Abstract: The purpose of the present work was to develop an innovative food product with good textural and sensorial characteristics. The product, a new type of bread, was prepared with wheat (90%) and lupin (10%) flours, without the addition of any conservatives. Several experiences were also done to find the most appropriate proportion of lupin flour. The optimized product was characterized considering the rheological, physical-chemical and sensorial properties. The water absorption of wheat flour with 10% of lupin was higher than that of the normal wheat flours, and Wheat Ceres flour presented the lower value, with lower dough development time and high stability time. The breads presented low moisture but a considerable water activity. The density of bread decreased with the introduction of lupin flour. The breads were quite white, and during storage the colour parameters decreased. The lupin flour clearly increased the number of alveolus, but the total area increased significantly just for the Wheat Cerealis bread. The addition of lupin flour increased the hardness and chewiness of breads, but the elasticity did not vary significantly. Lupin bread was sensorially similar to wheat bread produced with WCerealis flour, and the main differences are the crust rugosity, colour and alveolus characteristics.
Abstract: Wire Electric Discharge Machining (WEDM) is
thermal machining process capable of machining very hard
electrically conductive material irrespective of their hardness.
WEDM is being widely used to machine micro scale parts with the
high dimensional accuracy and surface finish. The objective of this
paper is to optimize the process parameters of wire EDM to fabricate
the micro channels and to calculate the surface finish and material
removal rate of micro channels fabricated using wire EDM. The
material used is aluminum 6061 alloy. The experiments were
performed using CNC wire cut electric discharge machine. The effect
of various parameters of WEDM like pulse on time (TON) with the
levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35,
45) and current (IP) with the levels (105, 110, 115) were investigated
to study the effect on output parameter i.e. Surface Roughness and
Material Removal Rate (MRR). Each experiment was conducted
under different conditions of pulse on time, pulse off time and peak
current. For material removal rate, TON and Ip
were the most significant process parameter. MRR increases with the increase in
TON and Ip and decreases with the increase in TOFF. For surface
roughness, TON and Ip have the maximum effect and TOFF was found
out to be less effective.
Abstract: Carefully scheduling the operations of pumps can be
resulted to significant energy savings. Schedules can be defined
either implicit, in terms of other elements of the network such as tank
levels, or explicit by specifying the time during which each pump is
on/off. In this study, two new explicit representations based on timecontrolled
triggers were analyzed, where the maximum number of
pump switches was established beforehand, and the schedule may
contain fewer switches than the maximum. The optimal operation of
pumping stations was determined using a Jumping Particle Swarm
Optimization (JPSO) algorithm to achieve the minimum energy cost.
The model integrates JPSO optimizer and EPANET hydraulic
network solver. The optimal pump operation schedule of VanZyl
water distribution system was determined using the proposed model
and compared with those from Genetic and Ant Colony algorithms.
The results indicate that the proposed model utilizing the JPSO
algorithm is a versatile management model for the operation of realworld
water distribution system.
Abstract: The moisture content of densified biomass is a
limiting parameter influencing the quality of this solid biofuel. It
influences its calorific value, density, mechanical strength and
dimensional stability as well as affecting its production process. This
paper deals with experimental research into the effect of moisture
content of the densified material on the final quality of biofuel in the
form of logs (briquettes or pellets). Experiments based on the singleaxis
densification of the spruce sawdust were carried out with a
hydraulic piston press (piston and die), where the densified logs were
produced at room temperature. The effect of moisture content on the
qualitative properties of the logs, including density, change of
moisture, expansion and physical changes, and compressive and
impact resistance were studied. The results show the moisture ranges
required for producing good-quality logs. The experiments were
evaluated and the moisture content of the tested material was
optimized to achieve the optimum value for the best quality of the
solid biofuel. The dense logs also have high-energy content per unit
volume. The research results could be used to develop and optimize
industrial technologies and machinery for biomass densification to
achieve high quality solid biofuel.
