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Alibek Issakhov
Al-Farabi Kazakh National University, Almaty, Kazakhstan

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Journal article
Published: 19 August 2021 in Energy Reports
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Due to its inherent ability of augmenting power system stability limit while maintaining good electric Power Quality (PQ), Power System Stabilizer (PSS) is envisaged to be an effective device in numerous Distributed Generation (DG) applications. It becomes a paramount work to maintain stable frequency, and alleviate the utility-grid collapse. Owing to this, this paper evaluates the performance of generic, and Multiband (MB)-PSSs for a hybrid 9 MW wind farm connected with mini/micro hydro power plant. The proposed system is interfaced with 200 MVA, 25 kV utility-grid system. A comparative analysis in the performance of a generic-PSS is presented with a MB-PSS at various voltage level points and power flows at various Point of Common Couplings (PCC) are analysed. Transient analysis is carried out during the presence of various unsymmetrical faults. It is envisaged that transients and unbalanced voltage sag-swells are mitigated at various PCCs while maintaining uninterruptable real and reactive power flows. The superiority of MB-PSS is established over generic-PSS in maintaining optimal PQ flow. Consequently, the reactive power requirement of the connected load is compensated by wind and mini/micro hydro controlling schemes using MB-PSS. Overall, the accurateness of the developed simulink models is demonstrated and satisfactory results are obtained in comparative analysis of both stabilizers.

ACS Style

Kamal Kant Sharma; Akhil Gupta; Gagandeep Kaur; Raman Kumar; Jasgurpreet Singh Chohan; Shubham Sharma; Jujhar Singh; Nima Khalilpoor; Alibek Issakhov. Power quality and transient analysis for a utility-tied interfaced distributed hybrid wind-hydro controls renewable energy generation system using generic and multiband power system stabilizers. Energy Reports 2021, 7, 5034 -5044.

AMA Style

Kamal Kant Sharma, Akhil Gupta, Gagandeep Kaur, Raman Kumar, Jasgurpreet Singh Chohan, Shubham Sharma, Jujhar Singh, Nima Khalilpoor, Alibek Issakhov. Power quality and transient analysis for a utility-tied interfaced distributed hybrid wind-hydro controls renewable energy generation system using generic and multiband power system stabilizers. Energy Reports. 2021; 7 ():5034-5044.

Chicago/Turabian Style

Kamal Kant Sharma; Akhil Gupta; Gagandeep Kaur; Raman Kumar; Jasgurpreet Singh Chohan; Shubham Sharma; Jujhar Singh; Nima Khalilpoor; Alibek Issakhov. 2021. "Power quality and transient analysis for a utility-tied interfaced distributed hybrid wind-hydro controls renewable energy generation system using generic and multiband power system stabilizers." Energy Reports 7, no. : 5034-5044.

Article
Published: 12 August 2021 in Wireless Personal Communications
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Network intrusion detection systems analyze traffic in a medical IoT system to detect abnormal behaviors. Machine learning and artificial intelligence (AI) algorithms are widely used in designing intrusion detection systems to prevent attacks on a medical IoT system. In this paper, an artificial neural network is employed to detect abnormal behavior in a medical IoT system. The accuracy of the detection depends heavily on the features that are fed into the artificial neural network. Selecting the important and discriminative features of network traffic is a crucial and challenging issue because it has a significant impact on the learning process. In the proposed method, the butterfly optimization algorithm which is a meta-heuristic optimization algorithm is employed to select the optimal features for the learning process in an artificial neural network. The results achieved, 93.27% accuracy, indicate the capability of the butterfly optimization algorithm to determine discriminative features of network traffic data. The proposed algorithm outperformed the decision tree, support vector machine, and ant colony optimization, which was proposed in previous researches for the same goal.

ACS Style

Ya Li; Seyed-Mohsen Ghoreishi; Alibek Issakhov. Improving the Accuracy of Network Intrusion Detection System in Medical IoT Systems through Butterfly Optimization Algorithm. Wireless Personal Communications 2021, 1 -19.

AMA Style

Ya Li, Seyed-Mohsen Ghoreishi, Alibek Issakhov. Improving the Accuracy of Network Intrusion Detection System in Medical IoT Systems through Butterfly Optimization Algorithm. Wireless Personal Communications. 2021; ():1-19.

