Abstract: Steel surface defect detection is essentially one of
pattern recognition problems. Support Vector Machines (SVMs) are
known as one of the most proper classifiers in this application. In this
paper, we introduce a more accurate classification method by using
SVMs as our final classifier of the inspection system. In this scheme,
multiclass classification task is performed based on the "one-againstone"
method and different kernels are utilized for each pair of the
classes in multiclass classification of the different defects.
In the proposed system, a decision tree is employed in the first
stage for two-class classification of the steel surfaces to "defect" and
"non-defect", in order to decrease the time complexity. Based on
the experimental results, generated from over one thousand images,
the proposed multiclass classification scheme is more accurate than
the conventional methods and the overall system yields a sufficient
performance which can meet the requirements in steel manufacturing.
Abstract: Within this work High Temperature Single Impact
Studies were performed to evaluate deformation mechanisms at
different energy and momentum levels. To show the influence of
different microstructures and hardness levels and their response to
single impacts four different materials were tested at various
temperatures up to 700°C. One carbide reinforced NiCrBSi based
Metal Matrix Composite and three different steels were tested. The
aim of this work is to determine critical energies for fracture
appearance and the materials response at different energy and
momenta levels. Critical impact loadings were examined at elevated
temperatures to limit operating conditions in impact dominated
regimes at elevated temperatures. The investigations on the
mechanisms were performed using different means of microscopy at
the surface and in metallographic cross sections. Results indicate
temperature dependence of the occurrence of cracks in hardphase
rich materials, such as Metal Matrix Composites High Speed Steels
and the influence of different impact momenta at constant energies
on the deformation of different steels.
Abstract: In this paper, transversal vibration of buried pipelines
during loading induced by underground explosions is analyzed. The
pipeline is modeled as an infinite beam on an elastic foundation, so
that soil-structure interaction is considered by means of transverse
linear springs along the pipeline. The pipeline behavior is assumed to
be ideal elasto-plastic which an ultimate strain value limits the plastic
behavior. The blast loading is considered as a point load, considering
the affected length at some point of the pipeline, in which the
magnitude decreases exponentially with time. A closed-form solution
for the quasi-static problem is carried out for both elastic and elasticperfect
plastic behaviors of pipe materials. At the end, a comparative
study on steel and polyethylene pipes with different sizes buried in
various soil conditions, affected by a predefined underground
explosion is conducted, in which effect of each parameter is
discussed.
Abstract: Conventionally the selection of parameters depends
intensely on the operator-s experience or conservative technological
data provided by the EDM equipment manufacturers that assign
inconsistent machining performance. The parameter settings given by
the manufacturers are only relevant with common steel grades. A
single parameter change influences the process in a complex way.
Hence, the present research proposes artificial neural network (ANN)
models for the prediction of surface roughness on first commenced
Ti-15-3 alloy in electrical discharge machining (EDM) process. The
proposed models use peak current, pulse on time, pulse off time and
servo voltage as input parameters. Multilayer perceptron (MLP) with
three hidden layer feedforward networks are applied. An assessment
is carried out with the models of distinct hidden layer. Training of the
models is performed with data from an extensive series of
experiments utilizing copper electrode as positive polarity. The
predictions based on the above developed models have been verified
with another set of experiments and are found to be in good
agreement with the experimental results. Beside this they can be
exercised as precious tools for the process planning for EDM.
Abstract: Bendability is constrained by maximum top roller
load imparting capacity of the machine. Maximum load is
encountered during the edge pre-bending stage of roller bending.
Capacity of 3-roller plate bending machine is specified by
maximum thickness and minimum shell diameter combinations that
can be pre-bend for given plate material of maximum width.
Commercially available plate width or width of the plate that can be
accommodated on machine decides the maximum rolling width.
Original equipment manufacturers (OEM) provide the machine
capacity chart based on reference material considering perfectly
plastic material model. Reported work shows the bendability analysis
of heavy duty 3-roller plate bending machine. The input variables for
the industry are plate thickness, shell diameter and material property
parameters, as it is fixed by the design. Analytical models of
equivalent thickness, equivalent width and maximum width based on
power law material model were derived to study the bendability.
Equation of maximum width provides bendability for designed
configuration i.e. material property, shell diameter and thickness
combinations within the machine limitations. Equivalent thicknesses
based on perfectly plastic and power law material model were
compared for four different materials grades of C-Mn steel in order
to predict the bend-ability. Effect of top roller offset on the
bendability at maximum top roller load imparting capacity is
reported.
