Abstract: The objective of this research is to study the physical and mechanical properties and durability of self-compacting mortars prepared by substituting a part of cement up to a percentage of 30% pozzolan according to different Blaine specific surface area (SSB1=7000 cm2/g and SSB=9000 cm2/g)). Order to evaluate durability, mortars were subjected to chemical attacks in various aggressive environments, a solution of a mixture of nitric acid and ammonium nitrate (HNO3 + NH4NO3) and a magnesium sulfate salt solution (MgSO4)) with a concentration of 10%, for a period of one month. This study is complemented by a comparative study of the durability of mortars elaborated with sulphate resistant cement (SRC). The results show that these mortars develop long-term, mechanical and chemical resistance better than mortars based Portland cement with 5% gypsum (CEM 1) and SRC. We found that the mass losses are lowest in mortars elaborated with pozzolanic cement (30% substitution with SSB2) in both of chemical attack solutions (3.28% in the solution acid and 1.16% in the salt solution) and the compressive strength gains of 14.68% and 8.5% respectively in the two media. This is due to the action of pozzolan which fixes portlandite to form hydrated calcium silicate (CSH) from the hydration of tricalcic silicate (C3S).
Abstract: In this paper, a compact wide-band, ultra-thin and flexible slot antenna intended for wearable applications is presented. The presented antenna is designed to provide Wireless Local Area Network (WLAN) and Long Term Evolution (LTE) connectivity. The presented design exhibits a relatively wide bandwidth (1600-3500 MHz below -6 dB impedance bandwidth limit). The antenna is positioned on a 33 mm x 30 mm flexible substrate with a thickness of 50 µm. Antenna properties, such as the far-field radiation patterns, scattering parameter S11 are provided. The presented compact, thin and flexible design along with excellent radiation characteristics are deemed suitable for integration into flexible and wearable devices.
Abstract: Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.
Abstract: Biotechnology is a discipline which explains the use of living organisms and systems to construct a product, or we can define it as an application or technology developed to use biological systems and organisms processes for a specific use. Particularly, it includes cells and its components use for new technologies and inventions. The tools developed can be further used in diverse fields such as agriculture, industry, research and hospitals etc. The 21st century has seen a drastic development and advancement in biotechnology in India. Significant increase in Government of India’s outlays for biotechnology over the past decade has been observed. A sectoral break up of biotechnology-based companies in India shows that most of the companies are agriculture-based companies having interests ranging from tissue culture to biopesticides. Major attention has been given by the companies in health related activities and in environmental biotechnology. The biopharmaceutical, which comprises of vaccines, diagnostic, and recombinant products is the most reliable and largest segment of the Indian Biotech industry. India has developed its vaccine markets and supplies them to various countries. Then there are the bio-services, which mainly comprise of contract researches and manufacturing services. India has made noticeable developments in the field of bio industries including manufacturing of enzymes, biofuels and biopolymers. Biotechnology is also playing a crucial and significant role in the field of agriculture. Traditional methods have been replaced by new technologies that mainly focus on GM crops, marker assisted technologies and the use of biotechnological tools to improve the quality of fertilizers and soil. It may only be a small contributor but has shown to have huge potential for growth. Bioinformatics is a computational method which helps to store, manage, arrange and design tools to interpret the extensive data gathered through experimental trials, making it important in the design of drugs.
Abstract: Deregulation in the power system industry and the invention of new technologies for producing electrical energy has led to innovations in power system planning. Distributed generation (DG) is one of the most attractive technologies that bring different kinds of advantages to a lot of entities, engaged in power systems. In this paper, a model for considering DGs in the power system planning problem is presented. Dynamic power system planning for reduction of maintenance and operational cost is presented in this paper. In addition to that, a modified particle swarm optimization (PSO) is used to find the optimal topology solution. Voltage Profile Improvement Index (VPII) and Line Loss Reduction Index (LLRI) are taken as benefit index of employing DG. The effectiveness of this method is demonstrated through examination of IEEE 30 bus test system.
Abstract: The importance of fruit trees and bushes growing for Romania is due the concordance that exists between the different ecological conditions in natural basins, and the requirements of different species and varieties. There are, in Romania, natural areas dedicated to the main trees species: plum, apple, pear, cherry, sour cherry, finding optimal conditions for harnessing the potential of fruitfulness, making fruit quality both in terms of ratio commercial, and content in active principles. The share of fruits crops in the world economy of agricultural production is due primarily to the role of fruits in nourishment for human, and in the prevention and combating of diseases, in increasing the national income of cultivator countries and to improve comfort for human life. For Romania, the perspectives of the sector are positive, and are due to European funding opportunities, which provide farmers a specialized program that meets the needs of development and modernization of fruit growing industry, cultivation technology and equipment, organization and grouping of producers, creating storage facilities, conditioning, marketing and the joint use of fresh fruit. This paper shows the evolution of fruit growing, in Romania compared to other states. The document presents the current situation of the main tree species both in terms of surface but also of the productions and the role that this activity may have for the development of rural communities.