Chicago/Turabian Style

Ya Li; Seyed-Mohsen Ghoreishi; Alibek Issakhov. 2021. "Improving the Accuracy of Network Intrusion Detection System in Medical IoT Systems through Butterfly Optimization Algorithm." Wireless Personal Communications , no. : 1-19.

Journal article
Published: 05 August 2021 in Sustainability
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The emerging environmental consequences of overdependence on fossil fuels have pushed many countries to invest in clean and renewable sources of power. Countries like Iran where these sources can be found in abundance can take advantage of this potential to reduce their dependence on fossil fuels. This study investigated the feasibility of the standalone use of a hybrid renewable energy system (HRES) to power buildings in the Bostegan village in the Hormozgan province of Iran. Technical, economic, and environmental assessments were performed with the help of the Hybrid Optimization of Multiple Energy Resources (HOMER) software, and the optimal configuration for the system components was determined accordingly. The results showed that the simultaneous use of wind and solar systems with a converter and a backup system comprised of a diesel generator and batteries will be the most economic option, offering electricity at a cost of 1.058 USD/kWh and with a renewable fraction of 64%. After selecting the most optimal system using the step-wise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assessment (WASPAS) techniques, a sensitivity analysis with 27 parameter settings was performed to determine the effect of fuel price fluctuations and the uncertainty in the renewable energy potentials on the results. This analysis showed that in the worst-case scenario, the price of electricity will reach as high as 1.343 $/kWh. In the end, the study investigated an alternative scenario where the generated power is used for hydrogen production, which showed that the system output can be used to produce 643.63 ton-H2/year.

ACS Style

Khalid Almutairi; Seyyed Hosseini Dehshiri; Seyyed Hosseini Dehshiri; Ali Mostafaeipour; Alibek Issakhov; Kuaanan Techato. Use of a Hybrid Wind—Solar—Diesel—Battery Energy System to Power Buildings in Remote Areas: A Case Study. Sustainability 2021, 13, 8764 .

AMA Style

Khalid Almutairi, Seyyed Hosseini Dehshiri, Seyyed Hosseini Dehshiri, Ali Mostafaeipour, Alibek Issakhov, Kuaanan Techato. Use of a Hybrid Wind—Solar—Diesel—Battery Energy System to Power Buildings in Remote Areas: A Case Study. Sustainability. 2021; 13 (16):8764.

Chicago/Turabian Style

Khalid Almutairi; Seyyed Hosseini Dehshiri; Seyyed Hosseini Dehshiri; Ali Mostafaeipour; Alibek Issakhov; Kuaanan Techato. 2021. "Use of a Hybrid Wind—Solar—Diesel—Battery Energy System to Power Buildings in Remote Areas: A Case Study." Sustainability 13, no. 16: 8764.

Original paper exploration engineering
Published: 08 July 2021 in Journal of Petroleum Exploration and Production Technology
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Power consumption of wellbore drilling in oil and gas exploitations count for 40% of total costs, hence power saving of WBM (water-based mud) by adding different concentrations of Al2O3, TiO2 and SiO2 nanoparticles is investigated here. A high-speed Taylor–Couette system (TCS) was devised to operate at speeds 0–1600 RPM to simulate power consumption of wellbore drilling using nanofluids in laminar to turbulent flow conditions. The TCS control unit uses several sensors to record current, voltage and rotational speed and Arduino microprocessors to process outputs including rheological properties and power consumption. Total power consumption of the TCS was correlated with a second-order polynomial function of rotational speed for different nanofluids, and the correlated parameters were found using an optimization technique. For the first time, energy saving of three nanofluids at four low volume concentrations 0.05, 0.1, 0.5 and 1% is investigated in the TCS simulating wellbore drilling operation. It is interesting to observe that the lower concentration nanofluids (0.05%) have better power savings. In average, for the lower concentration nanofluids (0.05%), power was saved by 39%, 30% and 26% for TiO2, Al2O3 and SiO2 WBM nanofluids, respectively. TiO2 nanofluids have better power saving at lower concentrations of 0.05 and 0.1%, while Al2O3 nanofluids have saved more power at higher concentrations of 0.5 and 1.0% compared with their counterpart nanofluids.

