Abstract: Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.
Abstract: Progressive collapse of the layered hyperbolic tower shells are studied considering the influences of changes in the supporting columns’ types and angles. 3-D time history analyses employing the finite element method are performed for the towers supported with I-type and ᴧ-type column. It is found that the inclination angle of the supporting columns is a very important parameter in optimization and safe design of the cooling towers against the progressive collapse. It is also concluded that use of Demand Capacity Ratio (DCR) criteria of the linear elastic approach recommended by GSA is un-conservative for the hyperbolic tower shells.
Abstract: Closed Loop Pulsating Heat Pipe (CLPHP) is a passive two-phase heat transfer device having potential to achieve high heat transfer rates over conventional cooling techniques. It is found in electronics cooling due to its outstanding characteristics such as excellent heat transfer performance, simple, reliable, cost effective, compact structure and no external mechanical power requirement etc. Comprehensive understanding of the thermo-hydrodynamic mechanism of CLPHP is still lacking due to its contradictory results available in the literature. The present paper discusses the experimental study on 9 turn CLPHP. Inner and outer diameters of the copper tube are 2 mm and 4 mm respectively. The lengths of the evaporator, adiabatic and condenser sections are 40 mm, 100 mm and 50 mm respectively. Water is used as working fluid. The Filling Ratio (FR) is kept as 50% throughout the investigations. The gravitational effect is studied by placing the evaporator heater at different orientations such as horizontal (90 degree), vertical top (180 degree) and bottom (0 degree) as well as inclined top (135 degree) and bottom (45 degree). Heat input is supplied in the range of 10-50 Watt. Heat transfer mechanism is natural convection in the condenser section. Vacuum pump is used to evacuate the system up to 10-5 bar. The results demonstrate the influence of input heat flux and gravity on the thermal performance of the CLPHP.
Abstract: The present paper discusses the prediction of gas-liquid two-phase frictional pressure drop in a 2.12 mm horizontal circular minichannel using Artificial Neural Network (ANN). The experimental results are obtained with air as gas phase and water as liquid phase. The superficial gas velocity is kept in the range of 0.0236 m/s to 0.4722 m/s while the values of 0.0944 m/s, 0.1416 m/s and 0.1889 m/s are considered for superficial liquid velocity. The experimental results are predicted using different Artificial Neural Network (ANN) models. Networks used for prediction are radial basis, generalised regression, linear layer, cascade forward back propagation, feed forward back propagation, feed forward distributed time delay, layer recurrent, and Elman back propagation. Transfer functions used for networks are Linear (PURELIN), Logistic sigmoid (LOGSIG), tangent sigmoid (TANSIG) and Gaussian RBF. Combination of networks and transfer functions give different possible neural network models. These models are compared for Mean Absolute Relative Deviation (MARD) and Mean Relative Deviation (MRD) to identify the best predictive model of ANN.
Abstract: In the past researchers have questioned the
effectiveness of ethics training in higher education. Also, there are
observations that support the view that ethical behaviour (range of
actions)/ethical decision making models used in the past make use of
vignettes to explain ethical behaviour. The understanding remains in
the perspective that these vignettes play a limited role in determining
individual intentions and not actions. Some authors have also agreed
that there are possibilities of differences in one’s intentions and
actions. This paper makes an attempt to fill those gaps by evaluating
real actions rather than intentions. In a way this study suggests the
use of an experiential methodology to explore Berlo’s model of
communication as an action along with orchestration of various
principles. To this endeavor, an attempt was made to use
conversational analysis in the pursuance of evaluating ethical
decision making behaviour among students and middle level
managers. The process was repeated six times with the set of an
average of 15 participants. Similarities have been observed in the
behaviour of students and middle level managers that calls for
understanding that both the groups of individuals have no cognizance
of their actual actions. The deliberations derived out of conversation
were taken a step forward for meta-ethical evaluations to portray a
clear picture of ethical behaviour among participants. This study
provides insights for understanding demonstrated unconscious human
behaviour which may fortuitously be termed both ethical and
unethical.
Abstract: Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision methodology.
Abstract: Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: Treatment of tar-containing wastewater is necessary
for the successful operation of biomass gasification plants (BGPs). In
the present study, tar-containing wastewater was treated using lime
and alum for the removal of in-organics, followed by adsorption on
powdered activated carbon (PAC) for the removal of organics. Limealum
experiments were performed in a jar apparatus and activated
carbon studies were performed in an orbital shaker. At optimum
concentrations, both lime and alum individually proved to be capable
of removing color, total suspended solids (TSS) and total dissolved
solids (TDS), but in both cases, pH adjustment had to be carried out
after treatment. The combination of lime and alum at the dose ratio
of 0.8:0.8 g/L was found to be optimum for the removal of inorganics.
The removal efficiency achieved at optimum
concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity,
TSS and TDS, respectively. The major advantages of the lime-alum
combination were observed to be as follows: no requirement of pH
adjustment before and after treatment and good settleability of
sludge. Coagulation-precipitation followed by adsorption on PAC
resulted in 92.3% chemical oxygen demand (COD) removal and
100% phenol removal at equilibrium. Ammonia removal efficiency
was found to be 11.7% during coagulation-flocculation and 36.2%
during adsorption on PAC. Adsorption of organics on PAC in terms
of COD and phenol followed Freundlich isotherm with Kf = 0.55 &
18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may
prove to be one of the fastest and most techno-economically feasible
methods for the treatment of tar-containing wastewater generated
from BGPs.
