Abstract: An array antenna system with innovative signal
processing can improve the resolution of a source direction of arrival
(DoA) estimation. High resolution techniques take the advantage of
array antenna structures to better process the incoming waves. They
also have the capability to identify the direction of multiple targets.
This paper investigates performance of the DOA estimation
algorithm namely; Capon and MUSIC on the uniform linear array
(ULA). The simulation results show that in Capon and MUSIC
algorithm the resolution of the DOA techniques improves as number
of snapshots, number of array elements, signal-to-noise ratio and
separation angle between the two sources θ increases.
Abstract: This paper provides an exergy analysis of the multistage refrigeration cycle used for C2+ recovery plant. The behavior of an industrial refrigeration cycle with refrigerant propane has been investigated by the exergy method. A computational model based on the exergy analysis is presented for the investigation of the effects of the valves on the exergy losses, the second law of efficiency, and the coefficient of performance (COP) of a vapor compression refrigeration cycle. The equations of exergy destruction and exergetic efficiency for the main cycle components such as evaporators, condensers, compressors, and expansion valves are developed. The relations for the total exergy destruction in the cycle and the cycle exergetic efficiency are obtained. An ethane recovery unit with its refrigeration cycle has been simulated to prepare the exergy analysis. Using a typical actual work input value; the exergetic efficiency of the refrigeration cycle is determined to be 39.90% indicating a great potential for improvements. The simulation results reveal that the exergetic efficiencies of the heat exchanger and expansion sections get the lowest rank among the other compartments of refrigeration cycle. Refrigeration calculations have been carried out through the analysis of T–S and P–H diagrams where coefficient of performance (COP) was obtained as 1.85. The novelty of this article includes the effect and sensitivity analysis of molar flow, pressure drops and temperature on the exergy efficiency and coefficient of performance of the cycle.
Abstract: The prediction of long-term deformations of concrete and reinforced concrete structures has been a field of extensive research and several different creep models have been developed so far. Most of the models were developed for constant concrete stresses, thus, in case of varying stresses a specific superposition principle or time-integration, respectively, is necessary. Nowadays, when modeling concrete creep the engineering focus is rather on the application of sophisticated time-integration methods than choosing the more appropriate creep model. For this reason, this paper presents a method to quantify the uncertainties of creep prediction originating from the selection of creep models or from the time-integration methods. By adapting variance based global sensitivity analysis, a methodology is developed to quantify the influence of creep model selection or choice of time-integration method. Applying the developed method, general recommendations how to model creep behavior for varying stresses are given.
Abstract: The present study focuses on the discussion over the
parameter of Artificial Neural Network (ANN). Sensitivity analysis is
applied to assess the effect of the parameters of ANN on the prediction
of turbidity of raw water in the water treatment plant. The result shows
that transfer function of hidden layer is a critical parameter of ANN.
When the transfer function changes, the reliability of prediction of
water turbidity is greatly different. Moreover, the estimated water
turbidity is less sensitive to training times and learning velocity than
the number of neurons in the hidden layer. Therefore, it is important to
select an appropriate transfer function and suitable number of neurons
in the hidden layer in the process of parameter training and validation.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: Along with forward supply chain organization needs
to consider the impact of reverse logistics due to its economic
advantage, social awareness and strict legislations. In this paper, we
develop a system dynamics framework for a closed-loop supply
chain with fuzzy demand and fuzzy collection rate by incorporating
product exchange policy in forward channel and various recovery
options in reverse channel. The uncertainty issues associated with
acquisition and collection of used product have been quantified using
possibility measures. In the simulation study, we analyze order
variation at both retailer and distributor level and compare bullwhip
effects of different logistics participants over time between the
traditional forward supply chain and the closed-loop supply chain.
Our results suggest that the integration of reverse logistics can reduce
order variation and bullwhip effect of a closed-loop system. Finally,
sensitivity analysis is performed to examine the impact of various
parameters on recovery process and bullwhip effect.
Abstract: The paper discusses a 3D numerical solution of the inverse boundary problem for a continuous casting process of alloy. The main goal of the analysis presented within the paper was to estimate heat fluxes along the external surface of the ingot. The verified information on these fluxes was crucial for a good design of a mould, effective cooling system and generally the whole caster. In the study an enthalpy-porosity technique implemented in Fluent package was used for modeling the solidification process. In this method, the phase change interface was determined on the basis of the liquid fraction approach. In inverse procedure the sensitivity analysis was applied for retrieving boundary conditions. A comparison of the measured and retrieved values showed a high accuracy of the computations. Additionally, the influence of the accuracy of measurements on the estimated heat fluxes was also investigated.
Abstract: This paper undertakes the problem of optimal
capacitor placement in a distribution system. The problem is how to
optimally determine the locations to install capacitors, the types and
sizes of capacitors to he installed and, during each load level,the
control settings of these capacitors in order that a desired objective
function is minimized while the load constraints,network constraints
and operational constraints (e.g. voltage profile) at different load
levels are satisfied. The problem is formulated as a combinatorial
optimization problem with a nondifferentiable objective function.
Four solution mythologies based on algorithms (GA),tabu search
(TS), and hybrid GA-SA algorithms are presented.The solution
methodologies are preceded by a sensitivity analysis to select the
candidate capacitor installation locations.
Abstract: Perishable goods constitute a large portion of retailer inventory and lose value with time due to deterioration and/or obsolescence. Retailers dealing with such goods required considering the factors of short shelf life and the dependency of sales on inventory displayed in determining optimal procurement policy. Many retailers follow the practice of using two bins - primary bin sales fresh items at a list price and secondary bin sales unsold items at a discount price transferred from primary bin on attaining certain age. In this paper, mathematical models are developed for primary bin and for secondary bin that maximizes profit with decision variables of order quantities, optimal review period and optimal selling price at secondary bin. The demand rates in two bins are assumed to be deterministic and dependent on displayed inventory level, price and age but independent of each other. The validity of the model is shown by solving an example and the sensitivity analysis of the model is also reported.