ACS Style

Masoud Rashidi; Ahmad Sedaghat; Biltayib Misbah; Mohammad Sabati; Koshy Vaidyan; Ali Mostafaeipour; Seyyed Shahabaddin Hosseini Dehshiri; Khalid Almutairi; Alibek Issakhov; Seyed Amir Abbas Oloomi; Mahdi Ashtian Malayer; Joshuva Arockia Dhanraj. Simulation of Wellbore Drilling Energy Saving of Nanofluids Using an Experimental Taylor–Couette Flow System. Journal of Petroleum Exploration and Production Technology 2021, 11, 2963 -2979.

AMA Style

Masoud Rashidi, Ahmad Sedaghat, Biltayib Misbah, Mohammad Sabati, Koshy Vaidyan, Ali Mostafaeipour, Seyyed Shahabaddin Hosseini Dehshiri, Khalid Almutairi, Alibek Issakhov, Seyed Amir Abbas Oloomi, Mahdi Ashtian Malayer, Joshuva Arockia Dhanraj. Simulation of Wellbore Drilling Energy Saving of Nanofluids Using an Experimental Taylor–Couette Flow System. Journal of Petroleum Exploration and Production Technology. 2021; 11 (7):2963-2979.

Chicago/Turabian Style

Masoud Rashidi; Ahmad Sedaghat; Biltayib Misbah; Mohammad Sabati; Koshy Vaidyan; Ali Mostafaeipour; Seyyed Shahabaddin Hosseini Dehshiri; Khalid Almutairi; Alibek Issakhov; Seyed Amir Abbas Oloomi; Mahdi Ashtian Malayer; Joshuva Arockia Dhanraj. 2021. "Simulation of Wellbore Drilling Energy Saving of Nanofluids Using an Experimental Taylor–Couette Flow System." Journal of Petroleum Exploration and Production Technology 11, no. 7: 2963-2979.

Journal article
Published: 29 June 2021 in Sustainable Energy Technologies and Assessments
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Transient performance assessment and techno-economic analysis are presented for a novel smart energy system driven by hybrid solar-Hydrogen energies. The proposed system is developed to provide power, heating, and cooling demands for a two-story building as the case study. In detail, the system is composed of photovoltaic thermal panels, fuel cells, thermal energy storage, solar collector, and a small-scale Organic Rankin Cycle. To generate the heating and cooling of a heat pump, an absorption chiller is occupied. The system is analyzed from technical and economic standpoints as well as environmental considerations. To find the best solution point for the system, a tri-objective optimization as a cutting-edge method to optimize all the mentioned indexes is conducted. The system is grid-connected, and the excess power could be sold to the power grid. The results show that the 19.92 kWh power can be sold to the grid, and the heating and cooling load demand are amended. Moreover, at the optimized point, the plant can accomplish the minimum cost and emission of 0.37 Ton/MWh and 8.46 $/GJ, respectively, while the yearly efficiency reaches 37.28%. In conclusion, this study has highlighted the potential of solar-driven micro-CCHP systems based on advanced technologies for residential applications.

ACS Style

Fereydoun Bahramian; Amin Akbari; Miralireza Nabavi; Saeed Esfandi; Esfandiyar Naeiji; Alibek Issakhov. Design and tri-objective optimization of an energy plant integrated with near-zero energy building including energy storage: An application of dynamic simulation. Sustainable Energy Technologies and Assessments 2021, 47, 101419 .

AMA Style

Fereydoun Bahramian, Amin Akbari, Miralireza Nabavi, Saeed Esfandi, Esfandiyar Naeiji, Alibek Issakhov. Design and tri-objective optimization of an energy plant integrated with near-zero energy building including energy storage: An application of dynamic simulation. Sustainable Energy Technologies and Assessments. 2021; 47 ():101419.

Chicago/Turabian Style

Fereydoun Bahramian; Amin Akbari; Miralireza Nabavi; Saeed Esfandi; Esfandiyar Naeiji; Alibek Issakhov. 2021. "Design and tri-objective optimization of an energy plant integrated with near-zero energy building including energy storage: An application of dynamic simulation." Sustainable Energy Technologies and Assessments 47, no. : 101419.