Abstract: Utilizing waste materials in civil engineering applications has a positive influence on the environment by reducing carbon dioxide emissions and issues associated with waste disposal. Granulated blast furnace slag (GBFS) is a by-product of the iron and steel industry, with millions of tons of slag being annually produced worldwide. Slag has been widely used in structural engineering and for stabilizing clay soils; however, studies on the effect of slag on sandy soils are scarce. This article investigates the effect of slag content on shear strength parameters through direct shear tests and unconsolidated undrained triaxial tests on mixtures of Perth sand and slag. For this purpose, sand-slag mixtures, with slag contents of 2%, 4%, and 6% by weight of samples, were tested with direct shear tests under three normal stress values, namely 100 kPa, 150 kPa, and 200 kPa. Unconsolidated undrained triaxial tests were performed under a single confining pressure of 100 kPa and relative density of 80%. The internal friction angles and shear stresses of the mixtures were determined via the direct shear tests, demonstrating that shear stresses increased with increasing normal stress and the internal friction angles and cohesion increased with increasing slag. There were no significant differences in shear stresses parameters when slag content rose from 4% to 6%. The unconsolidated undrained triaxial tests demonstrated that shear strength increased with increasing slag content.
Abstract: Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.
Abstract: For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.
Abstract: The present paper is concerned with a statistical approach involving latent and manifest variables applied in order to assess the organization's social responsibility performance. The main idea is to develop an assessment tool and a measurement of the Social Responsibility Performance, enabling the company to characterize her performance regarding to the ISO 26000 standard's seven core subjects. For this, we conceptualize a structural equation modeling (SEM) which describes various causal connections between the Social Responsibility’s components. The SEM’s resolution is based on the Partial Least squares (PLS) method and the implementation is running in the XLSTAT software.
Abstract: Corrosion problem which exists in every stage of oil and gas production has been a great challenge to the operators in the industry. The conventional carbon steel with all its inherent advantages has been adjudged susceptible to the aggressive corrosion environment of oilfield. This has aroused increased interest in the use of micro alloyed steels for oil and gas production and transportation. The corrosion behavior of three commercially supplied micro alloyed steels designated as A, B, and C have been investigated with API 5L X65 as reference samples. Electrochemical corrosion tests were conducted in an unbuffered 3.5 wt% NaCl solution saturated with CO2 at 30 0C for 24 hours. Pre-corrosion analyses revealed that samples A, B and X65 consist of ferrite-pearlite microstructures but with different grain sizes, shapes and distribution whereas sample C has bainitic microstructure with dispersed acicular ferrites. The results of the electrochemical corrosion tests showed that within the experimental conditions, the corrosion rate of the samples can be ranked as CR(A)< CR(X65)< CR(B)< CR(C). These results are attributed to difference in microstructures of the samples as depicted by ASTM grain size number in accordance with ASTM E112-12 Standard and ferrite-pearlite volume fractions determined by ImageJ Fiji grain size analysis software.
Abstract: Achieving continuous sustained economic growth and following economic development can be the target for all countries which are looking for it. In this regard, distribution industry plays an important role in growth and development of any nation. So, estimating the efficiency and productivity of the so called industry and identifying factors influencing it, is very necessary. The objective of the present study is to measure the efficiency and productivity of seven branches of Nina Distribution Company using window data envelopment analysis and Malmquist productivity index from spring 2013 to summer 2015. In this study, using criteria of fixed assets, payroll personnel, operating costs and duration of collection of receivables were selected as inputs and people and net sales, gross profit and percentage of coverage to customers were selected as outputs. Then, the process of performance window data envelopment analysis was driven and process efficiency has been measured using Malmquist index. The results indicate that the average technical efficiency of window Data Envelopment Analysis (DEA) model and fluctuating trend is sustainable. But the average management efficiency in window DEA model is related with negative growth (decline) of about 13%. The mean scale efficiency in all windows, except in the second one which is faced with 8%, shows growth of 18% compared to the first window. On the other hand, the mean change in total factor productivity in all branches of the industry shows average negative growth (decrease) of 12% which are the result of a negative change in technology.
