Search results for: temperature dependent viscosity

Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

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This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Alisa Salimova, Jiane Zuo, Christopher Homer

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The objective of this study is to analyse the North Canal riparian zone land use with the help of remote sensing analysis in ArcGis using 30 cloudless Landsat8 open-source satellite images from May to August of 2013 and 2017. Land cover, urban construction, heat island effect, vegetation cover, and water system change were chosen as the main parameters and further analysed to evaluate its impact on the North Canal water quality. The methodology involved the following steps: firstly, 30 cloudless satellite images were collected from the Landsat TM image open-source database. The visual interpretation method was used to determine different land types in a catchment area. After primary and secondary classification, 28 land cover types in total were classified. Visual interpretation method was used with the help ArcGIS for the grassland monitoring, US Landsat TM remote sensing image processing with a resolution of 30 meters was used to analyse the vegetation cover. The water system was analysed using the visual interpretation method on the GIS software platform to decode the target area, water use and coverage. Monthly measurements of water temperature, pH, BOD, COD, ammonia nitrogen, total nitrogen and total phosphorus in 2013 and 2017 were taken from three locations of the North Canal in Tongzhou district. These parameters were used for water quality index calculation and compared to land-use changes. The results of this research were promising. The vegetation coverage of North Canal riparian zone in 2017 was higher than the vegetation coverage in 2013. The surface brightness temperature value was positively correlated with the vegetation coverage density and the distance from the surface of the water bodies. This indicates that the vegetation coverage and water system have a great effect on temperature regulation and urban heat island effect. Surface temperature in 2017 was higher than in 2013, indicating a global warming effect. The water volume in the river area has been partially reduced, indicating the potential water scarcity risk in North Canal watershed. Between 2013 and 2017, urban residential, industrial and mining storage land areas significantly increased compared to other land use types; however, water quality has significantly improved in 2017 compared to 2013. This observation indicates that the Tongzhou Water Restoration Plan showed positive results and water management of Tongzhou district had been improved.

Keywords: North Canal, land use, riparian vegetation, river ecology, remote sensing

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Authors: Yousef Almutairi, Yajue Wu

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Various large-scale trends have characterized the current century thus far, including increasing shifts towards urbanization and greater movement. It is predicted that there will be 9.3 billion people on Earth in 2050 and that over two-thirds of this population will be city dwellers. Moreover, in larger cities worldwide, mass transportation systems, including underground systems, have grown to account for the majority of travel in those settings. Underground networks are vulnerable to fires, however, endangering travellers’ safety, with various examples of fire outbreaks in this setting. This study aims to increase knowledge of the impacts of extreme climatic conditions on fires, including the role of the high ambient temperatures experienced in Middle Eastern countries and specifically in Saudi Arabia. This is an element that is not always included when assessments of fire safety are made (considering visibility, temperatures, and flows of smoke). This paper focuses on a tunnel within Riyadh’s underground system as a case study and includes simulations based on computational fluid dynamics using ANSYS Fluent, which investigates the impact of various ventilation systems while identifying smoke density, speed, pressure and temperatures within this tunnel.

Keywords: fire, subway tunnel, CFD, mechanical ventilation, smoke, temperature, harsh weather

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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Authors: Shubham Damke, Md Imtiaz, Sanchita Dei

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To stimulate the well and to enhance the production from the shaly formations, fracturing is essential. Presently the chiefly employed technology is Hydraulic Fracturing. However Hydraulic Fracturing accompanies itself with problems like disposing large volumes of fracturing wastewater, removal of water from the pores, formation damage due to injection of large amount of chemicals into underground formations and many more. Therefore embarking on the path of innovation new techniques have been developed which uses different gases such as Nitrogen, Carbon dioxide, Frac Oil, LPG, etc. are used as a base fluid for fracturing formation. However LPG proves to be the most favorable of them which eliminates the use of water and chemicals. When using it as a fracturing fluid, within the surface equipment, it is stored, gelled, and proppant blended at a constant pressure. It is then pressurized with high pressure pumps to the required surface injection pressure With lowering the total cost and increasing the productivity, LPG is also very noteworthy for fracturing shale, where if the hydraulic fracturing is done the water ‘swells’ the formation and creates surface tension, both of which inhibit the flow of oil and gas. Also fracturing with LPG increases the effective fracture length and since propane, butane and pentane is used which are already present in the natural gas therefore there is no problem of back flow because these gases get mixed with the natural gas. LPG Fracturing technology can be a promising substitute of the Hydraulic Fracturing, which could substantially reduce the capital cost of fracturing shale and will also restrict the problems with the disposal of water and on the same hand increasing the fracture length and the productivity from the shale.

