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: This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.
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 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.
Abstract: This study investigated the influence of Cloisite-15A nanoclay on the physical, performance, and mechanical properties of bitumen binder. Cloisite-15A was blended in the bitumen in variegated percentages from 1% to 9% with increment of 2%. The blended bitumen was characterized using penetration, softening point, and dynamic viscosity using rotational viscometer, and compared with unmodified bitumen equally penetration grade 60/70. The rheological parameters were investigated using Dynamic Shear Rheometer (DSR), and mechanical properties were investigated by using Marshall Stability test. The results indicated an increase in softening point, dynamic viscosity and decrease in binder penetration. Rheological properties of bitumen increase complex modulus, decrease phase angle and improve rutting resistances as well. There was significant improvement in Marshall Stability, rather marginal improvement in flow value. The best improvement in the modified binder was obtained with 5% Cloisite-15A nanoclay.
Abstract: The scheduling based routing scheme is presented in this paper to avoid link failure. The main objective of this system is to introduce a cross-layer protocol framework that integrates routing with priority-based traffic management and distributed transmission scheduling. The reservation scheme is based on ID. The presented scheme guarantees that bandwidth reserved time slot is used by another packet in which end-to-end reservation is achieved. The Bandwidth and Delay Aware Routing Protocol with Scheduling Algorithm is presented to allocate channels efficiently. The experimental results show that the presented schemes performed well in various parameters compared to existing methods.
Abstract: The concept of converting the kinetic energy of quadcopter propellers into electrical energy is considered in this contribution following the feasibility study of the propeller vibrations, theoretical energy conversion, and simulation techniques. Analysis of the propeller vibration performance is presented via graphical representation of calculated and simulated parameters, in order to demonstrate the possibility of recovering the harvested energy from the propeller vibrations of the quadcopter while the quadcopter is in operation. Consideration of using piezoelectric materials in such concept, converting the mechanical energy of the propeller into the electrical energy, is given. Photographic evidence of the propeller in operation is presented and discussed together with experimental results to validate the theoretical concept.
Abstract: In the present work, emulsion liquid membrane (ELM) technique was applied for the extraction of cadmium(II) present in aqueous samples. Aliquat 336 (Chloride tri-N-octylmethylammonium) was used as carrier to extract cadmium(II). The main objective of this work is to investigate the influence of various parameters affected the ELM formation and its stability and testing the performance of the prepared ELM on removal of cadmium by using synthetic solution with different concentrations. Experiments were conducted to optimize pH of the feed solution and it was found that cadmium(II) can be extracted at pH 6.5. The influence of the carrier concentration and treat ratio on the extraction process was investigated. The obtained results showed that the optimal values are respectively 3% (Aliquat 336) and a ratio (feed: emulsion) equal to 1:1.
Abstract: The heat and mass transfer characteristics of
contaminants in groundwater subjected to a biodegradation reaction
is analyzed by taking into account the thermal diffusion (Soret)
effects. This phenomenon is modulated mathematically by a
system of partial differential equations which govern the motion
of fluid (groundwater) and solid (contaminants) particles. The
numerical results are presented graphically for different values of
the parameters entering into the problem on the velocity profiles of
fluid, contaminants, temperature and concentration profile.
Abstract: The commercially available titanium alloy, Ti-6Al-4V, was oxynitrided in the deoxygenated nitrogen gas at high temperatures followed by cooling in oxygen-containing nitrogen in order to analyze the influence of oxynitriding parameters on the phase modification, hardness, and the microstructural evolution of the oxynitrided coating. The surface microhardness of the oxynitrided alloy increased due to the strengthening effect of the formed titanium oxynitrides, TiNxOy. The maximum microhardness was obtained, when TiNxOy had near equiatomic composition of nitrogen and oxygen. It could be attained under the optimum oxygen partial pressure and temperature-time condition.
Abstract: Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.
Abstract: New sensors and technologies – such as microphones,
touchscreens or infrared sensors – are currently making their
appearance in the automotive sector, introducing new kinds of
Human-Machine Interfaces (HMIs). The interactions with such tools
might be cognitively expensive, thus unsuitable for driving tasks.
