Entropy analysis in a cilia transport of nanofluid under the influence of magnetic field

Muhammad N. Abrar,Rizwan Ul Haq,Muhammad Awais,Irfan Rashid 한국원자력학회 2017 Nuclear Engineering and Technology Vol.49 No.8

In this study, analysis is performed on entropy generation during cilia transport of water based titanium dioxide nanoparticles in the presence of viscous dissipation. Moreover, thermal heat flux is considered at the surface of a channel with ciliated walls. Mathematical formulation is constructed in the form of nonlinear partial differential equations. Making use of suitable variables, the set of partial differential equations is reduced to coupled nonlinear ordinary differential equations. Closed form exact solutions are obtained for velocity, temperature, and pressure gradient. Graphical illustrations for emerging flow parameters, such as Hartmann number (Ha), Brinkmann number (Br), radiation parameter (Rn), and flow rate, have been prepared in order to capture the physical behavior of these parameters. The main goal (i.e., the minimizing of entropy generation) of the second law of thermodynamics can be achieved by decreasing the magnitude of Br, Ha and Λ parameters.

Chitosan as a Flocculant: An Approach to Improve its Solubility for Efficient Harvesting of Microalgae

( Attia Sajjad ),( Muhammad Rizwan ),( Ghulam Mujtaba ),( Naim Rashid ) 한국화학공학회 2017 Korean Chemical Engineering Research(HWAHAK KONGHA Vol.55 No.4

Chitosan is a promising flocculant for microalgae harvesting, but its scale-up application is not economically supported yet. Low solubility of chitosan in microalgae suspension demands high dosage (as a flocculant) to destabilize the cells, and thus, increases the cost of microalgae harvesting. This study identifies efficient solvents for the chitosan, and optimizes the concentration of solvents and chitosan dose to improve the harvesting efficiency. Chitosan was dissolved in different acids, and subsequently used as a flocculant. The flocculant efficacy was measured in terms of harvesting efficiency and reduction in chemical oxygen demand (COD) of the microalgae suspension. It was found that chitosan dissolved in 0.05 M HCl showed the highest harvesting efficiency (89 ± 0.87%) at only 30 mg/L of dosage. In comparison, 270 mg/L of FeCl₃·6H₂O was required to attain 86 ± 0.083% of the harvesting efficiency. H₂SO₄ dissolved chitosan required high flocculant dose (150 mg/L) and resulted in relatively low harvesting efficiency (77±0.11%). It was concluded that the efficacy of chitosan is solvent dependent, and the selection of proper solvent can decrease the dosage requirement for microalgae harvesting.

Strengthening of concrete damaged by mechanical loading and elevated temperature

Ahmad, Hammad,Hameed, Rashid,Riaz, Muhammad Rizwan,Gillani, Asad Ali Techno-Press 2018 Advances in concrete construction Vol.6 No.6

Despite being one of the most abundantly used construction materials because of its exceptional properties, concrete is susceptible to deterioration and damage due to various factors particularly corrosion, improper loading, poor workmanship and design discrepancies, and as a result concrete structures require retrofitting and strengthening. In recent times, Fiber Reinforced Polymer (FRP) composites have substituted the conventional techniques of retrofitting and strengthening of damaged concrete. Most of the research studies related to concrete strengthening using FRP have been performed on undamaged test specimens. This contribution presents the results of an experimental study in which concrete specimens were damaged by mechanical loading and elevated temperature in laboratory prior to application of Carbon Fiber Reinforced Polymer (CFRP) sheets for strengthening. The test specimens prepared using concrete of target compressive strength of 28 MPa at 28 days were subjected to compressive and splitting tensile testing up to failure and the intact pieces of the failed specimens were collected for the purpose of repair. In order to induce damage as a result of elevated temperature, the concrete cylinders were subjected to $400^{\circ}C$ and $800^{\circ}C$ temperature for two hours duration. Concrete cylinders damaged under compressive and split tensile loads were re-cast using concrete and rich cement-sand mortar, respectively and then strengthened using CFRP wrap. Concrete cylinders damaged due to elevated temperature were also strengthened using CFRP wrap. Re-cast and strengthened concrete cylinders were tested in compression and splitting tension. The obtained results revealed that re-casting of specimens damaged by mechanical loadings using concrete & mortar, and then strengthened by single layer CFRP wrap exhibited strength even higher than their original values. In case of specimens damaged by elevated temperature, the results indicated that concrete strength is significantly dropped and strengthening using CFRP wrap made it possible to not only recover the lost strength but also resulted in concrete strength greater than the original value.