Keywords: Fracking, Shale, Surface Tension, Viscosity

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Authors: Belkacem Ould Said, Nourddine Retiel, Abdelilah Benazza, Mohamed Aichouni

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In this paper, a numerical study of two-dimensional steady flow has been made of natural convection in a differentially heated vertical conical partially annular space. The heat transfer is assumed to take place by natural convection. The inner and outer surfaces of annulus are maintained at uniform wall temperature. The annulus is filled with air. The CFD FLUENT12.0 code is used to solve the governing equations of mass, momentum and energy using constant properties and the Boussinesq approximation for density variation. The streamlines and the isotherms of the fluid are presented for different annuli with different boundary conditions and Rayleigh numbers. Emphasis is placed on the influences of the height of the inner vertical cone on the flow and the temperature fields. In addition, the effects on the heat transfer are discussed for various values of physical parameters of the fluid and geometric parameters of the annulus. The heat transfer on the hot walls of the annulus is also calculated in order to make comparisons between the cylinder annulus for boundary conditions and several Rayleigh numbers. A good agreement of Nusselt number has been found between the present predictions and reference from the literature data.

Keywords: natural convection, heat transfer, numerical simulation, conical partially, annular space

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Authors: Aminreza Noghrehabadi, Mohammad Behbahani, Ali Pourabbasi

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In this experimental work, unlike conventional methods that mix two nanoparticles together, silver nanoparticles have been synthesized on the surface of graphene. In this research, the effect of adding modified graphene nanocomposite-silver nanoparticles to the base fluid (distilled water) was studied. Different transmission electron microscopy (TEM) and field emission scanning electron microscope (FESEM) techniques have been used to examine the surfaces and atomic structure of nanoparticles. An ultrasonic device has been used to disperse the nanocomposite in distilled water. Also, the thermal conductivity coefficient was measured by the transient hot wire method using the KD2-pro device. In addition, the thermal conductivity coefficient was measured in the temperature range of 30°C to 50°C, concentration of 10 ppm to 1000 ppm, and ultrasonic time of 2 minutes to 15 minutes. The results showed that with the increase of all three parameters of temperature, concentration and ultrasonic time, the percentage of increase in thermal conductivity will go up until reaching the optimal point, and after passing the optimal point, the percentage of increase in thermal conductivity will have a downward trend. To calculate the thermal conductivity of this nanofluid, a very accurate experimental equation has been obtained using Design Expert software.

Keywords: thermal conductivity, nanofluids, enhancement, silver nano particle, optimal point

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Authors: Sadia Siddiqa, Z. Khan, M. A. Hossain

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In this article, the effect of thermal radiation on mixed convection boundary layer flow of a viscous fluid along a highly heated vertical flat plate is considered with varying density and volumetric expansion coefficient. The density of the fluid is assumed to vary exponentially with temperature, however; volumetric expansion coefficient depends linearly on temperature. Boundary layer equations are transformed into convenient form by introducing primitive variable formulations. Solutions of transformed system of equations are obtained numerically through implicit finite difference method along with Gaussian elimination technique. Results are discussed in view of various parameters, like thermal radiation parameter, volumetric expansion parameter and density variation parameter on the wall shear stress and heat transfer rate. It is concluded from the present investigation that increase in volumetric expansion parameter decreases wall shear stress and enhances heat transfer rate.

Keywords: thermal radiation, mixed convection, variable density, variable volumetric expansion coefficient

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Authors: Kumaresh Selvakumar, Man Young Kim

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In order to elaborate the main idea of investigating the flow physics inside the catalytic combustor, the characteristics of the catalytic surface reactions are analyzed by employing the CHEMKIN methodology with detailed gas and surface chemistries. The presence of a catalyst inside an engine enables complete combustion at lower temperatures which promotes desired chemical reactions. A single channel from the honeycomb monolith catalytic combustor is preferred to analyze the gas and surface reactions in the catalyst bed considering the fact that every channel in the honeycomb monolith behaves in similar fashion. The simplified approach with single catalyst channel using plug flow reactor can be used to predict the flow behavior inside the catalytic combustor. The hydrogen addition to the combustion reactants offers a way to light-off catalytic combustion of methane on platinum catalyst and aids to reduce the surface ignition temperature. Indeed, the hydrogen adsorption is higher on the uncovered Pt(s) surface sites because the sticking coefficient of hydrogen is larger than that of methane. The location of flame position in the catalyst bed is validated by igniting the methane fuel with the presence of hydrogen for corresponding multistep surface reactions.

