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Showing 4 results for Ghanbari

Mr Mani Ghanbari, Dr Gholamhassan Najafi, Dr Barat Ghobadian,
Volume 10, Issue 4 (12-2020)

In this paper, the exhaust emissions of a diesel engine operating with different nanoparticles additives in diesel-biodiesel blended fuels were investigated. Firstly multi wall carbon nano tubes (CNT) with concentrations of 40, 80 and 120 ppm and nano silver particles of 40, 80 and 120 ppm with nano-structure were produced and then added as additives to the diesel-biodiesel blended fuels. A four-stroke six cylinders diesel engine was fuelled with the new fuels and operated at different engine speeds. The experimental results showed that CO2 emission increased by 17% with an increase in nanoparticles concentrations at diesel-biodiesel blended fuel. Also, CO emission with nanoparticles added to biodiesel-diesel fuel was 25.17% lower than neat diesel fuel. The results showed a decrease up to 28.56% in UHC emission using the silver nano-diesel-biodiesel blended fuel. NOx emission increased with adding nanoparticles to the blended fuels compared to the neat diesel fuel. The experimental results demonstrated that silver & CNT nanoparticles can effectively be used as additive in diesel-biodiesel blended fuel in order to enhance complete combustion of the air-fuel mixture and reduce the exhaust emissions. Consequently the nano biodiesel can be considered as an alternative and environment friendly fuel for CI engine. 

Mani Ghanbari, Lotfali Mozafarivanani, Masoud Dehghanisoufi,
Volume 11, Issue 3 (9-2021)

The fuel system in internal combustion engines is one of the most accurate and sensitive parts and its operation has a significant effect on the quality of combustion process and the content of exhaust emissions. In this study, the effect of fuel filter life on lambda and exhaust emissions of engine has been investigated using the response surface method (RSM). The results showed that the elevated values of lambda (1.042) and CO (0.88%) occur at the engine speed of 5000 rpm with a fuel filter life (FFL) of 60,000 km. Also, the highest CO2 content was obtained as 14.9% at 1000 rpm with a new fuel filter (0 km). Moreover, the highest amount of HC emission (215 ppm) was measured at 1000 rpm and using FFL of 60,000 km. The results showed that increasing the fuel filter life increases the exhaust emissions of the engine. Therefore, timely replacement of the fuel filter, in addition to increasing engine performance, will reduce air pollution, especially in big cities. 

Abolfazl Ghanbari Barzian, Mohammad Saadat, Hossein Saeedi Masine,
Volume 12, Issue 1 (3-2022)

Environmental pollution and reduction of fossil fuel resources can be considered as the most important challenges for human society in the recent years. The results of previous studies show that the main consumer of fossil fuels and, consequently, most of the air pollutants, is related to the transportation industry and especially cars. The increasing growth of vehicles, the increase in traffic and the decrease in the average speed of inner-city vehicles have led to a sharp increase in fuel consumption. To address this problem, automakers have proposed the development and commercialization of hybrid vehicles as an alternative to internal combustion vehicles. In this paper, the design of an energy management system in a fuel-cell hybrid vehicle based on the look-ahead fuzzy control is considered. The preparation of fuzzy rules and the design of membership functions is based on the fuel efficiency curve of the fuel-cell. In look-ahead fuzzy control, the ahead conditions of the vehicle are the basis for decision in terms of slope and speed limit due to path curves as well as battery charge level. The fuzzy controller will determine the on or off status of the fuel-cell, as well as the power required. The motion of the fuel-cell hybrid vehicle on a real road is simulated and the performance of the proposed look-ahead controller is compared with the base controller (thermostatic method). The simulation results show that using the proposed approach can reduce the fuel consumption of the fuel-cell hybrid vehicle as well as travel time.
Hossein Ghanbari, Mostafa Shabani, Dr Emran Mohammadi,
Volume 13, Issue 4 (12-2023)

Portfolio optimization is the process of distributing a specific amount of wealth across various available assets, with the aim of achieving the highest possible returns while minimizing investment risks. There are a large number of studies on portfolio optimization in various cases, covering numerous applications; however, none have focused exclusively on the automotive industry as one of the largest manufacturing sectors in the global economy. Since the economic activity of this industry has a coherent pattern with that of the global economy, the automotive industry is very sensitive to the booms and busts of business cycles. Due to the volatile global economic environment and significant inter-industry implications, providing an appropriate approach to investing in this sector is essential. Thus, this paper aims to provide an appropriate approach to investing in this sector. In this study, an extended Conditional Drawdown at Risk (CDaR) model with cardinality and threshold constraints for portfolio optimization problems is proposed, which is highly beneficial in practical portfolio management. The feature of this risk management technique is that it admits the formulation of a portfolio optimization model as a linear programming problem. The CDaR risk functions family also enables a risk manager to control the worst ( 1-α)×100%  drawdowns. In order to demonstrate the effectiveness of the proposed model, a real-world empirical case study from the annual financial statements of automotive companies and their suppliers in the Tehran Stock Exchange (TSE) database is utilized.

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