Abstract: This paper employs a new approach to regulate the
blood glucose level of type I diabetic patient under an intensive
insulin treatment. The closed-loop control scheme incorporates
expert knowledge about treatment by using reinforcement learning
theory to maintain the normoglycemic average of 80 mg/dl and the
normal condition for free plasma insulin concentration in severe
initial state. The insulin delivery rate is obtained off-line by using Qlearning
algorithm, without requiring an explicit model of the
environment dynamics. The implementation of the insulin delivery
rate, therefore, requires simple function evaluation and minimal
online computations. Controller performance is assessed in terms of
its ability to reject the effect of meal disturbance and to overcome the
variability in the glucose-insulin dynamics from patient to patient.
Computer simulations are used to evaluate the effectiveness of the
proposed technique and to show its superiority in controlling
hyperglycemia over other existing algorithms
Abstract: Basic objective of this study is to create a regression
analysis method that can estimate the length of a plastic hinge which
is an important design parameter, by making use of the outcomes of
(lateral load-lateral displacement hysteretic curves) the experimental
studies conducted for the reinforced square concrete columns. For
this aim, 170 different square reinforced concrete column tests results
have been collected from the existing literature. The parameters
which are thought affecting the plastic hinge length such as crosssection
properties, features of material used, axial loading level,
confinement of the column, longitudinal reinforcement bars in the
columns etc. have been obtained from these 170 different square
reinforced concrete column tests. In the study, when determining the
length of plastic hinge, using the experimental test results, a
regression analysis have been separately tested and compared with
each other. In addition, the outcome of mentioned methods on
determination of plastic hinge length of the reinforced concrete
columns has been compared to other methods available in the
literature.
Abstract: The use of composite materials in offshore engineering for deep sea oil production riser systems has drawn considerable interest due to the potential weight savings and improvement in durability. The design of composite risers consists of two stages: (1) local design based on critical local load cases, and (2) global analysis of the full length composite riser under global loads and assessment of critical locations. In the first stage, eight different material combinations were selected and their laminate configurations optimised under local load considerations. Stage two includes a final local stress analysis of the critical sections of the riser under the combined loads determined in the global analysis. This paper describes two design methodologies of the composite riser to provide minimum structural weight and shows that the use of off angle fibre orientations in addition to axial and hoop reinforcements offer substantial weight savings and ensure the structural capacity.
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: There are only limited studies that directly correlate
the increase in reinforced concrete (RC) panel structural capacities in
resisting the blast loads with different RC panel structural properties
in terms of blast loading characteristics, RC panel dimensions, steel
reinforcement ratio and concrete material strength. In this paper,
numerical analyses of dynamic response and damage of the one-way
RC panel to blast loads are carried out using the commercial software
LS-DYNA. A series of simulations are performed to predict the blast
response and damage of columns with different level and magnitude
of blast loads. The numerical results are used to develop pressureimpulse
(P-I) diagrams of one-way RC panels. Based on the
numerical results, the empirical formulae are derived to calculate the
pressure and impulse asymptotes of the P-I diagrams of RC panels.
The results presented in this paper can be used to construct P-I
diagrams of RC panels with different concrete and reinforcement
properties. The P-I diagrams are very useful to assess panel capacities
in resisting different blast loads.
Abstract: This paper deals with behavior and capacity of
punching shear force for flat slabs produced from steel fiber
reinforced self compacting concrete (SFRSCC) by application
nonlinear finite element method. Nonlinear finite element analysis on
nine slab specimens was achieved by using ANSYS software. A
general description of the finite element method, theoretical modeling
of concrete and reinforcement are presented. The nonlinear finite
element analysis program ANSYS is utilized owing to its capabilities
to predict either the response of reinforced concrete slabs in the post
elastic range or the ultimate strength of a flat slabs produced from
steel fiber reinforced self compacting concrete (SFRSCC). In order to
verify the analytical model used in this research using test results of
the experimental data, the finite element analysis were performed
then a parametric study of the effect ratio of flexural reinforcement,
ratio of the upper reinforcement, and volume fraction of steel fibers
were investigated. A comparison between the experimental results
and those predicted by the existing models are presented. Results and
conclusions may be useful for designers, have been raised, and
represented.