Keywords: catalytic combustor, hydrogen adsorption, plug flow reactor, surface ignition temperature

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Authors: Chakrit Chotamonsak

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In this study, the Weather Research and Forecasting (WRF) model was used as regional climate model to dynamically downscale the ECHAM5 Global Climate Model projection for the regional climate change impact on air quality–related meteorological conditions in the upper northern Thailand. The analyses were focused on meteorological variables that potentially impact on the regional air quality such as sea level pressure, planetary boundary layer height (PBLH), surface temperature, wind speed and ventilation. Comparisons were made between the present (1990–2009) and future (2045–2064) climate downscaling results during majority air pollution season (dry season, January-April). Analyses showed that the sea level pressure will be stronger in the future, suggesting more stable atmosphere. Increases in temperature were obvious observed throughout the region. Decreases in surface wind and PBLH were predicted during air pollution season, indicating weaker ventilation rate in this region. Consequently, air quality-related meteorological variables were predicted to change in almost part of the upper northern Thailand, yielding a favorable meteorological condition for pollutant accumulation in the future.

Keywords: climate change, climate impact, air quality, air pollution, Thailand

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Authors: Pablo Vidal, Misael Martinez, Carlos Hernandez, Ananta R. Adhikari, Luis Materon, Yuanbing Mao, Karen Lozano

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Conjugated polymers are smart materials that show tremendous practical applications in diverse subjects. Polydiacetylenes are conjugated polymers with special optical properties. In response to the environmental changes such as pH and molecular binding, it changes its color. Such an interesting chromic and emissive behavior of polydiacetylenes make them a highly popular polymer in wide areas, including biomedicine such as a biosensor. In this research, we used polyvinyl butyrate as a matrix to fibrillate polydiacetylenes. We initially prepared polyvinyl butyrate/diacetylene matrix using forcespinning technique. They were then polymerized to form polyvinyl butyrate/polydiacetylene (PVB/PDA). These matrices then studied for their bio-sensing response to gram-positive and gram-negative bacteria. The sensing ability of the PVB/PDA biosensor was observed as early as 30 min in the presence of bacteria at 37°C. Now our effort is to decrease this effective temperature to room temperature to make this device applicable in the general daily life. These chromic biosensors will find extensive application not only alert the infection but also find other promising applications such as wearable sensors and diagnostic systems.

Keywords: smart material, conjugated polymers, biosensor, polyvinyl butyrate/polydiacetylene

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Authors: Khalil Trigui, Rafik Ben Said, Fourat Akrout, Neji Aloui

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In this study, we examined in the first part the eco-biology of Artemia (A.salina) collected from Sahline Salt Lake (governorate of Monastir: Tunisia) during an annual cycle. The correlations between environmental factors and some biological parameters of Artemia were determined. The results obtained showed that the environmental factors affected the biology of Artemia. The highest abundance was recorded in May (550 ± 2,16 ind/l) and all life history stages existed with different seasonal proportions. The Artemia population is bisexual with ovoviviparous reproduction at the beginning and oviparous at the end of the life cycle. We also recorded the dominance of males at the start and the females at the end of the cycle. During all the study period, the size of mature females is bigger than that of males. The fertility obtained resulted in a significant production of cysts compared to the nauplii. A negative correlation with highly significant effect was deduced between environmental factors (temperature and salinity) and the production of nauplii (ovoviviparity) in contrast with dissolved oxygen. In the second part of our work is consecrated to the mastery of breeding Artemia. For this, we tested the effect of five external factors (temperature, salinity, dissolved oxygen, light intensity and food) on the survival of this crustacean. Thereby, the survival rates of Artemia were affected by the different values of studied factors. The recorded results showed that Artemia salina has an optimum temperature ranged from 25 to 27°C with a survival rate ranging from 84 to 88%. The optimal salinity to breed Artemia salina was 37 psu (62 ± 0,23%). Nevertheless, this crustacean was able to survive and withstand the salinity of 0 psu (freshwater). The optimum concentration of dissolved oxygen was 7mg/l with a survival rate of 87,11 ± 0,04%. An optimum light intensity of 10 lux revealed a survival rate equal to 85,33 ± 0,01%. The results also showed that the preferred micro-algae by Artemia is Dunaliella salina with a maximum survival rate of the order of 80 ± 0,15%. There is a significant effect for all experienced parameters on the survival of Artemia reared except the nature of food.