Abstract: This paper will discuss how we optimize our physical
verification flow in our IC Design Department having various rule
decks from multiple foundries. Our ultimate goal is to achieve faster
time to tape-out and avoid schedule delay. Currently the physical
verification runtimes and memory usage have drastically increased
with the increasing number of design rules, design complexity, and
the size of the chips to be verified. To manage design violations, we
use a number of solutions to reduce the amount of violations needed
to be checked by physical verification engineers. The most important
functions in physical verifications are DRC (design rule check), LVS
(layout vs. schematic), and XRC (extraction). Since we have a
multiple number of foundries for our design tape-outs, we need a
flow that improve the overall turnaround time and ease of use of the
physical verification process. The demand for fast turnaround time is
even more critical since the physical design is the last stage before
sending the layout to the foundries.
Abstract: The current tools for real time management of sewer
systems are based on two software tools: the software of weather
forecast and the software of hydraulic simulation. The use of the first
ones is an important cause of imprecision and uncertainty, the use of
the second requires temporal important steps of decision because of
their need in times of calculation. This way of proceeding fact that
the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by
approaching the problem by the "automatic" face rather than by that
"hydrology". The objective is to make possible the realization of a
large number of simulations at very short times (a few seconds)
allowing to take place weather forecasts by using directly the real
time meditative pluviometric data. The aim is to reach a system
where the decision-making is realized from reliable data and where
the correction of the error is permanent. A first model of control laws was realized and tested with different
return-period rainfalls. The gains obtained in rejecting volume vary
from 19 to 100 %. The development of a new algorithm was then
used to optimize calculation time and thus to overcome the
subsequent combinatorial problem in our first approach. Finally, this
new algorithm was tested with 16- year-rainfall series. The obtained
gains are 40 % of total volume rejected to the natural environment
and of 65 % in the number of discharges.
Abstract: This paper is aimed to study combustion characteristics
of low NOx burner using petroleum cokes as fuel. The petroleum coke,
which is produced through the oil refining process, is an attractive fuel
in terms of its high heating value and low price. But petroleum coke is
a challenging fuel because of its low volatile content, high sulfur and
nitrogen content, which give rise to undesirable emission
characteristics and low ignitability. Therefore, the research and
development regarding the petroleum coke burner is needed for
applying this industrial system. In this study, combustion and emission
characteristics of petroleum cokes burner are experimentally
investigated in an industrial steam boiler. The low NOx burner is
designed to control fuel and air mixing to achieve staged combustion,
which, in turn reduces both flame temperature and oxygen. Air
distribution ratio of triple staged air is optimized experimentally. The
result showed that NOx concentration is lowest when overfire air is
used, and the burner function at a fuel rich condition. That is, the
burner is operated at the equivalence ratio of 1.67 and overall
equivalence ratio including overfire air is kept 0.87.
Abstract: Water resource systems modeling has constantly been
a challenge through history for human beings. As the innovative
methodological development is evolving alongside computer sciences
on one hand, researches are likely to confront more complex and
larger water resources systems due to new challenges regarding
increased water demands, climate change and human interventions,
socio-economic concerns, and environment protection and
sustainability. In this research, an automatic calibration scheme has
been applied on the Gilan’s large-scale water resource model using
mathematical programming. The water resource model’s calibration
is developed in order to attune unknown water return flows from
demand sites in the complex Sefidroud irrigation network and other
related areas. The calibration procedure is validated by comparing
several gauged river outflows from the system in the past with model
results. The calibration results are pleasantly reasonable presenting a
rational insight of the system. Subsequently, the unknown optimized
parameters were used in a basin-scale linear optimization model with
the ability to evaluate the system’s performance against a reduced
inflow scenario in future. Results showed an acceptable match
between predicted and observed outflows from the system at selected
hydrometric stations. Moreover, an efficient operating policy was
determined for Sefidroud dam leading to a minimum water shortage
in the reduced inflow scenario.