Abstract: Brain information transmission in the neuronal network occurs in the form of electrical signals. Neural work transmits information between the neurons or neurons and target cells by moving charged particles in a voltage field; a fraction of the energy utilized in this process is dissipated via entropy generation. Exergy loss and entropy generation models demonstrate the inefficiencies of the communication along the dendritic trees. In this study, neurons of 4 different animals were analyzed with one dimensional cable model with N=6 identical dendritic trees and M=3 order of symmetrical branching. Each branch symmetrically bifurcates in accordance with the 3/2 power law in an infinitely long cylinder with the usual core conductor assumptions, where membrane potential is conserved in the core conductor at all branching points. In the model, exergy loss and entropy generation rates are calculated for each branch of equivalent cylinders of electrotonic length (L) ranging from 0.1 to 1.5 for four different dendritic branches, input branch (BI), and sister branch (BS) and two cousin branches (BC-1 & BC-2). Thermodynamic analysis with the data coming from two different cat motoneuron studies show that in both experiments nearly the same amount of exergy is lost while generating nearly the same amount of entropy. Guinea pig vagal motoneuron loses twofold more exergy compared to the cat models and the squid exergy loss and entropy generation were nearly tenfold compared to the guinea pig vagal motoneuron model. Thermodynamic analysis show that the dissipated energy in the dendritic tress is directly proportional with the electrotonic length, exergy loss and entropy generation. Entropy generation and exergy loss show variability not only between the vertebrate and invertebrates but also within the same class. Concurrently, single action potential Na+ ion load, metabolic energy utilization and its thermodynamic aspect contributed for squid giant axon and mammalian motoneuron model. Energy demand is supplied to the neurons in the form of Adenosine triphosphate (ATP). Exergy destruction and entropy generation upon ATP hydrolysis are calculated. ATP utilization, exergy destruction and entropy generation showed differences in each model depending on the variations in the ion transport along the channels.
Abstract: The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.
Abstract: The paper presents the results and industrial
applications in the production setup period estimation based on
industrial data inherited from the field of polymer cutting. The
literature of polymer cutting is very limited considering the number
of publications. The first polymer cutting machine is known since the
second half of the 20th century; however, the production of polymer
parts with this kind of technology is still a challenging research topic.
The products of the applying industrial partner must met high
technical requirements, as they are used in medical, measurement
instrumentation and painting industry branches. Typically, 20% of
these parts are new work, which means every five years almost the
entire product portfolio is replaced in their low series manufacturing
environment. Consequently, it requires a flexible production system,
where the estimation of the frequent setup periods' lengths is one of
the key success factors. In the investigation, several (input)
parameters have been studied and grouped to create an adequate
training information set for an artificial neural network as a base for
the estimation of the individual setup periods. In the first group,
product information is collected such as the product name and
number of items. The second group contains material data like
material type and colour. In the third group, surface quality and
tolerance information are collected including the finest surface and
tightest (or narrowest) tolerance. The fourth group contains the setup
data like machine type and work shift. One source of these
parameters is the Manufacturing Execution System (MES) but some
data were also collected from Computer Aided Design (CAD)
drawings. The number of the applied tools is one of the key factors
on which the industrial partners’ estimations were based previously.
The artificial neural network model was trained on several thousands
of real industrial data. The mean estimation accuracy of the setup
periods' lengths was improved by 30%, and in the same time the
deviation of the prognosis was also improved by 50%. Furthermore,
an investigation on the mentioned parameter groups considering the
manufacturing order was also researched. The paper also highlights
the manufacturing introduction experiences and further
improvements of the proposed methods, both on the shop floor and
on the quotation preparation fields. Every week more than 100 real
industrial setup events are given and the related data are collected.
Abstract: Model updating method has received increasing
attention in damage detection structures based on measured modal
parameters. Therefore, a probability-based damage detection
(PBDD) procedure based on a model updating procedure is
presented in this paper, in which a one-stage model-based damage
identification technique based on the dynamic features of a structure
is investigated. The presented framework uses a finite element
updating method with a Monte Carlo simulation that considers the
uncertainty caused by measurement noise. Enhanced ideal gas
molecular movement (EIGMM) is used as the main algorithm for
model updating. Ideal gas molecular movement (IGMM) is a multiagent
algorithm based on the ideal gas molecular movement. Ideal
gas molecules disperse rapidly in different directions and cover all
the space inside. This is embedded in the high speed of molecules,
collisions between them and with the surrounding barriers. In IGMM
algorithm to accomplish the optimal solutions, the initial population
of gas molecules is randomly generated and the governing equations
related to the velocity of gas molecules and collisions between those
are utilized. In this paper, an enhanced version of IGMM, which
removes unchanged variables after specified iterations, is developed.
The proposed method is implemented on two numerical examples in
the field of structural damage detection. The results show that the
proposed method can perform well and competitive in PBDD of
structures.