Keywords: Artemia salina, biology, breeding, ecology, Sahline salt lake

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Authors: Fayiz Saifurahman, Noori Fida Mohammad

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Afghanistan produces the highest rate of wheat, it is the first source of food, and food security in Afghanistan is dependent on the availability of wheat. Although Afghanistan is the main producer of wheat, on the other hand, Afghanistan is the largest importers of flour. The objective of this study is to assess the structure and dynamics of the wheat market in Afghanistan, can compute with foreign markets, and increase the level of production. To complete this, a broad series of secondary data was complied with, group discussions and interviews with farmers, agricultural and market experts. The research findings propose that; the government should adopt different policies to support the local market. The government should distribute the seed, support financially and technically to increase wheat production.

Keywords: Afghanistan, wheat, production , import

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Authors: Jiachen Wang, Dongxu Ji

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Geothermal power generation is a mature technology with zero carbon emission and stable power output, which could play a vital role as an optimum substitution of base load technology in China’s future decarbonization society. However, the development of geothermal power plants in China is stagnated for a decade due to the underestimation of geothermal energy and insufficient favoring policy. Lack of understanding of the potential value of base-load technology and environmental benefits is the critical reason for disappointed policy support. This paper proposed a different energy-economic model to uncover the potential benefit of developing a geothermal power plant in Puer, including the value of base-load power generation, and environmental and economic benefits. Optimization of the Organic Rankine Cycle (ORC) for maximum power output and minimum Levelized cost of electricity was first conducted. This process aimed at finding the optimum working fluid, turbine inlet pressure, pinch point temperature difference and superheat degrees. Then the optimal ORC model was sent to the energy-economic model to simulate the potential economic and environmental benefits. Impact of geothermal power plants based on the scenarios of implementing carbon trade market, the direct subsidy per electricity generation and nothing was tested. In addition, a requirement of geothermal reservoirs, including geothermal temperature and mass flow rate for a competitive power generation technology with other renewables, was listed. The result indicated that the ORC power plant has a significant economic and environmental benefit over other renewable power generation technologies when implementing carbon trading market and subsidy support. At the same time, developers must locate the geothermal reservoirs with minimum temperature and mass flow rate of 130 degrees and 50 m/s to guarantee a profitable project under nothing scenarios.

Keywords: geothermal power generation, optimization, energy model, thermodynamics

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Authors: Fares Almomani, Majeda Khraisheh, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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Septic tanks (STs) are very commonly used wastewater collection systems in the world especially in rural areas. In this study, the use of moving bed biological reactors (MBBR) for the treatment of septic tanks effluents (STE) was studied. The study was included treating septic tank effluent from one house hold using MBBRs. Significant ammonia removal rate was observed in all the reactors throughout the 180 days of operation suggesting that the MBBRs were successful in reducing the concentration of ammonia from septic tank effluent. The average ammonia removal rate at 25◦C for the reactor operated at hydraulic retention time of 5.7 hr (R1) was 0.540 kg-N/m3and for the reactor operated at hydraulic retention time of 13.3hr (R2) was 0.279 kg-N/m3. Ammonia removal rates were decreased to 0.3208 kg-N/m3 for R1 and 0.212 kg-N/m3 for R3 as the temperature of reactor was decreased to 8 ◦C. A strong correlation exists between theta model and the rates of ammonia removal for the reactors operated in continuous flow. The average ϴ values for the continuous flow reactors during the temperature change from 8°C to 20 °C were found to be 1.053±0.051. MBBR technology can be successfully used as a polishing treatment for septic tank effluent.