Original article
Published: 22 May 2021 in Engineering with Computers
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In this study, frequency simulation and critical angular velocity of a size-dependent laminated rotary microsystem using modified couple stress theory (MCST) as the higher-order elasticity model is undertaken. The centrifugal and Coriolis impacts due to the spinning are taken into account. The size-dependent thick annular microsystem's computational formulation, non-classical governing equations, and corresponding boundary conditions are obtained by using the higher-order stress tensors and symmetric rotation gradient to the strain energy. By using a single material length scale factor, the most recent non-classical approach captures the size-dependency in the annular laminated microsystem. Furthermore, by ignoring the length scale element of the material, an annular microsystem’s mathematical formulation based on the classical model can be retrieved from the current model. Ultimately, the governing equations, which are non-classic, have been solved for various boundary conditions (BCs) using the two-dimensional generalized differential quadrature (2D-GDQ) approach. The effects of Young's modulus ratio the, rotating speed, radius ratio, laminated layers’ number, length scale element, and laminated types on the critical rotating speed and frequency responses of the laminated spinning microdisk are then investigated using MCST. The outcomes reveal that the negative influence from spinning velocity on the system’s dynamics is more significant than the negative influence from radius ratio, and the mentioned problem is more considerable for the vertical laminated pattern. Finally, the critical radius ratio and rotating speed increase by changing the laminated pattern from vertical to longitudinal.

ACS Style

Hui Liu; Yao Zhao; Mohammad Pishbin; Mostafa Habibi; M-O Bashir; Alibek Issakhov. A comprehensive mathematical simulation of the composite size-dependent rotary 3D microsystem via two-dimensional generalized differential quadrature method. Engineering with Computers 2021, 1 -16.

AMA Style

Hui Liu, Yao Zhao, Mohammad Pishbin, Mostafa Habibi, M-O Bashir, Alibek Issakhov. A comprehensive mathematical simulation of the composite size-dependent rotary 3D microsystem via two-dimensional generalized differential quadrature method. Engineering with Computers. 2021; ():1-16.

Chicago/Turabian Style

Hui Liu; Yao Zhao; Mohammad Pishbin; Mostafa Habibi; M-O Bashir; Alibek Issakhov. 2021. "A comprehensive mathematical simulation of the composite size-dependent rotary 3D microsystem via two-dimensional generalized differential quadrature method." Engineering with Computers , no. : 1-16.

Journal article
Published: 21 April 2021 in Sustainability
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With the rising demand for food products and the direct impact of climate change on food production in many parts of the world, recent years have seen growing interest in the subject of food security and the role of rainfed farming in this area. Machine learning methods can be used to predict crop yield based on a combination of remote sensing data and data collected by ground weather stations. This paper argues that forecasting drylands farming yield can be reliable for management purpose under uncertain conditions using machine learning methods and remote sensing data and determines which indicators are most important in predicting the yield of chickpea. In this study, the yield of rainfed chickpea farms in 11 top chickpea producing counties in Kermanshah province, Iran, was predicted using three machine learning methods, namely support vector regression (SVR), random forest (RF), and K-nearest neighbors (KNN). To improve prediction accuracy, for each county, remote sensing data were overlaid by the satellite images of rainfed farms with a suitable slope and altitude for rainfed farming. An integrated database was created by combining weather data, remote sensing data, and chickpea yield statistics. The methods were evaluated using the leave-one-out cross-validation (LOOCV) technique and compared in terms of multiple measures. Given the sensitivity of rainfed chickpea yield to the time of data, the predictions were made in two scenarios: (1) using the averages of the data of all growing months, and (2) using the data of a combination of months. The results showed that RF provides more accurate yield predictions than other methods. The predictions of this method were 7–8% different from the statistics reported by the Statistical Center and the Ministry of Agriculture of Iran. It was found that for pre-harvest prediction of rainfed chickpea yield, using the data of the March–April period (the averages of two months) offers the best result in terms of the correlation coefficient for the relationship between the yield and the predictor indices.

ACS Style

Shahram Rezapour; Erfan Jooyandeh; Mohsen Ramezanzade; Ali Mostafaeipour; Mehdi Jahangiri; Alibek Issakhov; Shahariar Chowdhury; Kuaanan Techato. Forecasting Rainfed Agricultural Production in Arid and Semi-Arid Lands Using Learning Machine Methods: A Case Study. Sustainability 2021, 13, 4607 .

AMA Style

Shahram Rezapour, Erfan Jooyandeh, Mohsen Ramezanzade, Ali Mostafaeipour, Mehdi Jahangiri, Alibek Issakhov, Shahariar Chowdhury, Kuaanan Techato. Forecasting Rainfed Agricultural Production in Arid and Semi-Arid Lands Using Learning Machine Methods: A Case Study. Sustainability. 2021; 13 (9):4607.