It could for instance be dangerous to use touchscreens with a
visual feedback while driving, as it distracts the driver’s visual
attention away from the road. Furthermore, new technologies in
car cockpits modify the interactions of the users with the central
system. In particular, touchscreens are preferred to arrays of buttons
for space improvement and design purposes. However, the buttons’
tactile feedback is no more available to the driver, which makes
such interfaces more difficult to manipulate while driving. Gestures
combined with an auditory feedback might therefore constitute an
interesting alternative to interact with the HMI. Indeed, gestures can
be performed without vision, which means that the driver’s visual
attention can be totally dedicated to the driving task. In fact, the
auditory feedback can both inform the driver with respect to the task
performed on the interface and on the performed gesture, which might
constitute a possible solution to the lack of tactile information. As
audition is a relatively unused sense in automotive contexts, gesture
sonification can contribute to reducing the cognitive load thanks
to the proposed multisensory exploitation. Our approach consists
in using a virtual object (VO) to sonify the consequences of the
gesture rather than the gesture itself. This approach is motivated
by an ecological point of view: Gestures do not make sound, but
their consequences do. In this experiment, the aim was to identify
efficient sound strategies, to transmit dynamic information of VOs to
users through sound. The swipe gesture was chosen for this purpose,
as it is commonly used in current and new interfaces. We chose
two VO parameters to sonify, the hand-VO distance and the VO
velocity. Two kinds of sound parameters can be chosen to sonify the
VO behavior: Spectral or temporal parameters. Pitch and brightness
were tested as spectral parameters, and amplitude modulation as a
temporal parameter. Performances showed a positive effect of sound
compared to a no-sound situation, revealing the usefulness of sounds
to accomplish the task.
Abstract: A sequence of different Reservoir Engineering methods and tools in reservoir characterization and field development are presented in this paper. The real data of Jin Gas Field of L-Basin of Pakistan is used. The basic concept behind this work is to enlighten the importance of well test analysis in a broader way (i.e. reservoir characterization and field development) unlike to just determine the permeability and skin parameters. Normally in the case of reservoir characterization we rely on well test analysis to some extent but for field development plan, the well test analysis has become a forgotten tool specifically for locations of new development wells. This paper describes the successful implementation of well test analysis in Jin Gas Field where the main uncertainties are identified during initial stage of field development when location of new development well was marked only on the basis of G&G (Geologic and Geophysical) data. The seismic interpretation could not encounter one of the boundary (fault, sub-seismic fault, heterogeneity) near the main and only producing well of Jin Gas Field whereas the results of the model from the well test analysis played a very crucial rule in order to propose the location of second well of the newly discovered field. The results from different methods of well test analysis of Jin Gas Field are also integrated with and supported by other tools of Reservoir Engineering i.e. Material Balance Method and Volumetric Method. In this way, a comprehensive way out and algorithm is obtained in order to integrate the well test analyses with Geological and Geophysical analyses for reservoir characterization and field development. On the strong basis of this working and algorithm, it was successfully evaluated that the proposed location of new development well was not justified and it must be somewhere else except South direction.
Abstract: This paper studies the design of an adaptive control strategy to tune an active steering system for better drivability and maneuverability. In the first step, adaptive control strategy is applied to estimate the uncertain parameters on-line (e.g. cornering stiffness), then the estimated parameters are fed into the pole placement controller to generate corrective feedback gain to improve the steering system dynamic’s characteristics. The simulations are evaluated for three types of road conditions (dry, wet, and icy), and the performance of the adaptive pole placement control (APPC) are compared with pole placement control (PPC) and a passive system. The results show that the APPC strategy significantly improves the yaw rate and side slip angle of a bicycle plant model.
Abstract: In the present case study we examined the development and testing methods of systems that contain safety-critical elements in different industrial fields. Consequentially, we observed the classical object-oriented development and testing environment, as both medical technology and automobile industry approaches the development of safety critical elements that way. Subsequently, we examined model-based development. We introduce the quality parameters that define development and testing. While taking modern agile methodology (scrum) into consideration, we examined whether and to what extent the methodologies we found fit into this environment.
Abstract: The effects of thermal radiation, Soret and Dufour
parameters on mixed convection and nanofluid flow over a stretching
sheet in the presence of a magnetic field are investigated. The flow is
subject to temperature dependent viscosity and a chemical reaction
parameter. It is assumed that the nanoparticle volume fraction at the
wall may be actively controlled. The physical problem is modelled
using systems of nonlinear differential equations which have been
solved numerically using a spectral relaxation method. In addition
to the discussion on heat and mass transfer processes, the velocity,
nanoparticles volume fraction profiles as well as the skin friction
coefficient are determined for different important physical parameters.
A comparison of current findings with previously published results
for some special cases of the problem shows an excellent agreement.