Keywords: septic tanks, wastewater treatment, morphology, moving biological reactors, nitrification

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Authors: Min Chang Shin, Byung Hun Jeong, Jeong Sik Han, Jung Hoon Park

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In modern times, as flight speeds have increased due to improvements in aircraft and missile engine performance, thermal loads have also increased. Because of the friction heat of air flow with high speed on the surface of the vehicle, it is not easy to cool the superheat of the vehicle by the simple air cooling method. For this reason, a cooling method through endothermic heat is attracting attention by using a fuel that causes an endothermic reaction in a high-speed vehicle. There are two main ways of cooling the fuel through the endothermic reaction. The first is physical heat absorption. When the temperature rises, there is a sensible heat that accompanies it. The second is the heat of reaction corresponding to the chemical heat absorption, which absorbs heat during the fuel decomposes. Generally, since the decomposition reaction of the fuel proceeds at a high temperature, it does not achieve a great efficiency in cooling the high-speed flight body. However, when the catalyst is used, decomposition proceeds at a low temperature thereby increasing the cooling efficiency. However, when the catalyst is used as a powder, the catalyst enters the engine and damages the engine or the catalyst can deteriorate the performance due to the sintering. On the other hand, when used in the form of pellets, catalyst loss can be prevented. However, since the specific surface of pellet is small, the efficiency of the catalyst is low. And it can interfere with the flow of fuel, resulting in pressure loss and problems with fuel injection. In this study, we tried to maximize the performance of the catalyst by preparing a hollow fiber type pellet for zeolite ZSM-5, which has a higher amount of heat absorption, than other conventional pellets. The hollow fiber type pellet was prepared by phase inversion method. The hollow fiber type pellet has a finger-like pore and sponge-like pore. So it has a higher specific surface area than conventional pellets. The crystal structure of the prepared ZSM-5 catalyst was confirmed by XRD, and the characteristics of the catalyst were analyzed by TPD/TPR device. This study was conducted as part of the Basic Research Project (Pure-17-20) of Defense Acquisition Program Administration.

Keywords: catalyst, endothermic reaction, high-speed vehicle cooling, zeolite, ZSM-5

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Authors: Wilaisri Limphapayom

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Lime is one of the economically important produced in Thailand. The objective of this research is to increase utilization in food and cosmetic. Extraction of essential oil and pectin from lime (Citrus aurantifolia (Christm & Panz ) Swing) have been studied. Extraction of essential oil has been made by using hydro-distillation .The essential oil ranged from 1.72-2.20%. The chemical composition of essential oil composed of alpha-pinene , beta-pinene , D-limonene , comphene , a-phellandrene , g-terpinene , a-ocimene , O-cymene , 2-carene , Linalool , trans-ocimenol , Geraniol , Citral , Isogeraniol , Verbinol , and others when analyzed by using GC-MS method. Pectin extraction from lime waste , boiled water after essential oil extraction. Pectin extraction were found 40.11-65.81 g /100g of lime peel. The best extraction condition was found to be higher in yield by using ethanol extraction. The potential of this study had satisfactory results to improve lime processing system for value-added . The present study was also focused on Lime powder production as source of vitamin C or ascorbic acid and the potential of lime waste as a source of essential oil and pectin. Lime powder produced from Spray Dryer . Lime juice with 2 different level of maltodextrins DE 10 , 30 and 50% w/w was sprayed at 150 degrees celsius inlet air temperature and at 90-degree celsius outlet temperature. Lime powder with 50% maltodextrin gave the most desirable quality product. This product has vitamin C contents of 25 mg/100g (w/w).

Keywords: extraction, pectin, essential oil, lime

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Imed Mezghani, Yousra Ben Salah, Mohamed Chaieb

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Tricholaena teneriffae L. is a xerophytic perennial herb that belongs to the Poaceae family likely to be used for ecological restoration programs. It's a dominant and economically important species widely distributed in the Bou-Hedma National Park, Tunisia. Reintroduction and expansion of T. teneriffae depend solely on sexual reproduction. This makes the understanding of its germination requirements vital for conservation and management. To provide basic information for its conservation and reintroduction, we studied the influence of environmental factors on seed germination patterns. The germination responses of seeds were determined over a wide range of constant temperatures (15–35°C), polyethylene glycol solutions of different osmotic potentials (0 to −2 MPa) and salt solution (0 to 150 mM of NaCl). Results indicated that the optimum temperature germination was attained at 25°C which corresponds to temperatures prevailing during mid spring season in the Mediterranean area. Seeds germinated in Polyethylene Glycol solutions exhibited significantly lower germination than control especially when water potential fell below -0.6 MPa. Germination percentage and rate decreased with an increase NaCl concentration. Seeds germination was substantially delayed and reduced with an increase in NaCl to levels above 50 mM. T. teneriffae is moderately salt tolerant at germination stage.

