehicles. A modified World Harmonized Vehicle Cycle (WHVC) was implemented, incorporating steady-state operational segments (urban: 21.3 km/h, rural: 43.6 km/h, motorway: 76.7 km/h), and applied to evaluate 51 Iranian-manufactured diesel vehicles. The tested fleet comprised heavy-duty trucks, buses, and pickup trucks equipped with diverse propulsion systems (e.g., ISF3.8s5154, OM457LA.IV) and after-treatment technologies, including SCR, DOC, and DPF. Results demonstrate that original equipment manufacturer (OEM)-installed DPFs reduced PN emissions by 7000-fold compared to non-DPF-equipped vehicles (2.49 × 10¹⁰ vs. 1.74 × 10¹⁴ particles/km; p < 0.001). Euro VI-compliant vehicles exhibited the lowest emissions (6.01 × 10¹⁰ particles/km), outperforming Euro V and Enhanced Environmentally Friendly Vehicle (EEV) standards. These findings underscore the necessity of adopting OEM-grade filtration systems and enforcing stringent emission regulations, such as Euro VI, to mitigate particulate pollution in urban environments. The methodology provides a replicable framework for emerging markets to align with global emission compliance protocols.

The limitation of fossil energy sources and environmental concerns have caused efforts to use clean and sustainable energy sources. The solid oxide fuel cell with intermediate working temperature and ammonia fuel is one of the promising sources to replace conventional energy sources. On the other hand, the use of fuel cell performance prediction methods with appropriate and high accuracy and speed is significantly important. In this research, first, the solid oxide fuel cell with ammonia fuel, electrolyte leakage, and average working temperature are numerically simulated. Then the effective input parameters are selected to calculate the performance of the fuel cell in different conditions. In this regard, after generating a sufficient data set, different machine learning algorithms are used to predict the objective functions, including the power density and the maximum temperature of the fuel cell. The results indicate the complexity of predicting the power density of the fuel cell compared to the maximum temperature. It was also observed that the XG Boosting method with R2 equal to 0.99 has the best efficiency in predicting the parameters of maximum temperature and power density.

rapid population growth will increase the need for renewable energy resources. On the other hand, the extent of pollution from fossil fuels has made life on Earth difficult. However, the need to choose a suitable, cheap and clean alternative to fossil fuels is obvious. One of the proposed energy sources is electrical energy generated by fuel cells, which are currently a suitable solution due to high efficiency, non-pollution of the environment and the use of hydrogen as fuel. In this research, a solid oxide fuel cell with two different geometries is simulated in three dimensions. The equations governing the performance of the fuel cell, including electrochemical, momentum, mass transfer, and energy, are coupled using a finite element code defined, solved, and investigated. The results showed that the tubular geometry with the same dimensions and mechanical characteristics has a better performance than the planar type. It was shown that solving the energy equation and non-uniform temperature distribution reduces the power density of the fuel cell by about 7%. It was also found that cathodic pressure changes have a greater effect on fuel cell performance than anodic pressure changes. In the end, the results showed that increasing the thickness of the anode has a significant effect on increasing its performance compared to increasing the thickness of other fuel cell components.

Cardiovascular diseases have been one of the main causes of death throughout the world in recent decades.One of the most common heart diseases is stenotic arteries, which usually appears with middle age. This disease, called atherosclerosis, causes an abnormal reduction in the inside diameter of blood vessels. In this study, the effect of a uniform magnetic field on blood flow and artery walls is investigated. The geometry of the problem is simulated in three dimensions. The governing equations, which include continuity, momentum, ohm’s law, stress-strain of linear elastic material, and fluid-solid interaction with moving mesh method, are defined, coupled, and solved with a finite element code in the Comsol software.The results indicate that the magnetic field has a significant effect on the behavior of blood flow and artery walls. For example, the Hartmann number is inversely related to the blood flow velocity and is directly related to the wall shear stress, the von Mises stress, and the artery wall displacement. It is also observed that the trend of changes with non-Newtonian viscosity model is greater than the Newtonian model.

One of the most common cardiovascular deseases is stenotic arteries. In this study, blood flow with different models of viscosity in a stenotic artery with the assumption of a wall has been investigated. Stenosis geometry is modeled by cosine relation. for The problem equations including continuity, momentum, energy, Hooke's law for linear elastic material, and the method (ALE) for fluid-solid interaction are defined and solved as finite element code. The results showed that the vessel wall had the most displacement near the stenosis region. Assuming the fluid-solid interaction reduces the wall shear stres. For example, the maximum wall shear stress in the stenotic region decreases from 2.32 to 2.23 with Carreau viscosity and from 2.1 to 2 with Newtonian viscosity. It was also observed that applying heat flux on the outer surface of the vessel wall causes a significant increase in blood flow and the wall temperature in the stenotic region.

The purpose of this study is the numerical analysis of hyperthermia on the damage of cancerous tissue in the presence of magnetic nanoparticles under the influence of external magnetic field. For this purpose the governing equations continuity, momentum, energy and arrhenius damage equation are coupled and solved by COMSOL, a finite element based code. The blood flow in capillary is assumed as non-newtonian fluid with the Carreau viscosity model. A three dimensional geometric model includes the capillary and surrounding tissue. The results indicated that the temperature of the blood stream increases with the application of the magnetic field, and the surrounding tissue is damaged over time as a result of this heat. The effect of field strength and concentration was also investigated, which was found to correlate with the amount of damaged tissue. In general, this method can be used to degrade the tissues by placing the nearby magnetic field and injecting nanoparticles at low scales.

In this study, numerically investigated effect of magnetic heat sources (residual and hysteresis) that can be useful in hyperthermia and their effects on cancerous tissue. The governing equations of continuty, momentum, concentration, energy and Arrhenius tissue destruction equation in the form of couplings are defined, solved and investigated in the finite-element COMSOL software. For blood flow inside the cancerous capillary, non-newtonian and temperature dependent model is used. The geometric model is simulated in three dimensions, including the capillary and cancerous tissue. Thermophysical properties of blood and tissue are also temperature dependent. Results indicated that the residual heat source plays a major role in increasing the temperature of the blood and tissue and can be ignored the effect of hysteresis heat source. The residual heat source has an inverse relation to the particle size and is ineffective in the particle size above 100 nm but hysteresis heat source is directly related to the size of the nanoparticles, and for particles with a size of 150 nm, it will result in a 1 degree increase in temperature for the tissue. The increase in blood temperature for 25 nm magnetic nanoparticles with the residual heat source can lead to the most destruction in cancerous tissue. Also, the viscosity of blood has an inverse relation with the concentration of magnetic nanoparticles in the capillary wall and blood temperature.