Abstract: The application of cold Radio-Frequency (RF) plasma
in the conservation of cultural heritage became important in the last
decades due to the positive results obtained in decontamination
treatments. This paper presents an equipment especially designed for cold RF
plasma application on paper documents, developed within a research
project. The equipment consists in two modules: the first one is
designed for decontamination and cleaning treatments of any type of
paper supports, while the second one can be used for coating friable
papers with adequate polymers, for protection purposes. All these
operations are carried out in cold radio-frequency plasma, working in
gaseous nitrogen, at low pressure. In order to optimize the equipment parameters ancient paper
samples infested with microorganisms have been treated in nitrogen
plasma and the decontamination effects, as well as changes in surface
properties (color, pH) were assessed. The microbiological analysis
revealed complete decontamination at 6 minutes treatment duration;
only minor modifications of the surface pH were found and the
colorimetric analysis showed a slight yellowing of the support.
Abstract: It is the patient compliance and stability in
combination with controlled drug delivery and biocompatibility that
forms the core feature in present research and development of
sustained biodegradable patch formulation intended for wound
healing. The aim was to impart sustained degradation, sterile
formulation, significant folding endurance, elasticity,
biodegradability, bio-acceptability and strength. The optimized
formulation comprised of polymers including Hydroxypropyl methyl
cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric
acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric
mixture dissolved in geometric order in suitable medium through
continuous stirring under ambient conditions. With continued stirring
Curcumin was added with aid of DCM and Methanol in optimized
ratio to get homogenous dispersion. The dispersion was sonicated
with optimum frequency and for given time and later casted to form a
patch form. All steps were carried out under strict aseptic conditions.
The formulations obtained in the acceptable working range were
decided based on thickness, uniformity of drug content, smooth
texture and flexibility and brittleness. The patch kept on stability
using butter paper in sterile pack displayed folding endurance in
range of 20 to 23 times without any evidence of crack in an
optimized formulation at room temperature (RT) (24 ± 2°C). The
patch displayed acceptable parameters after stability study conducted
in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) up to 90
days. Further, no significant changes were observed in critical
parameters such as elasticity, biodegradability, drug release and drug
content during stability study conducted at RT 24±2°C for 45 and 90
days. The drug content was in range 95 to 102%, moisture content
didn’t exceeded 19.2% and patch passed the content uniformity test.
Percentage cumulative drug release was found to be 80% in 12h and
matched the biodegradation rate as drug release with correlation
factor R2>0.9. The biodegradable patch based formulation developed
shows promising results in terms of stability and release profiles.
Abstract: This paper introduces a method to optimal design of a
hybrid Wind/Photovoltaic/Fuel cell generation system for a typical
domestic load that is not located near the electricity grid. In this
configuration the combination of a battery, an electrolyser, and a
hydrogen storage tank are used as the energy storage system. The aim
of this design is minimization of overall cost of generation scheme
over 20 years of operation. The Matlab/Simulink is applied for
choosing the appropriate structure and the optimization of system
sizing. A teaching learning based optimization is used to optimize the
cost function. An overall power management strategy is designed for
the proposed system to manage power flows among the different
energy sources and the storage unit in the system. The results have
been analyzed in terms of technical and economic. The simulation
results indicate that the proposed hybrid system would be a feasible
solution for stand-alone applications at remote locations.
Abstract: In this paper, a new SMC (Sliding Mode Control)
method with MP (Model Predictive Control) integral action for the
slip suppression of EV (Electric Vehicle) under braking is proposed.
The proposed method introduce the integral term with standard SMC
gain , where the integral gain is optimized for each control period by
the MPC algorithms. The aim of this method is to improve the safety
and the stability of EVs under braking by controlling the wheel slip
ratio. There also include numerical simulation results to demonstrate
the effectiveness of the method.