Keywords: germination, temperature, Tricholaena teneriffae L., salt stress, water stress, rehabilitation

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Authors: Naoki Ohshima, Ken Kaminishi

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Four types of dependencies, which are 'Finish-to-start', 'Finish-to-finish', 'Start-to-start' and 'Start-to-finish (S-F)' as logical relationship are modeled based on the definition by 'the predecessor activity is defined as an activity to come before a dependent activity in a schedule' in PMBOK. However, it is found a self-contradiction in the precedence diagram for S-F relationship by PMBOK. In this paper, author would like to validate logical relationship of S-F by Graph Theory and propose a new interpretation of the precedence diagram for S-F relationship.

Keywords: project time management, sequence activity, start-to-finish relationship, precedence diagram, PMBOK

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Authors: Parvaneh Hajeb, Shahram Shakibazadeh, Md. Zaidul Islam Sarker

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High-quality fish oil for human consumption requires low levels of toxic elements. The aim of this study was to develop a method to extract oil from fish wastes with the least toxic elements contamination. Supercritical fluid extraction (SFE) was applied to detoxify fish oils from toxic elements. The SFE unit used consisted of an intelligent HPLC pump equipped with a cooling jacket to deliver CO2. The freeze-dried fish waste sample was extracted by heating in a column oven. Under supercritical conditions, the oil dissolved in CO2 was separated from the supercritical phase using pressure reduction. The SFE parameters (pressure, temperature, CO2 flow rate, and extraction time) were optimized using response surface methodology (RSM) to extract the highest levels of toxic elements. The results showed that toxic elements in fish oil can be reduced using supercritical CO2 at optimum pressure 40 MPa, temperature 61 ºC, CO2 flow rate 3.8 MPa, and extraction time 4.25 hr. There were significant reductions in the mercury (98.2%), cadmium (98.9%), arsenic (96%), and lead contents (99.2%) of the fish oil. The fish oil extracted using this method contained elements at levels that were much lower than the accepted limits of 0.1 μg/g. The reduction of toxic elements using the SFE method was more efficient than that of the conventional methods due to the high selectivity of supercritical CO2 for non-polar compounds.

Keywords: food safety, toxic elements, fish oil, supercritical carbon dioxide

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Authors: Surya Chandra Tiwari, Kamal Kishore Pant, Sreedevi Upadhyayula

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CO2 capture using benign cost-effective solvents is an essential unit operation not only in the process industry for CO2 separation and recovery from industrial off-gas streams but also for direct capture from air to clean the environment. Several solvents are identified, by researchers, with high CO2 capture efficiency due to their favorable chemical and physical properties, interaction mechanism with CO2, and low regeneration energy cost. However, N-Methyldiethanolamine (MDEA) is the most frequently used solvent for CO2 capture with promoters such as piperazine (Pz) and monoethanolamine (MEA). These promoters have several issues such as low thermal stability, heat-stable salt formation, and being highly degradable. Therefore, new class promoters need to be used to overcome these issues. Functionalized ionic liquids (FILs) have the potential to overcome these limitations. Hence, in this work, four different new class functionalized ionic liquids (FILs) were used as promoters and determined their effectivity toward enhancement of the CO2 absorption performance. The CO2 absorption is performed at different pressure (2 bar, 4.4 bar, and 7 bar) and different temperature (303, 313, and 323K). The results confirmed that CO2 loading increases around 18 to 22% after 5wt% FILs blended in the MDEA. It was noticed that the CO2 loading increases with increasing pressure and decreases with increasing temperature for all absorbents systems. Further, the absorption kinetics was determined, and results showed that all the FILs provide an excellent absorption rate enhancement. Additionally, for the interaction mechanism study, 13C NMR analysis was performed for the blend aqueous MDEA-CO2 system. The results suggested that the FILs blend MDEA system produced a high amount of carbamates and bicarbonates during CO2 absorption, which further decreases with increasing temperature. Eventually, regeneration energy was calculated, and results confirmed that the energy heat duty penalty was lower in the [TETAH][Im] blend MDEA system. Overall, [TETAH][Pz], [TETAH][Im], [DETAH][Im] and [DETAH][Tz] showed the promising ability as promoters to enhance CO2 capturing performance of MDEA.