Abstract: In this work, efficient directional coupler composed of
dielectric waveguides and metallic film has been analyzed in details
by simulations using finite element method (FEM). The structure
consists of a step-index fiber with dielectric core, silica cladding, and
a metal nanowire parallel to the core. The results show that an
efficient conversion of optical dielectric modes to long range
plasmonic is possible. Low insertion losses in conjunction with short
coupling length and a broadband operation can be achieved under
certain conditions. This kind of couplers has potential applications for
the design of photonic integrated circuits for signal routing between
dielectric/plasmonic waveguides, sensing, lithography, and optical
storage systems. A high efficient focusing of light in a very small
region can be obtained.
Abstract: In order to reduce numerical computations in the
nonlinear dynamic analysis of seismically base-isolated structures, a
Mixed Explicit-Implicit time integration Method (MEIM) has been
proposed. Adopting the explicit conditionally stable central
difference method to compute the nonlinear response of the base
isolation system, and the implicit unconditionally stable Newmark’s
constant average acceleration method to determine the superstructure
linear response, the proposed MEIM, which is conditionally stable
due to the use of the central difference method, allows to avoid the
iterative procedure generally required by conventional monolithic
solution approaches within each time step of the analysis. The main
aim of this paper is to investigate the stability and computational
efficiency of the MEIM when employed to perform the nonlinear
time history analysis of base-isolated structures with sliding bearings.
Indeed, in this case, the critical time step could become smaller than
the one used to define accurately the earthquake excitation due to the
very high initial stiffness values of such devices. The numerical
results obtained from nonlinear dynamic analyses of a base-isolated
structure with a friction pendulum bearing system, performed by
using the proposed MEIM, are compared to those obtained adopting a
conventional monolithic solution approach, i.e. the implicit
unconditionally stable Newmark’s constant acceleration method
employed in conjunction with the iterative pseudo-force procedure.
According to the numerical results, in the presented numerical
application, the MEIM does not have stability problems being the
critical time step larger than the ground acceleration one despite of
the high initial stiffness of the friction pendulum bearings. In
addition, compared to the conventional monolithic solution approach,
the proposed algorithm preserves its computational efficiency even
when it is adopted to perform the nonlinear dynamic analysis using a
smaller time step.
Abstract: In this paper, an advanced Nonlinear Exponential
Model (NEM), able to simulate the uniaxial dynamic behavior of
seismic isolators having a continuously decreasing tangent stiffness
with increasing displacement in the relatively large displacements
range and a hardening or softening behavior at large displacements, is
presented. The mathematical model is validated by comparing the
experimental force-displacement hysteresis loops obtained during
cyclic tests, conducted on a helical wire rope isolator and a recycled
rubber-fiber reinforced bearing, with those predicted analytically.
Good agreement between the experimental and simulated results
shows that the proposed model can be an effective numerical tool to
predict the force-displacement relationship of seismic isolation
devices within the large displacements range. Compared to the
widely used Bouc-Wen model, unable to simulate the response of
seismic isolators at large displacements, the proposed one allows to
avoid the numerical solution of a first order nonlinear ordinary
differential equation for each time step of a nonlinear time history
analysis, thus reducing the computation effort. Furthermore, the
proposed model can simulate the smooth transition of the hysteresis
loops from small to large displacements by adopting only one set of
five parameters determined from the experimental hysteresis loops
having the largest amplitude.
Abstract: In this paper, a one-dimensional (1d) Parallel Elasto-
Plastic Model (PEPM), able to simulate the uniaxial dynamic
behavior of seismic isolators having a continuously decreasing
tangent stiffness with increasing displacement, is presented. The
parallel modeling concept is applied to discretize the continuously
decreasing tangent stiffness function, thus allowing to simulate the
dynamic behavior of seismic isolation bearings by putting linear
elastic and nonlinear elastic-perfectly plastic elements in parallel. The
mathematical model has been validated by comparing the
experimental force-displacement hysteresis loops, obtained testing a
helical wire rope isolator and a recycled rubber-fiber reinforced
bearing, with those predicted numerically. Good agreement between
the simulated and experimental results shows that the proposed
model can be an effective numerical tool to predict the forcedisplacement
relationship of seismic isolators within relatively large
displacements. Compared to the widely used Bouc-Wen model, the
proposed one allows to avoid the numerical solution of a first order
ordinary nonlinear differential equation for each time step of a
nonlinear time history analysis, thus reducing the computation effort,
and requires the evaluation of only three model parameters from
experimental tests, namely the initial tangent stiffness, the asymptotic
tangent stiffness, and a parameter defining the transition from the
initial to the asymptotic tangent stiffness.