Chicago/Turabian Style

Shahram Rezapour; Erfan Jooyandeh; Mohsen Ramezanzade; Ali Mostafaeipour; Mehdi Jahangiri; Alibek Issakhov; Shahariar Chowdhury; Kuaanan Techato. 2021. "Forecasting Rainfed Agricultural Production in Arid and Semi-Arid Lands Using Learning Machine Methods: A Case Study." Sustainability 13, no. 9: 4607.

Journal article
Published: 19 April 2021 in Sustainability
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Observing the growing energy demand of modern societies, many countries have recognized energy security as a looming problem and renewable energies as a solution to this issue. Renewable hydrogen production is an excellent method for the storage and transfer of energy generated by intermittent renewable sources such as wind and solar so that they can be used at a place and time of our choosing. In this study, the suitability of 15 cities in Fars province, Iran, for renewable hydrogen production was investigated and compared by the use of multiple multi-criteria decision-making methods including ARAS, SAW, CODAS, and TOPSIS. The obtained rankings were aggregated by rank averaging, Borda method, and Copeland method. Finally, the partially ordered set ranking technique was used to reach a general consensus about the ranking. The criteria that affect hydrogen production were found to be solar energy potential, wind energy potential, population, air temperature, natural disasters, altitude, relative humidity, land cost, skilled labor, infrastructure, topographic condition, and distance from main roads. These criteria were weighted using the best–worst method (BWM) based on the data collected by a questionnaire. Solar energy potential was estimated using the Angstrom model. Wind energy potential was estimated by using the Weibull distribution function for each month independently. The results of the multi-criteria decision-making methods showed Izadkhast to be the most suitable location for renewable hydrogen production in the studied area.

ACS Style

Khalid Almutairi; Ali Mostafaeipour; Ehsan Jahanshahi; Erfan Jooyandeh; Youcef Himri; Mehdi Jahangiri; Alibek Issakhov; Shahariar Chowdhury; Seyyed Hosseini Dehshiri; Seyyed Hosseini Dehshiri; Kuaanan Techato. Ranking Locations for Hydrogen Production Using Hybrid Wind-Solar: A Case Study. Sustainability 2021, 13, 4524 .

AMA Style

Khalid Almutairi, Ali Mostafaeipour, Ehsan Jahanshahi, Erfan Jooyandeh, Youcef Himri, Mehdi Jahangiri, Alibek Issakhov, Shahariar Chowdhury, Seyyed Hosseini Dehshiri, Seyyed Hosseini Dehshiri, Kuaanan Techato. Ranking Locations for Hydrogen Production Using Hybrid Wind-Solar: A Case Study. Sustainability. 2021; 13 (8):4524.

Chicago/Turabian Style

Khalid Almutairi; Ali Mostafaeipour; Ehsan Jahanshahi; Erfan Jooyandeh; Youcef Himri; Mehdi Jahangiri; Alibek Issakhov; Shahariar Chowdhury; Seyyed Hosseini Dehshiri; Seyyed Hosseini Dehshiri; Kuaanan Techato. 2021. "Ranking Locations for Hydrogen Production Using Hybrid Wind-Solar: A Case Study." Sustainability 13, no. 8: 4524.

Journal article
Published: 09 April 2021 in Energy Reports
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Owing to enormous increase in the automobile population, traditional petroleum fuels for internal combustion engines will be usable only for a few years. Moreover, by releasing toxic emissions into the atmosphere at higher levels these fuels create severe environmental problems. In general, Carbon-monoxide (CO), Unburnt hydrocarbons (UHC), and smoke are emissions emitted by engines. The pollution of the environment can be controlled by replacing petroleum fuel with the use of alternative fuels like acetylene gas, hydrogen, CNG, LPG etc. In this current research, an experimental investigation was carried out in Compression Ignition engine using acetylene fuel, further enhancing the performance and emission properties by using diethyl ether (DEE) and ethanol as oxygenated fuel. In view of the performance and outflow (emission) parameters optimizing valve of acetylene gas as 12 lpm with oxygenated fuels, the performance and outflow characteristics were improved. The findings show an enhancement in brake thermal-efficiency of up to 3 to 4%, a decrease in exhaust temperature and emissions like CO, UHC and smoke of up to 40%, 20%–30% and 10%–35% respectively, there is decrease in fuel consumption of 10%–30%. It was found that ethanol is better than diethyl ether and diesel fuels when used as an oxygenated fuel with acetylene gas. In view of the performance and emission parameters, the best oxygenated fuel is ethanol and the optimize blend for diesel engine is E15+A12.