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Abstract: In this paper, an attempt has been made to obtain nonsensitive
solutions in the multi-objective optimization of a
photovoltaic/thermal (PV/T) air collector. The selected objective
functions are overall energy efficiency and exergy efficiency.
Improved thermal, electrical and exergy models are used to calculate
the thermal and electrical parameters, overall energy efficiency,
exergy components and exergy efficiency of a typical PV/T air
collector. A computer simulation program is also developed. The
results of numerical simulation are in good agreement with the
experimental measurements noted in the previous literature. Finally,
multi-objective optimization has been carried out under given
climatic, operating and design parameters. The optimized ranges of
inlet air velocity, duct depth and the objective functions in optimal
Pareto front have been obtained. Furthermore, non-sensitive solutions
from energy or exergy point of view in the results of multi-objective
optimization have been shown.
Abstract: Gas condensate Reservoirs show complicated thermodynamic behavior when their pressure reduces to under dew point pressure. Condensate blockage around the producing well cause significant reduction of production rate as well bottom-hole pressure drops below saturation pressure. The main objective of this work was to examine the well test analysis of naturally fractured lean gas condensate reservoir and investigate the effect of condensate formed around the well-bore on behavior of single phase pseudo pressure and its derivative curves. In this work a naturally fractured lean gas condensate reservoir is simulated with compositional simulator. Different sensitivity analysis done on Corry parameters and result of simulator is feed to analytical well testing software. For consideration of these phenomena eighteen compositional models with Capillary number effect are constructed. Matrix relative permeability obeys Corry relative permeability and relative permeability in fracture is linear. Well testing behavior of these models are studied and interpreted. Results show different sensitivity analysis on relative permeability of matrix does not have strong effect on well testing behavior even most part of the matrix around the well is occupied with condensate.
Abstract: The bridge vibration due to traffic loading has been a
subject of extensive research during the last decades. A number of
these studies are concerned with the effects of the unevenness of
roadways on the dynamic responses of highway bridges. The road
unevenness is often described as a random process that constitutes
of different wavelengths. Thus, the study focuses on examining
the effects of the random description of roadways on the dynamic
response and its variance. A new setting of variance based sensitivity
analysis is proposed and used to identify and quantify the
contributions of the roadway-s wavelengths to the variance of the
dynamic response. Furthermore, the effect of the vehicle-s speed on
the dynamic response is studied.
Abstract: Sensors possess several properties of physical
measures. Whether devices that convert a sensed signal into an
electrical signal, chemical sensors and biosensors, thus all these
sensors can be considered as an interface between the physical and
electrical equipment. The problem is the analysis of the multitudes of
saved settings as input variables. However, they do not all have the
same level of influence on the outputs. In order to identify the most
sensitive parameters, those that can guide users in gathering
information on the ground and in the process of model calibration
and sensitivity analysis for the effect of each change made.
Mathematical models used for processing become very complex.
In this paper a fuzzy rule-based system is proposed as a solution
for this problem. The system collects the available signals
information from sensors. Moreover, the system allows the study of
the influence of the various factors that take part in the decision
system. Since its inception fuzzy set theory has been regarded as a
formalism suitable to deal with the imprecision intrinsic to many
problems. At the same time, fuzzy sets allow to use symbolic models.
In this study an example was applied for resolving variety of
physiological parameters that define human health state. The
application system was done for medical diagnosis help. The inputs
are the signals expressed the cardiovascular system parameters, blood
pressure, Respiratory system paramsystem was done, it will be able
to predict the state of patient according any input values.
Abstract: This research aims to analyze the regenerative burner and the recuperative burner for the different reheating furnaces in the steel industry. The warm air temperatures of the burners are determined to suit with the sizes of the reheating furnaces by considering the air temperature, the fuel cost and the investment cost. The calculations of the payback period and the net present value are studied to compare the burners for the different reheating furnaces. The energy balance is utilized to calculate and compare the energy used in the different sizes of reheating furnaces for each burner. It is found that the warm air temperature is different if the sizes of reheating furnaces are varied. Based on the considerations of the net present value and the payback period, the regenerative burner is suitable for all plants at the same life of the burner. Finally, the sensitivity analysis of all factors has been discussed in this research.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue –despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: Actual load, material characteristics and other
quantities often differ from the design values. This can cause worse
function, shorter life or failure of a civil engineering structure, a
machine, vehicle or another appliance. The paper shows main causes
of the uncertainties and deviations and presents a systematic
approach and efficient tools for their elimination or mitigation of
consequences. Emphasis is put on the design stage, which is most
important for reliability ensuring. Principles of robust design and
important tools are explained, including FMEA, sensitivity analysis
and probabilistic simulation methods. The lifetime prediction of
long-life objects can be improved by long-term monitoring of the
load response and damage accumulation in operation. The condition
evaluation of engineering structures, such as bridges, is often based
on visual inspection and verbal description. Here, methods based on
fuzzy logic can reduce the subjective influences.
Abstract: In the paper, the results of sensitivity analysis of the influence of initial imperfections on the web stress state of a thinwalled girder are presented. The results of the study corroborate a very good and effective agreement of experiments with theory. Most input random quantities were found experimentally. The change of sensitivity coefficients in dependence on working load value is analysed. The stress was analysed by means of a geometrically and materially non-linear solution by applying the program ANSYS. This research study offers important background for theoretical studies of stability problems, post-critical effects and limit states of thin-walled steel structures.