Abstract: The paper deals with the analysis of the dynamic
response of footbridges under human - induced dynamic loads.
This is a frequently occurring and often dominant load for
footbridges as it stems from the very purpose of a footbridge - to
convey pedestrian. Due to the emergence of new materials and
advanced engineering technology, slender footbridges are
increasingly becoming popular to satisfy the modern transportation
needs and the aesthetical requirements of the society. These
structures however are always lively with low stiffness, low mass,
low damping and low natural frequencies. As a consequence, they are
prone to vibration induced by human activities and can suffer severe
vibration serviceability problems, particularly in the lateral direction.
Pedestrian bridges are designed according to first and second limit
states, these are the criteria involved in response to static design load.
However, it is necessary to assess the dynamic response of bridge
design load on pedestrians and assess it impact on the comfort of the
user movement. Usually the load is considered a person or a small
group which can be assumed in perfect motion synchronization.
Already one person or small group can excite significant vibration of
the deck. In order to calculate the dynamic response to the movement
of people, designer needs available and suitable computational model
and criteria. For the calculation program ANSYS based on finite
element method was used.
Abstract: The small interfering RNA (siRNA) alters the
regulatory role of mRNA during gene expression by translational
inhibition. Recent studies show that upregulation of mRNA because
serious diseases like cancer. So designing effective siRNA with good
knockdown effects plays an important role in gene silencing. Various
siRNA design tools had been developed earlier. In this work, we are
trying to analyze the existing good scoring second generation siRNA
predicting tools and to optimize the efficiency of siRNA prediction
by designing a computational model using Artificial Neural Network
and whole stacking energy (%G), which may help in gene silencing
and drug design in cancer therapy. Our model is trained and tested
against a large data set of siRNA sequences. Validation of our results
is done by finding correlation coefficient of experimental versus
observed inhibition efficacy of siRNA. We achieved a correlation
coefficient of 0.727 in our previous computational model and we
could improve the correlation coefficient up to 0.753 when the
threshold of whole tacking energy is greater than or equal to -32.5
kcal/mol.
Abstract: Temperature, relative humidity and overhygroscopic
moisture fields in a sandstone wall provided with interior thermal
insulation were calculated in order to assess the hygric performance
of the retrofitted wall. Computational simulations showed that during
the time period of 10 years which was subject of investigation no
overhygroscopic moisture appeared in the analyzed building
envelope so that it performed in a satisfactory way from the hygric
point of view.
Abstract: In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: The paper presents the results of simple measurements
conducted on a model of a wind-driven venturi-type room ventilator.
The ventilator design is new and was developed employing
mathematical modeling. However, the computational model was not
validated experimentally for the particular application considered.
The paper presents the performance of the ventilator model under
laboratory conditions, for five different wind tunnel speeds. The
results are used to both demonstrate the effectiveness of the new
design and to validate the computational model employed to develop
it.
Abstract: In this research, heat transfer of a poly Ethylene
fluidized bed reactor without reaction were studied experimentally
and computationally at different superficial gas velocities. A multifluid
Eulerian computational model incorporating the kinetic theory
for solid particles was developed and used to simulate the heat
conducting gas–solid flows in a fluidized bed configuration.
Momentum exchange coefficients were evaluated using the Syamlal–
O-Brien drag functions. Temperature distributions of different phases
in the reactor were also computed. Good agreement was found
between the model predictions and the experimentally obtained data
for the bed expansion ratio as well as the qualitative gas–solid flow
patterns. The simulation and experimental results showed that the gas
temperature decreases as it moves upward in the reactor, while the
solid particle temperature increases. Pressure drop and temperature
distribution predicted by the simulations were in good agreement
with the experimental measurements at superficial gas velocities
higher than the minimum fluidization velocity. Also, the predicted
time-average local voidage profiles were in reasonable agreement
with the experimental results. The study showed that the
computational model was capable of predicting the heat transfer and
the hydrodynamic behavior of gas-solid fluidized bed flows with
reasonable accuracy.
Abstract: In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.
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: A novel methodology has been used to design an
evaporator coil of a refrigerant. The methodology used is through a
complete Computer Aided Design /Computer Aided Engineering
approach, by means of a Computational Fluid Dynamic/Finite
Element Analysis model which is executed many times for the
thermal-fluid exploration of several designs' configuration by an
commercial optimizer. Hence the design is carried out automatically
by parallel computations, with an optimization package taking the
decisions rather than the design engineer. The engineer instead takes
decision regarding the physical settings and initializing of the
computational models to employ, the number and the extension of the
geometrical parameters of the coil fins and the optimization tools to
be employed. The final design of the coil geometry found to be better
than the initial design.