Abstract: In this study, an ablation, mechanical and thermal properties of a rocket motor insulation from phenolic/ fiber matrix composites forming a laminate with different fiber between fiberglass and locally available synthetic fibers. The phenolic/ fiber matrix composites was mechanics and thermal properties by means of tensile strength, ablation, TGA and DSC. The design of thermal insulation involves several factors.Determined the mechanical properties according to MIL-I-24768: Density >1.3 g/cm3, Tensile strength >103 MPa and Ablation
Abstract: It is necessary to evaluate the bridges conditions and
strengthen bridges or parts of them. The reinforcement necessary due
to some reasons can be summarized as: First, a changing in use of
bridge could produce internal forces in a part of structural which
exceed the existing cross-sectional capacity. Second, bridges may
also need reinforcement because damage due to external factors
which reduced the cross-sectional resistance to external loads. One of
other factors could listed here its misdesign in some details, like
safety of bridge or part of its.This article identify the design demands
of Qing Shan bridge located in is in Heilongjiang Province He gang -
Nen Jiang Road 303 provincial highway, Wudalianchi area, China, is
an important bridge in the urban areas. The investigation program
was include the observation and evaluate the damage in T- section
concrete beams , prestressed concrete box girder bridges section in
additional evaluate the whole state of bridge includes the pier ,
abutments , bridge decks, wings , bearing and capping beam, joints,
........etc. The test results show that the bridges in general structural
condition are good. T beam span No 10 were observed, crack
extended upward along the ribbed T beam, and continue to the T
beam flange. Crack width varying between 0.1mm to 0.4mm, the
maximum about 0.4mm. The bridge needs to be improved flexural
bending strength especially at for T beam section.
Abstract: In this study the effect of incorporation of recycled
glass-fibre reinforced polymer (GFRP) waste materials, obtained by
means of milling processes, on mechanical behaviour of polyester
polymer mortars was assessed. For this purpose, different contents of
recycled GFRP waste powder and fibres, with distinct size gradings,
were incorporated into polyester based mortars as sand aggregates
and filler replacements. Flexural and compressive loading capacities
were evaluated and found better than unmodified polymer mortars.
GFRP modified polyester based mortars also show a less brittle
behaviour, with retention of some loading capacity after peak load.
Obtained results highlight the high potential of recycled GFRP waste
materials as efficient and sustainable reinforcement and admixture for
polymer concrete and mortars composites, constituting an emergent
waste management solution.
Abstract: This article presents the analysis of experimental values regarding cracking pattern, specific strains and deformability for reinforced high strength concrete beams. The beams have the concrete class C80/95 and a longitudinal reinforcement ratio of 2.01%, respectively 3.39%. The elements were subjected to flexure under static short-term and long-term loading. The experimental values are compared with calculation values using the design relationships according to Eurocode 2.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
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: Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.
Abstract: This paper focuses on PSS/E modeling of wind farms
of Doubly-fed Induction Generator (DFIG) type and their impact on
issues of power system operation. Since Wind Turbine Generators
(WTG) don-t have the same characteristics as synchronous
generators, the appropriate modeling of wind farms is essential for
transmission system operators to analyze the best options of
transmission grid reinforcements as well as to evaluate the wind
power impact on reliability and security of supply. With the high
excepted penetration of wind power into the power system a
simultaneous loss of Wind Farm generation will put at risk power
system security and reliability. Therefore, the main wind grid code
requirements concern the fault ride through capability and frequency
operation range of wind turbines. In case of grid faults wind turbines
have to supply a definite reactive power depending on the
instantaneous voltage and to return quickly to normal operation.
Abstract: This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.
Abstract: The use of externally bonded Carbon Fiber
Reinforced Polymer (CFRP) reinforcement has proven to be an
effective technique to strengthen steel structures. An experimental
study on CFRP bonded steel plate with double strap joint has been
conducted and specimens are tested under tensile loadings. An
empirical model has been developed using stress-based approach to
predict ultimate capacity of the CFRP bonded steel structure. The
results from the model are comparable with the experimental result
with a reasonable accuracy.
Abstract: High strength concrete (HSC) provides high strength
but lower ductility than normal strength concrete. This low ductility
limits the benefit of using HSC in building safe structures. On the
other hand, when designing reinforced concrete beams, designers
have to limit the amount of tensile reinforcement to prevent the
brittle failure of concrete. Therefore the full potential of the use of
steel reinforcement can not be achieved. This paper presents the idea
of confining concrete in the compression zone so that the HSC will
be in a state of triaxial compression, which leads to improvements in
strength and ductility. Five beams made of HSC were cast and tested.
The cross section of the beams was 200×300 mm, with a length of 4
m and a clear span of 3.6 m subjected to four-point loading, with
emphasis placed on the midspan deflection. The first beam served as
a reference beam. The remaining beams had different tensile
reinforcement and the confinement shapes were changed to gauge
their effectiveness in improving the strength and ductility of the
beams. The compressive strength of the concrete was 85 MPa and the
tensile strength of the steel was 500 MPa and for the stirrups and
helixes was 250 MPa. Results of testing the five beams proved that
placing helixes with different diameters as a variable parameter in the
compression zone of reinforced concrete beams improve their
strength and ductility.
Abstract: A novel biologically inspired controller for the autonomous
navigation of a mobile robot in an evasion task is
proposed. The controller takes advantage of the environment by
calculating a measure of danger and subsequently choosing the
parameters of a reinforcement learning based decision process.
Two different reinforcement learning algorithms were used: Qlearning
and Sarsa (λ). Simulations show that selecting dynamic
parameters reduce the time while executing the decision making
process, so the robot can obtain a policy to succeed in an escaping
task in a realistic time.
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.