Keywords: CO2 capture, interaction mechanism, kinetics, Ionic liquids

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Authors: Tae Hyun Ahn, Gyo Woo Lee, Man Young Kim

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Because of high thermal efficiency and low CO2 emission, diesel engines are being used widely in many industrial fields although it makes many PM and NOx which give both human health and environment a negative effect. NOx regulations for diesel engines, however, are being strengthened and it is impossible to meet the emission standard without NOx reduction devices such as SCR (Selective Catalytic Reduction), LNC (Lean NOx Catalyst), and LNT (Lean NOx Trap). Among the NOx reduction devices, urea-SCR system is known as the most stable and efficient method to solve the problem of NOx emission. But this device has some issues associated with the ammonia slip phenomenon which is occurred by shortage of evaporation and thermolysis time, and that makes it difficult to achieve uniform distribution of the injected urea in front of monolith. Therefore, this study has focused on the mixing enhancement between urea and exhaust gases to enhance the efficiency of the SCR catalyst equipped in catalytic muffler by changing inlet gas temperature and spray conditions to improve the spray uniformity of the urea water solution. Finally, it can be found that various parameters such as inlet gas temperature and injector and injection angles significantly affect the evaporation and mixing of the urea water solution with exhaust gases, and therefore, optimization of these parameters are required.

Keywords: UWS (Urea-Water-Solution), selective catalytic reduction (SCR), evaporation, thermolysis, injection

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Authors: Mahyar Maali, Merve Sagiroglu, Mahmut Kilic, Abdulkadir Cuneyt Aydin

Abstract:

In order to evaluate the residual strength of S235 (St37) steel structures after the fire, an experimental program was undertaken to investigate the post-fire mechanical properties. Tensile coupons taken from S235 sheets were exposed to varying temperatures as 200°C, 400°C, 600°C, and 800 °C. The samples were then allowed to cool down to ambient temperature before they were tested to failure. To obtain the mechanical properties of steels; tensile tests are performed, and the post-fire stress-strain curves are evaluated. The microstructures of the heat-treated specimens were examined by Scanning Electron Microscope (SEM). It is seen that morphology and size of the precipitates in the specimens change, as the heat increases. The modulus of elasticity decreases, and deformation increases with temperature. Energy dissipation decreases due to lower stress according to the stress-strain curves of the specimens. Especially, the mechanical properties were decreased compared with the pre-fire ones. As a result of the post-fire and pre-fire behavior of S235, a set of equations is evaluated to predict the mechanical properties after the fire. These types of equations may allow the structural and/or fire engineers to predict accurately the post-fire behavior of the buildings constructed with S235 type steel.

Keywords: post-fire behavior, stress-strain curves, experimental study, S235 steel

Procedia PDF Downloads 349

Authors: Mohammad A. U. Khan, Omar A. Kittaneh, M. Akbar, Tariq M. Khan, Husam A. Bayoud

Abstract:

The Shannon Entropy measure has been widely used for measuring uncertainty. However, in partial settings, the histogram is used to estimate the underlying distribution. The histogram is dependent on the number of bins used. In this paper, a modification is proposed that makes the Shannon entropy based on histogram consistent. For providing the benefits, two application are picked in medical image processing applications. The simulations are carried out to show the superiority of this modified measure for image segmentation problem. The improvement may be contributed to robustness shown to uneven background in images.

Keywords: Shannon entropy, medical image processing, image segmentation, modification

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Authors: Ila Shukla, Lubna Azmi, Shyam Sunder Gupta, C. V. Rao

Abstract:

Treatments against Hepatitis-C virus (HCV) are already available, but the current high cost of such treatments limit them to wealthy patients only. Hence our current study is aimed at the rectification of HCV infection by using Lichen rangiferinus (LRE) extract in in vitro cultures. Anti-HCV activity of the given extract was evaluated using the virus grown in cell culture (HCVcc). Two control inhibitors, erlotinib and telaprevir, were systematically included in each experiment. At the end of the incubation period, we evaluated cell viability and viral replication. The LRE inhibited the growth of HCV in a dose dependent manner.