ACS Style

Gursharan Singh; Shubham Sharma; Jujhar Singh; Som Kumar; Yadvinder Singh; Mohammad H. Ahmadi; Alibek Issakhov. Optimization of performance, combustion and emission characteristics of acetylene aspirated diesel engine with oxygenated fuels: An Experimental approach. Energy Reports 2021, 7, 1857 -1874.

AMA Style

Gursharan Singh, Shubham Sharma, Jujhar Singh, Som Kumar, Yadvinder Singh, Mohammad H. Ahmadi, Alibek Issakhov. Optimization of performance, combustion and emission characteristics of acetylene aspirated diesel engine with oxygenated fuels: An Experimental approach. Energy Reports. 2021; 7 ():1857-1874.

Chicago/Turabian Style

Gursharan Singh; Shubham Sharma; Jujhar Singh; Som Kumar; Yadvinder Singh; Mohammad H. Ahmadi; Alibek Issakhov. 2021. "Optimization of performance, combustion and emission characteristics of acetylene aspirated diesel engine with oxygenated fuels: An Experimental approach." Energy Reports 7, no. : 1857-1874.

Journal article
Published: 23 March 2021 in Journal of Hydrology
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This paper considered the behavior of an incompressible fluid, sediment and solid particles debris at the time of a dam break. This process was studied numerically on the basis of three-dimensional Reynolds-averaged Navier-Stokes equations in combination with the k-ω turbulence model. The VOF (Volume of Fluid) method was used to simulate the fluid and sediment. In order to simulate the movement of water and sediment, a combination of Newtonian and non-Newtonian models was carried out. The effect of water flow on the transport of solid particles and moving sediments is also considered. In order to be convinced of the effectiveness and reliability of the model, the numerical results were compared with experimental data and with calculated data performed by other authors. Further, a proven mathematical model is applied to numerically simulate the movement of fluid behind the dam during the break of the dam body with a riverbed landscape, taking into account multi-level protection. The pressure that the water flow exerts on the additional dam in downstream in the case of cylindrical columns and without them was calculated. Since the columns block the path of solid particles, the pressure exerted on the additional dam is noticeably reduced, and in this case it can be assumed that a potential dam break will not occur, and if it does, then with the least damage. This configuration imitates a robust multi-level protection system that can be used to prevent the serious consequences of a dam failure.

ACS Style

Alibek Issakhov; Aliya Borsikbayeva. The impact of a multilevel protection column on the propagation of a water wave and pressure distribution during a dam break: Numerical simulation. Journal of Hydrology 2021, 598, 126212 .

AMA Style

Alibek Issakhov, Aliya Borsikbayeva. The impact of a multilevel protection column on the propagation of a water wave and pressure distribution during a dam break: Numerical simulation. Journal of Hydrology. 2021; 598 ():126212.

Chicago/Turabian Style

Alibek Issakhov; Aliya Borsikbayeva. 2021. "The impact of a multilevel protection column on the propagation of a water wave and pressure distribution during a dam break: Numerical simulation." Journal of Hydrology 598, no. : 126212.

Journal article
Published: 11 March 2021 in Sustainability
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The present experimental work is performed to investigate the convection heat transfer (HT), pressure drop (PD), irreversibility, exergy efficiency and thermal performance for turbulent flow inside a uniformly heated circular channel fitted with novel geometry of hybrid tape. Air is taken as the working fluid and the Reynolds number is varied from 10,000 to 80,000. Hybrid tape is made up of a combination of grooved spring tape and wavy tape. The results obtained with the novel hybrid tape show significantly better performance over individual tapes. A correlation has been developed for predicting the friction factor (f) and Nusselt number (Nu) with novel hybrid tape. The results of this investigation can be used in designing heat exchangers. This paper also presented a statistical analysis of the heat transfer and fluid flow by developing an artificial neural network (ANN)-based machine learning (ML) model. The model is trained based on the features of experimental data, which provide an estimation of experimental output based on user-defined input parameters. The model is evaluated to have an accuracy of 98.00% on unknown test data. These models will help the researchers working in heat transfer enhancement-based experiments to understand and predict the output. As a result, the time and cost of the experiments will reduce.