Abstract: The present paper deals with the experimental and
computational study of axial collapse of the aluminum metallic shells
having combined tube-frusta geometry between two parallel plates.
Shells were having bottom two third lengths as frusta and remaining
top one third lengths as tube. Shells were compressed to recognize
their modes of collapse and associated energy absorption capability.
An axisymmetric Finite Element computational model of collapse
process is presented and analysed, using a non-linear FE code
FORGE2. Six noded isoparametric triangular elements were used to
discretize the deforming shell. The material of the shells was
idealized as rigid visco-plastic. To validate the computational model
experimental and computed results of the deformed shapes and their
corresponding load-compression and energy-compression curves
were compared. With the help of the obtained results progress of the
axisymmetric mode of collapse has been presented, analysed and
discussed.
Abstract: Stochastic models of biological networks are well established in systems biology, where the computational treatment of such models is often focused on the solution of the so-called chemical master equation via stochastic simulation algorithms. In contrast to this, the development of storage-efficient model representations that are directly suitable for computer implementation has received significantly less attention. Instead, a model is usually described in terms of a stochastic process or a "higher-level paradigm" with graphical representation such as e.g. a stochastic Petri net. A serious problem then arises due to the exponential growth of the model-s state space which is in fact a main reason for the popularity of stochastic simulation since simulation suffers less from the state space explosion than non-simulative numerical solution techniques. In this paper we present transition class models for the representation of biological network models, a compact mathematical formalism that circumvents state space explosion. Transition class models can also serve as an interface between different higher level modeling paradigms, stochastic processes and the implementation coded in a programming language. Besides, the compact model representation provides the opportunity to apply non-simulative solution techniques thereby preserving the possible use of stochastic simulation. Illustrative examples of transition class representations are given for an enzyme-catalyzed substrate conversion and a part of the bacteriophage λ lysis/lysogeny pathway.
Abstract: NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.
Abstract: The dynamics of Min proteins plays a center role in
accurate cell division. Although the nucleoids may presumably play
an important role in prokaryotic cell division, there is a lack of
models to account for its participation. In this work, we apply the
lattice Boltzmann method to investigate protein oscillation based on a
mesoscopic model that takes into account the nucleoid-s role. We
found that our numerical results are in reasonably good agreement
with the previous experimental results On comparing with the other
computational models without the presence of nucleoids, the
highlight of our finding is that the local densities of MinD and MinE
on the cytoplasmic membrane increases, especially along the cell
width, when the size of the obstacle increases, leading to a more
distinct cap-like structure at the poles. This feature indicated the
realistic pattern and reflected the combination of Min protein
dynamics and nucleoid-s role.
Abstract: A Watson-Crick automaton is recently introduced as a
computational model of DNA computing framework. It works on
tapes consisting of double stranded sequences of symbols. Symbols
placed on the corresponding cells of the double-stranded sequences are
related by a complimentary relation. In this paper, we investigate a
variation of Watson-Crick automata in which both heads read the tape
in reverse directions. They are called reverse Watson-Crick finite
automata (RWKFA). We show that all of following four classes, i.e.,
simple, 1-limited, all-final, all-final and simple, are equal to
non-restricted version of RWKFA.
Abstract: This paper present a new way to find the aerodynamic
characteristic equation of missile for the numerical trajectories
prediction more accurate. The goal is to obtain the polynomial
equation based on two missile characteristic parameters, angle of
attack (α ) and flight speed (ν ). First, the understudied missile is
modeled and used for flow computational model to compute
aerodynamic force and moment. Assume that performance range of
understudied missile where range -10< α
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.
Abstract: The presented article deals with the description of a
numerical model of a corridor at a Central Interim Spent Fuel Storage
Facility (hereinafter CISFSF). The model takes into account the
effect of air flows on the temperature of stored waste. The
computational model was implemented in the ANSYS/CFX
programming environment in the form of a CFD task solution, which
was compared with an approximate analytical calculation. The article
includes a categorization of the individual alternatives for the
ventilation of such underground systems. The aim was to evaluate a
ventilation system for a CISFSF with regard to its stability and
capacity to provide sufficient ventilation for the removal of heat
produced by stored casks with spent nuclear fuel.
Abstract: In the territories where high-intensity
earthquakes are frequent is paid attention to the solving of the
seismic problems. In the paper are described two
computational model variants based on finite element method
of the construction with different subsoil simulation (rigid or
elastic subsoil) is used. For simulation and calculations
program system based on method final elements ANSYS was
used. Seismic responses calculations of residential building
structure were effected on loading characterized by
accelerogram for comparing with the responses spectra
method.
Abstract: Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.