Keywords: Erlotinib, Hepatitis C, Lichen rangiferinus, Telaprevir

Procedia PDF Downloads 336

Authors: Frank Adusah-Poku, John Bosco Dramani, Prince Boakye Frimpong

Abstract:

Climate change is considered a principal threat to human existence and livelihood. The persistence and intensity of droughts and floods in recent years have adversely affected food production systems and value chains, making it impossible to end global hunger by 2030. Thus, this study aims to examine the effect of climate change on food consumption for both farm and non-farm households in Ghana. An important focus of the analysis is to investigate how climate change affects alternative dimensions of food security, examine the extent to which these effects vary across heterogeneous groups, and explore the channels through which climate change affects food consumption. Finally, we conducted a pilot study to understand the significance of farm and non-farm diversification measures in reducing the harmful impact of climate change on farm households. The approach of this article is to use two secondary and one primary datasets. The first secondary dataset is the Ghana Socioeconomic Panel Survey (GSPS). The GSPS is a household panel dataset collected during the period 2009 to 2019. The second dataset is monthly district rainfall and temperature gridded data from the Ghana Meteorological Agency. This data was matched to the GSPS dataset at the district level. Finally, the primary data was obtained from a survey of farm and non-farm adaptation practices used by farmers in three regions in Northern Ghana. The study employed the household fixed effects model to estimate the effect of climate change (measured by temperature and rainfall) on food consumption in Ghana. Again, it used the spatial and temporal variation in temperature and rainfall across the districts in Ghana to estimate the household-level model. Evidence of potential mechanisms through which climate change affects food consumption was explored using two steps. First, the potential mechanism variables were regressed on temperature, rainfall, and the control variables. In the second and final step, the potential mechanism variables were included as extra covariates in the first model. The results revealed that extreme average temperature and drought had caused a decrease in food consumption as well as reduced the intake of important food nutrients such as carbohydrates, protein and vitamins. The results further indicated that low rainfall increased food insecurity among households with no education compared with those with primary and secondary education. Again, non-farm activity and silos have been revealed as the transmission pathways through which the effect of climate change on farm households can be moderated. Finally, the results indicated over 90% of the small-holder farmers interviewed had no farm diversification adaptation strategies for climate change, and a little over 50% of the farmers owned unskilled or manual non-farm economic ventures. This makes it very difficult for the majority of the farmers to withstand climate-related shocks. These findings suggest that achieving the Sustainable Development Goal of Zero Hunger by 2030 needs an integrated approach, such as reducing the over-reliance on rainfed agriculture, educating farmers, and implementing non-farm interventions to improve food consumption in Ghana.

Keywords: climate change, food consumption, Ghana, non-farm activity

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Authors: Allouache Nadia

Abstract:

Solid adsorption cooling machines have been extensively studied recently. They constitute very attractive solutions recover important amount of industrial waste heat medium temperature and to use renewable energy sources such as solar energy. The development of the technology of these machines can be carried out by experimental studies and by mathematical modelisation. This last method allows saving time and money because it is suppler to use to simulate the variation of different parameters. The adsorption cooling machines consist essentially of an evaporator, a condenser and a reactor (object of this work) containing a porous medium, which is in our case the activated carbon reacting by adsorption with ammoniac. The principle can be described as follows: When the adsorbent (at temperature T) is in exclusive contact with vapour of adsorbate (at pressure P), an amount of adsorbate is trapped inside the micro-pores in an almost liquid state. This adsorbed mass m, is a function of T and P according to a divariant equilibrium m=f (T,P). Moreover, at constant pressure, m decreases as T increases, and at constant adsorbed mass P increases with T. This makes it possible to imagine an ideal refrigerating cycle consisting of a period of heating/desorption/condensation followed by a period of cooling/adsorption/evaporation. Effect of key parameters on the machine performances are analysed and discussed.

Keywords: activated carbon-ammoniac pair, effect of key parameters, numerical modeling, solar cooling machine

Procedia PDF Downloads 255

Authors: Esra Ece Var

Abstract:

Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

Procedia PDF Downloads 239