ACS Style

Suvanjan Bhattacharyya; Devendra Vishwakarma; Shramona Chakraborty; Rahul Roy; Alibek Issakhov; Mohsen Sharifpur. Turbulent Flow Heat Transfer through a Circular Tube with Novel Hybrid Grooved Tape Inserts: Thermohydraulic Analysis and Prediction by Applying Machine Learning Model. Sustainability 2021, 13, 3068 .

AMA Style

Suvanjan Bhattacharyya, Devendra Vishwakarma, Shramona Chakraborty, Rahul Roy, Alibek Issakhov, Mohsen Sharifpur. Turbulent Flow Heat Transfer through a Circular Tube with Novel Hybrid Grooved Tape Inserts: Thermohydraulic Analysis and Prediction by Applying Machine Learning Model. Sustainability. 2021; 13 (6):3068.

Chicago/Turabian Style

Suvanjan Bhattacharyya; Devendra Vishwakarma; Shramona Chakraborty; Rahul Roy; Alibek Issakhov; Mohsen Sharifpur. 2021. "Turbulent Flow Heat Transfer through a Circular Tube with Novel Hybrid Grooved Tape Inserts: Thermohydraulic Analysis and Prediction by Applying Machine Learning Model." Sustainability 13, no. 6: 3068.

Journal article
Published: 24 February 2021 in Sustainability
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Worldwide energy supply is mostly reliant on fossil fuels. Carbon dioxide emissions have caused many negative environmental issues like climate change, air pollution, and energy security. An important alternative to this hazard is substituting the fossil fuel-based carbon energy sources with renewable energy sources. Passive strategies, which are devised to provide thermal comfort in buildings are examples of how to use renewable energies. For this study, a dairy product warehouse in the city of Yazd in Iran was thoroughly investigated. The main goal of this study is to introduce different scenarios, then identifying them based upon optimization of energy consumption. Another main purpose of the present study is to maximize the use of passive energy to meet the cooling needs of a dairy products warehouse in the studied area. Underground temperature is lower than the surface in summer, also it is higher in winter. Therefore, this property of soil is investigated by using nine different scenarios at different heights for constructing underground warehouse for storing dairy products. Clearly, different renewable tools like wind turbine, wind catcher, solar chiller, and different roof designs by Savanah grass, roof pond are also investigated. At first, the cooling load of the warehouse is calculated separately for each season. Then, according to the energy load values obtained, the nominated scenarios are investigated. The results of the comparisons show that the construction of a warehouse at a depth of 3 m from the ground with a green roof covered with Savannah grass helps achieve the best degree of reduction in the cooling power.

ACS Style

Khalid Almutairi; Elham Esfahani; Ali Mostafaeipour; Alibek Issakhov; Chila Kaewpraek; Kuaanan Techato. A Novel Policy to Optimize Energy Consumption for Dairy Product Warehouses: A Case Study. Sustainability 2021, 13, 2445 .

AMA Style

Khalid Almutairi, Elham Esfahani, Ali Mostafaeipour, Alibek Issakhov, Chila Kaewpraek, Kuaanan Techato. A Novel Policy to Optimize Energy Consumption for Dairy Product Warehouses: A Case Study. Sustainability. 2021; 13 (5):2445.

Chicago/Turabian Style

Khalid Almutairi; Elham Esfahani; Ali Mostafaeipour; Alibek Issakhov; Chila Kaewpraek; Kuaanan Techato. 2021. "A Novel Policy to Optimize Energy Consumption for Dairy Product Warehouses: A Case Study." Sustainability 13, no. 5: 2445.