Abstract: In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.
Abstract: In the present work, behavior of inoxydable steel as
reinforcement bar in composite concrete is being investigated. The
bar-concrete adherence in reinforced concrete (RC) beam is studied
and focus is made on the tension stiffening parameter. This study
highlighted an approach to observe this interaction behavior in
bending test instead of direct tension as per reported in many
references. The approach resembles actual loading condition of the
structural RC beam. The tension stiffening properties are then
applied to numerical finite element analysis (FEA) to verify their
correlation with laboratory results. Comparison with laboratory
shows a good correlation between the two. The experimental settings
is able to determine tension stiffening parameters in RC beam and
the modeling strategies made in ABAQUS can closely represent the
actual condition. Tension stiffening model used can represent the
interaction properties between inoxydable steel and concrete.
Abstract: This paper reports on the results of experimental
investigations of flash evaporation from superheated jet issues
vertically upward from a round straight nozzle of 81.3 mm diameter.
For the investigated range of jet superheat degree and velocity, it was
shown that flash evaporation enhances with initial temperature
increase. Due to the increase of jet inertia and subsequently the delay
of jet shattering, increase of jet velocity was found to result in
increase of evaporation "delay period". An empirical equation
predicts the jet evaporation completion height was developed, this
equation is thought to be useful in designing the flash evaporation
chamber. In attempts for enhancement of flash evaporation, use of
steel wire mesh located at short distance downstream was found
effective with no consequent pressure drop.
Abstract: Understanding of how and where NOx formation
occurs in industrial burner is very important for efficient and clean
operation of utility burners. Also the importance of this problem is
mainly due to its relation to the pollutants produced by more burners
used widely of gas turbine in thermal power plants and glass and steel
industry.
In this article, a numerical model of an industrial burner operating
in MILD combustion is validated with experimental data.. Then
influence of air flow rate and air temperature on combustor
temperature profiles and NOX product are investigated. In order to
modification this study reports on the effects of fuel and air dilution
(with inert gases H2O, CO2, N2), and also influence of lean-premixed
of fuel, on the temperature profiles and NOX emission.
Conservation equations of mass, momentum and energy, and
transport equations of species concentrations, turbulence, combustion
and radiation modeling in addition to NO modeling equations were
solved together to present temperature and NO distribution inside the
burner.
The results shows that dilution, cause to a reduction in value of
temperature and NOX emission, and suppresses any flame
propagation inside the furnace and made the flame inside the furnace
invisible. Dilution with H2O rather than N2 and CO2 decreases further
the value of the NOX. Also with raise of lean-premix level, local
temperature of burner and the value of NOX product are decreases
because of premixing prevents local “hot spots" within the combustor
volume that can lead to significant NOx formation. Also leanpremixing
of fuel with air cause to amount of air in reaction zone is
reach more than amount that supplied as is actually needed to burn
the fuel and this act lead to limiting NOx formation
Abstract: Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Abstract: The commercial finite element program LS-DYNA was employed to evaluate the response and energy absorbing capacity of cylindrical metal tubes that are externally wrapped with composite. The effects of composite wall thickness, loading conditions and fiber ply orientation were examined. The results demonstrate that a wrapped composite can be utilized effectively to enhance the crushing characteristics and energy absorbing capacity of the tubes. Increasing the thickness of the composite increases the mean force and the specific energy absorption under both static and dynamic crushing. The ply pattern affects the energy absorption capacity and the failure mode of the metal tube and the composite material property is also significant in determining energy absorption efficiency.
Abstract: The effect of different tempering temperatures and heat treatment times on the corrosion resistance of austenitic stainless steels in oxalic acid was studied in this work using conventional weight loss and electrochemical measurements. Typical 304 and 316 stainless steel samples were tempered at 150oC, 250oC and 350oC after being austenized at 1050oC for 10 minutes. These samples were then immersed in 1.0M oxalic acid and their weight losses were measured at every five days for 30 days. The results show that corrosion of both types of ASS samples increased with an increase in tempering temperature and time and this was due to the precipitation of chromium carbides at the grain boundaries of these metals. Electrochemical results also confirm that the 304 ASS is more susceptible to corrosion than 316 ASS in this medium. This is attributed to the molybdenum in the composition of the latter. The metallographic images of these samples showed non–uniform distribution of precipitated chromium carbides at the grain boundaries of these metals and unevenly distributed carbides and retained austenite phases which cause galvanic effects in the medium.