Abstract: This study demonstrates the feasibility of joining the commercial pure copper plates by friction stir welding (FSW). Microstructure, microhardness and tensile properties in terms of the joint efficiency were found 94.03 % compare to as receive base material (BM). The average hardness at the top was higher than bottom. Hardness of weld zone was higher than the base material. Different microstructure zones were revealed by optical microscopy and scanning electron microscopy. The stirred zone (SZ) exhibited primary two phases namely, recrystallized grains and fine precipitates in matrix of copper.
Abstract: In this paper, the generalized (2+1)-dimensional Calogero-Bogoyavlenskii-Schiff (shortly CBS) equations are investigated. We employ the Hirota-s bilinear method to obtain the bilinear form of CBS equations. Then by the idea of extended homoclinic test approach (shortly EHTA), some exact soliton solutions including breather type solutions are presented.
Abstract: Studies revealing the positive relationship between
trade and income are often criticized with the argument that
“development should mean more than rising incomes". Taking this
argument as a base and utilizing panel data, Davies and Quinlivan [1]
have demonstrated that increases in trade are positively associated
with future increases in social welfare as measured by the Human
Development Index (HDI). The purpose of this study is twofold:
Firstly, utilizing an income based country classification; it is aimed
to investigate whether the positive association between foreign trade
and HDI is valid within all country groups. Secondly, keeping the
same categorization as a base; it is aimed to reveal whether the
positive link between trade and HDI still exists when the income
components of the index are excluded. Employing a panel data
framework of 106 countries, this study reveals that the positive link
between trade and human development is valid only for high and
medium income countries. Moreover, the positive link between trade
and human development diminishes in lower-medium income
countries when only non-income components of the index are taken
into consideration.
Abstract: Calcium [Ca2+] is an important second messenger
which plays an important role in signal transduction. There are
several parameters that affect its concentration profile like buffer
source etc. The effect of stationary immobile buffer on Ca2+
concentration has been incorporated which is a very important
parameter needed to be taken into account in order to make the
model more realistic. Interdependence of all the important parameters
like diffusion coefficient and influx over [Ca2+] profile has been
studied. Model is developed in the form of advection diffusion
equation together with buffer concentration. A program has been
developed using finite volume method for the entire problem and
simulated on an AMD-Turion 32-bit machine to compute the
numerical results.
Abstract: Mathematical and computational modeling of calcium
signalling in nerve cells has produced considerable insights into how
the cells contracts with other cells under the variation of biophysical
and physiological parameters. The modeling of calcium signaling in
astrocytes has become more sophisticated. The modeling effort has
provided insight to understand the cell contraction. Main objective
of this work is to study the effect of voltage gated (Operated)
calcium channel (VOC) on calcium profile in the form of advection
diffusion equation. A mathematical model is developed in the form
of advection diffusion equation for the calcium profile. The model
incorporates the important physiological parameter like diffusion
coefficient etc. Appropriate boundary conditions have been framed.
Finite volume method is employed to solve the problem. A program
has been developed using in MATLAB 7.5 for the entire problem
and simulated on an AMD-Turion 32-bite machine to compute the
numerical results.
Abstract: Disposal of health-care waste (HCW) is considered as
an important environmental problem especially in large cities.
Multiple criteria decision making (MCDM) techniques are apt to deal
with quantitative and qualitative considerations of the health-care
waste management (HCWM) problems. This research proposes a
fuzzy multi-criteria group decision making approach with a multilevel
hierarchical structure including qualitative as well as
quantitative performance attributes for evaluating HCW disposal
alternatives for Istanbul. Using the entropy weighting method,
objective weights as well as subjective weights are taken into account
to determine the importance weighting of quantitative performance
attributes. The results obtained using the proposed methodology are
thoroughly analyzed.
Abstract: In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.
Abstract: Apart from geometry, functionality is one of the most
significant hallmarks of a product. The functionality of a product can
be considered as the fundamental justification for a product
existence. Therefore a functional analysis including a complete and
reliable descriptor has a high potential to improve product
development process in various fields especially in knowledge-based
design. One of the important applications of the functional analysis
and indexing is in retrieval and design reuse concept. More than 75%
of design activity for a new product development contains reusing
earlier and existing design know-how. Thus, analysis and
categorization of product functions concluded by functional
indexing, influences directly in design optimization. This paper
elucidates and evaluates major classes for functional analysis by
discussing their major methods. Moreover it is finalized by
presenting a noble hybrid approach for functional analysis.
Abstract: The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.
Abstract: In this present study, experimental work was
conducted to study the effectiveness of newly innovated steel-CFRP
composite (CFRP laminates sandwiched between two steel strips) as
stirrups. A total numbers of eight concrete beams were tested under
four point loads. Each beam measured 1600 mm long, 160mm width
and 240 mm depth. The beams were reinforced with different shear
reinforcements; one without stirrups, one with steel stirrups and six
with different types and numbers of steel-CRFR stirrups. Test results
indicated that the steel-CFRP stirrups had enhanced the shear
strength capacity of beams. Moreover, the tests revealed that steel-
CFRP stirrups reached to their ultimate tensile strength unlike FRP
stirrups which rupture at much lower level than their ultimate
strength as werereported in various researches.
Abstract: By means of the extended homoclinic test approach (shortly EHTA) with the aid of a symbolic computation system such as Maple, some complexiton type solutions for the (3+1)-dimensional Jimbo-Miwa equation are presented.