Abstract: The aim of our study is to project an optimized wind turbine of Darrieus type. This type of wind turbine is characterized by a low starting torque in comparison with the Savonius rotor allowing them to operate for a period greater than wind speed. This led us to reconsider the Darrieus rotor to optimize a design which will increase its starting torque. The study of a system of monitoring and control of the angle of attack of blade profile, which allows an auto start to wind speeds as low as possible is presented for the straight blade of Darrieus turbine. The study continues to extend to other configurations namely those of parabolic type.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: The synthesis of CuFe2O4 spinel powders by an
optimized combustion-like process followed by calcination is
described herein. The samples were characterized using X-ray
diffraction (XRD), differential thermal analysis (TG/DTA), scanning
electron microscopy (SEM), dilatometry and 4-probe DC methods.
Different glycine to nitrate (G/N) ratios of 1 (fuel-deficient), 1.48
(stoichiometric) and 2 (fuel-rich) were employed. Calcining the asprepared
powders at 800 and 1000°C for 5 hours showed that the G/N
ratio of 2 results in the formation of the desired copper spinel single
phase at both calcination temperatures. For G/N=1, formation of
CuFe2O4 takes place in three steps. First, iron and copper nitrates
decompose to iron oxide and pure copper. Then, copper transforms to
copper oxide and finally, copper and iron oxides react with each other
to form a copper ferrite spinel phase. The electrical conductivity and
the coefficient of thermal expansion of the sintered pelletized
samples were 2 S.cm-1 (800°C) and 11×10-6 °C-1 (25-800°C),
respectively.
Abstract: Distillery spentwash contains high chemical oxygen
demand (COD), biological oxygen demand (BOD), color, total
dissolved solids (TDS) and other contaminants even after biological
treatment. The effluent can’t be discharged as such in the surface
water bodies or land without further treatment. Reverse osmosis (RO)
treatment plants have been installed in many of the distilleries at
tertiary level in many of the distilleries in India, but are not properly
working due to fouling problem which is caused by the presence of
high concentration of organic matter and other contaminants in
biologically treated spentwash. In order to make the membrane
treatment a proven and reliable technology, proper pre-treatment is
mandatory. In the present study, ultra-filtration (UF) for pretreatment
of RO at tertiary stage has been performed. Operating
parameters namely initial pH (pHo: 2–10), trans-membrane pressure
(TMP: 4-20 bars) and temperature (T: 15-43°C) were used for
conducting experiments with UF system. Experiments were
optimized at different operating parameters in terms of COD, color,
TDS and TOC removal by using response surface methodology
(RSM) with central composite design. The results showed that
removal of COD, color and TDS was 62%, 93.5% and 75.5%
respectively, with UF, at optimized conditions with increased
permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The
performance of the RO system was greatly improved both in term of
pollutant removal as well as water recovery.
Abstract: Superabsorbent polymers received much attention and
are used in many fields because of their superior characters to
traditional absorbents, e.g., sponge and cotton. So, it is very
important but challenging to prepare highly and fast-swelling
superabsorbents. A reliable, efficient and low-cost technique for
removing heavy metal ions from wastewater is the adsorption using
bio-adsorbents obtained from biological materials, such as
polysaccharides-based hydrogels superabsorbents. In this study, novel multi-functional superabsorbent composites
type semi-interpenetrating polymer networks (Semi-IPNs) were
prepared via graft polymerization of acrylamide onto chitosan
backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium
persulfate and N,N’-methylene bisacrylamide as initiator and
crosslinker, respectively. These hydrogels were also partially
hydrolyzed to achieve superabsorbents with ampholytic properties
and uppermost swelling capacity. The formation of the grafted
network was evidenced by Fourier Transform Infrared Spectroscopy
(ATR-FTIR) and Thermogravimetric Analysis (TGA). The porous
structures were observed by Scanning Electron Microscope (SEM).