Abstract: Polarization modulation infrared reflection absorption
spectroscopy (PM-IRRAS) in combination with electrochemistry,
was employed to study the influence of surface charge (potential) on
the kinetics of bovine serum albumin (BSA) adsorption on a
biomedical-grade 316LVM stainless steel surface is discussed. The
BSA adsorption kinetics was found to greatly depend on the surface
potential. With an increase in surface potential towards more
negative values, both the BSA initial adsorption rate and the
equilibrium (saturated) surface concentration also increased. Both
effects were explained on the basis of replacement of well-ordered
water molecules at the 316LVM / solution interface, i.e. by the
increase in entropy of the system.
Abstract: To date, theoretical studies concerning the Carbon
Fiber Reinforced Polymer (CFRP) strengthening of RC beams with
openings have been rather limited. In addition, various numerical
analyses presented so far have effectively simulated the behaviour of
solid beam strengthened by FRP material. In this paper, a two
dimensional nonlinear finite element analysis is presented to validate
against the laboratory test results of six RC beams. All beams had the
same rectangular cross-section geometry and were loaded under four
point bending. The crack pattern results of the finite element model
show good agreement with the crack pattern of the experimental
beams. The load midspan deflection curves of the finite element
models exhibited a stiffer result compared to the experimental beams.
The possible reason may be due to the perfect bond assumption used
between the concrete and steel reinforcement.
Abstract: Martensitic stainless steels have been extensively used for their good corrosion resistance and better mechanical properties. Heat treatment was suggested as one of the most excellent ways to this regard; hence, it affects the microstructure, mechanical and corrosion properties of the steel. In the current research work the microstructural changes and corrosion behavior in an AISI 420A stainless steel exposed to temperatures in the 980-1035oC range were investigated. The heat treatment is carried out in vacuum furnace within the said temperature range. The quenching of the samples was carried out in oil, brine and water media. The formation and stability of passive film was studied by Open Circuit Potential, Potentiodynamic polarization and Electrochemical Scratch Tests. The Electrochemical Impedance Spectroscopy results simulated with Equivalent Electrical Circuit suggested bilayer structure of outer porous and inner barrier oxide films. The quantitative data showed thick inner barrier oxide film retarded electrochemical reactions. Micrographs of the quenched samples showed sigma and chromium carbide phases which prove the corrosion resistance of steel alloy.
Abstract: In this paper, creep constitutive equations of base
(Parent) and weld materials of the weldment for cold-drawn 304L
stainless steel have been obtained experimentally. For this purpose,
test samples have been generated from cold drawn bars and weld
material according to the ASTM standard. The creep behavior and
properties have been examined for these materials by conducting uniaxial
creep tests. Constant temperatures and constant load uni-axial
creep tests have been carried out at two high temperatures, 680 and
720 oC, subjected to constant loads, which produce initial stresses
ranging from 240 to 360 MPa. The experimental data have been used
to obtain the creep constitutive parameters using numerical
optimization techniques.
Abstract: Primary barrier of membrane type LNG containment system consist of corrugated 304L stainless steel. This 304L stainless steel is austenitic stainless steel which shows different material behaviors owing to phase transformation during the plastic work. Even though corrugated primary barriers are subjected to significant amounts of pre-strain due to press working, quantitative mechanical behavior on the effect of pre-straining at cryogenic temperatures are not available. In this study, pre-strain level and pre-strain temperature dependent tensile tests are carried to investigate mechanical behaviors. Also, constitutive equations with material parameters are suggested for a verification study.
Abstract: In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively
Abstract: A transient finite element model has been developed
to study the heat transfer and fluid flow during spot Gas Tungsten
Arc Welding (GTAW) on stainless steel. Temperature field, fluid
velocity and electromagnetic fields are computed inside the cathode,
arc-plasma and anode using a unified MHD formulation. The
developed model is then used to study the influence of different
helium-argon gas mixtures on both the energy transferred to the
workpiece and the time evolution of the weld pool dimensions. It is
found that the addition of helium to argon increases the heat flux
density on the weld axis by a factor that can reach 6.5. This induces
an increase in the weld pool depth by a factor of 3. It is also found
that the addition of only 10% of argon to helium decreases
considerably the weld pool depth, which is due to the electrical
conductivity of the mixture that increases significantly when argon is
added to helium.
Abstract: The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.