Article
Published: 07 January 2021 in Journal of thermal analysis
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Ensuring efficient operation of energy conversion systems in terms of economics and ecology is a prime objective that should be addressed within the design, optimization, and development stages of such systems. Adopting appropriate measures for accurate assessment and comprehensive evaluation of thermodynamic systems is a sheer necessity for accomplishing this purpose. In this study, the newly developed emergy-based exergoeconomic (i.e., emergoeconomic) and emergy-based exergoenvironmental (i.e., emergoenvironmental) analyses have been employed to assess a combined power and cooling system, including a gas turbine cycle, a steam Rankine cycle, and an integrated organic Rankine cycle-vapor compression refrigeration (ORC-VCR) subsystem serving as a waste heat recovery unit. The merit of emergy-based methods is that they can evaluate and express results by an identical unit of measurement (i.e., sej) which enables us to undertake a fair and accurate comparison between the methods in question. The results showed that the combustion chamber, with the total economic emergy rate of 6.83E13 (sej h−1) and the total ecological emergy rate of 6.05E14 (sej h−1), was the most critical component in the entire system from both the economic and ecological viewpoints. Moreover, a parametric study was carried out on the entire system, as well as the ORC-VCR unit, to examine the effect of design parameters on the emergy-based monetary and ecological performances. Increasing the air compressor pressure ratio from 6 to 11 enhanced the entire system’s both emergy-based performances by almost 8%, followed by improvements made by the gas turbine isentropic efficiency and combustor inlet temperature, with 6.5% and 5.5%, respectively. However, other design parameters exerted limited impact. Regarding the ORC-VCR, raising the ORC turbine inlet temperature and the isentropic efficiencies associated with the ORC turbine and VCR compressor improved the emergy-based performances, while the reverse was observed for the ORC condenser and evaporator temperature rise.

ACS Style

Alireza Mahmoudan; Parviz Samadof; Ravinder Kumar; Mohamad Jalili; Alibek Issakhov. Emergy-based exergoeconomic and exergoenvironmental evaluation of a combined power and cooling system based on ORC-VCR. Journal of thermal analysis 2021, 145, 1353 -1372.

AMA Style

Alireza Mahmoudan, Parviz Samadof, Ravinder Kumar, Mohamad Jalili, Alibek Issakhov. Emergy-based exergoeconomic and exergoenvironmental evaluation of a combined power and cooling system based on ORC-VCR. Journal of thermal analysis. 2021; 145 (3):1353-1372.

Chicago/Turabian Style

Alireza Mahmoudan; Parviz Samadof; Ravinder Kumar; Mohamad Jalili; Alibek Issakhov. 2021. "Emergy-based exergoeconomic and exergoenvironmental evaluation of a combined power and cooling system based on ORC-VCR." Journal of thermal analysis 145, no. 3: 1353-1372.

Journal article
Published: 31 October 2020 in Agriculture
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The global population growth has led to a considerable rise in demand for wheat. Today, the amount of energy consumption in agriculture has also increased due to the need for sufficient food for the growing population. Thus, agricultural policymakers in most countries rely on prediction models to influence food security policies. This research aims to predict and reduce the amount of energy consumption in wheat production. Data were collected from the farms of Estahban city in Fars province of Iran by the Jihad Agricultural Department’s experts for 20 years from 1994 to 2013. In this study, a novel prediction method based on consumed energy in the production period is proposed. The model is developed based on artificial intelligence to forecast the output energy in wheat production and uses extreme learning machine (ELM) and support vector regression (SVR). In the experimental stage, the value of elevation metrics for the EVM and ELM was reported to be equal to 0.000000409 and 0.9531, respectively. Total input energy (consumed) is found to be 1,460,503.1 Mega Joules (MJ), and output energy (produced wheat) is 1,401,011.945 MJ for the Estahban. The result indicates the superiority of the ELM model to enhance the decisions of the agricultural policymakers.

ACS Style

Ali Mostafaeipour; Mohammad Fakhrzad; Sajad Gharaat; Mehdi Jahangiri; Joshuva Dhanraj; Shahab Band; Alibek Issakhov; Amir Mosavi. Machine Learning for Prediction of Energy in Wheat Production. Agriculture 2020, 10, 517 .

AMA Style

Ali Mostafaeipour, Mohammad Fakhrzad, Sajad Gharaat, Mehdi Jahangiri, Joshuva Dhanraj, Shahab Band, Alibek Issakhov, Amir Mosavi. Machine Learning for Prediction of Energy in Wheat Production. Agriculture. 2020; 10 (11):517.

Chicago/Turabian Style

Ali Mostafaeipour; Mohammad Fakhrzad; Sajad Gharaat; Mehdi Jahangiri; Joshuva Dhanraj; Shahab Band; Alibek Issakhov; Amir Mosavi. 2020. "Machine Learning for Prediction of Energy in Wheat Production." Agriculture 10, no. 11: 517.