From TGA analysis, it was concluded that the incorporation of the Ge
in the CTS-g-PAAm network has marginally affected its thermal
stability. The effect of gelatin content on the swelling capacities of
these superabsorbent composites was examined in various media
(distilled water, saline and pH-solutions). The water absorbency was
enhanced by adding Ge in the network, where the optimum value was
reached at 2 wt. % of Ge. Their hydrolysis has not only greatly
optimized their absorption capacity but also improved the swelling
kinetic.These materials have also showed reswelling ability. We
believe that these super-absorbing materials would be very effective
for the adsorption of harmful metal ions from wastewater.
Abstract: Waste Load Allocation (WLA) strategies usually
intend to find economic policies for water resource management.
Water quality trading (WQT) is an approach that uses discharge
permit market to reduce total environmental protection costs. This
primarily requires assigning discharge limits known as total
maximum daily loads (TMDLs). These are determined by monitoring
organizations with respect to the receiving water quality and
remediation capabilities. The purpose of this study is to compare two
approaches of TMDL assignment for WQT policy in small catchment
area of Haraz River, in north of Iran. At first, TMDLs are assigned
uniformly for the whole point sources to keep the concentrations of
BOD and dissolved oxygen (DO) at the standard level at checkpoint
(terminus point). This was simply simulated and controlled by
Qual2kw software. In the second scenario, TMDLs are assigned
using multi objective particle swarm optimization (MOPSO) method
in which the environmental violation at river basin and total treatment
costs are minimized simultaneously. In both scenarios, the equity
index and the WLA based on trading discharge permits (TDP) are
calculated. The comparative results showed that using economically
optimized TMDLs (2nd scenario) has slightly more cost savings rather
than uniform TMDL approach (1st scenario). The former annually
costs about 1 M$ while the latter is 1.15 M$. WQT can decrease
these annual costs to 0.9 and 1.1 M$, respectively. In other word,
these approaches may save 35 and 45% economically in comparison
with command and control policy. It means that using multi objective
decision support systems (DSS) may find more economical WLA,
however its outcome is not necessarily significant in comparison with
uniform TMDLs. This may be due to the similar impact factors of
dischargers in small catchments. Conversely, using uniform TMDLs
for WQT brings more equity that makes stakeholders not feel that
much envious of difference between TMDL and WQT allocation. In
addition, for this case, determination of TMDLs uniformly would be
much easier for monitoring. Consequently, uniform TMDL for TDP
market is recommended as a sustainable approach. However,
economical TMDLs can be used for larger watersheds.
Abstract: Several parameters are established in order to measure
biodiesel quality. One of them is the iodine value, which is an
important parameter that measures the total unsaturation within a
mixture of fatty acids. Limitation of unsaturated fatty acids is
necessary since warming of higher quantity of these ones ends in
either formation of deposits inside the motor or damage of lubricant.
Determination of iodine value by official procedure tends to be very
laborious, with high costs and toxicity of the reagents, this study uses
artificial neural network (ANN) in order to predict the iodine value
property as an alternative to these problems. The methodology of
development of networks used 13 esters of fatty acids in the input
with convergence algorithms of back propagation of back
propagation type were optimized in order to get an architecture of
prediction of iodine value. This study allowed us to demonstrate the
neural networks’ ability to learn the correlation between biodiesel
quality properties, in this caseiodine value, and the molecular
structures that make it up. The model developed in the study reached
a correlation coefficient (R) of 0.99 for both network validation and
network simulation, with Levenberg-Maquardt algorithm.
Abstract: Model predictive control is a kind of optimal feedback
control in which control performance over a finite future is optimized
with a performance index that has a moving initial time and a moving
terminal time. This paper examines the stability of model predictive
control for linear discrete-time systems with additive stochastic
disturbances. A sufficient condition for the stability of the closed-loop
system with model predictive control is derived by means of a linear
matrix inequality. The objective of this paper is to show the results
of computational simulations in order to verify the effectiveness of
the obtained stability condition.