Reactivity of aluminosilicate materials and synthesis of geopolymer mortar under ambient and hot curing condition

Zafar, Idrees,Tahir, Muhammad Akram,Hameed, Rizwan,Rashid, Khuram,Ju, Minkwan Techno-Press 2022 Advances in concrete construction Vol.13 No.1

Aluminosilicate materials as precursors are heterogenous in nature, consisting of inert and partially reactive portion, and have varying proportions depending upon source materials. It is essential to assess the reactivity of precursor prior to synthesize geopolymers. Moreover, reactivity may act as decisive factor for setting molar concentration of NaOH, curing temperature and setting proportion of different precursors. In this experimental work, the reactivities of two precursors, low calcium (fly ash (FA)) and high calcium (ground granulated blast furnace slag (GGBS)), were assessed through the dissolution of aluminosilicate at (i) three molar concentrations (8, 12, and 16 M) of NaOH solution, (ii) 6 to 24 h dissolution time, and (iii) 20-100℃. Based on paratermeters influencing the reactivity, different proportions of ternary binders (two precursors and ordinary cement) were activated by the combined NaOH and Na2SiO3 solutions with two alkaline activators to precursor ratios, to synthesize the geopolymer. Reactivity results revealed that GGBS was 20-30% more reactive than FA at 20℃, at all three molar concentrations, but its reactivity decreased by 32-46% with increasing temperature due to the high calcium content. Setting time of geopolymer paste was reduced by adding GGBS due to its fast reactivity. Both GGBS and cement promoted the formation of all types of gels (i.e., C-S-H, C-A-S-H, and N-A-S-H). As a result, it was found that a specified mixing proportion could be used to improve the compressive strength over 30 MPa at both the ambient and hot curing conditions.

Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan

Nawaz Asif,Ali Tariq,Hafeez Yaser,Rehman Saif ur,Rashid Muhammad Rizwan 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2

Twitter has emerged as outstanding and most prominent social media in today’s technological age. The data proliferates in quick and words with its activities trigger get fast responses from the users. This platform is perfect for promoting political perspectives, particularly when election campaigns are on its peak. Political trends on Twitter media has been contemplated in the course of recent years. In the past research, both supervised and unsupervised methodologies have been used to analyze the Twitter trends. Most of the Tweet classification approaches utilized built in Dictionaries, Naı¨ve Bayes, K-Nearest Neighbors (KNN), decision tree and Support Vector Machines (SVM) classifiers. However, in case of democratic election these trends can be mined to predict the winning party. However, all such approaches produce poor results due to language issues, low accuracy, limited access to internet and lower literacy rate in less developed countries such as Pakistan. This research study, find the best possible way for collection of tweets related to different political parties and build a prediction model that may analyze sentiments and opinions expressed by peoples in their Tweets. In this research work, a prediction based model along with novel similarity measure has been proposed to predict the election results of political parties in Pakistan. The proposed work is composed of data collection, preprocessing, aspect extraction, aspect refinement and final prediction using Bayesian theorem. Form the experimental results, it is concluded that proposed approach perform better than existing techniques by obtaining almost 98% accuracy and efficiently cover the limitations of existing studies.

Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan

Nawaz Asif,Ali Tariq,Hafeez Yaser,Rehman Saif ur,Rashid Muhammad Rizwan 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1

Twitter has emerged as outstanding and most prominent social media in today’s technological age. The data proliferates in quick and words with its activities trigger get fast responses from the users. This platform is perfect for promoting political perspectives, particularly when election campaigns are on its peak. Political trends on Twitter media has been contemplated in the course of recent years. In the past research, both supervised and unsupervised methodologies have been used to analyze the Twitter trends. Most of the Tweet classification approaches utilized built in Dictionaries, Naı¨ve Bayes, K-Nearest Neighbors (KNN), decision tree and Support Vector Machines (SVM) classifiers. However, in case of democratic election these trends can be mined to predict the winning party. However, all such approaches produce poor results due to language issues, low accuracy, limited access to internet and lower literacy rate in less developed countries such as Pakistan. This research study, find the best possible way for collection of tweets related to different political parties and build a prediction model that may analyze sentiments and opinions expressed by peoples in their Tweets. In this research work, a prediction based model along with novel similarity measure has been proposed to predict the election results of political parties in Pakistan. The proposed work is composed of data collection, preprocessing, aspect extraction, aspect refinement and final prediction using Bayesian theorem. Form the experimental results, it is concluded that proposed approach perform better than existing techniques by obtaining almost 98% accuracy and efficiently cover the limitations of existing studies.