Search results for: nonlinear vehicle dynamics.

Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

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Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO₂ emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: Axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization.

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Authors: Vasana M. Don, Eldad J. Avital, Fariborz Motallebi

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Supersonic open and closed cavity flows are investigated experimentally and computationally. Free stream Mach number of two is set. Schlieren imaging is used to visualise the flow behaviour showing stark differences between open and closed. Computational Fluid Dynamics (CFD) is used to simulate open cavity of flow with aspect ratio of 4. A rear wall treatment is implemented in order to pursue a simple passive control approach. Good qualitative agreement is achieved between the experimental flow visualisation and the CFD in terms of the expansion-shock waves system. The cavity oscillations are shown to be dominated by the first and third Rossister modes combining to high fluctuations of non-linear nature above the cavity rear edge. A simple rear wall treatment in terms of a hole shows mixed effect on the flow oscillations, RMS contours, and time history density fluctuations are given and analysed.

Keywords: Supersonic, Schlieren, open-cavity, flow simulation, passive control.

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Authors: Srimuruganandam. B, S.M. Shiva Nagendra

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In this paper the influence of heterogeneous traffic on the temporal variation of ambient PM10, PM2.5 and PM1 concentrations at a busy arterial route (Sardar Patel Road) in the Chennai city has been analyzed. The hourly PM concentration, traffic counts and average speed of the vehicles have been monitored at the study site for one week (19th-25th January 2009). Results indicated that the concentrations of coarse (PM10) and fine PM (PM2.5 and PM1) concentrations at SP road are having similar trend during peak and non-peak hours, irrespective of the days. The PM concentrations showed daily two peaks corresponding to morning (8 to 10 am) and evening (7 to 9 pm) peak hour traffic flow. The PM10 concentration is dominated by fine particles (53% of PM2.5 and 45% of PM1). The high PM2.5/PM10 ratio indicates that the majority of PM10 particles originate from re-suspension of road dust. The analysis of traffic flow at the study site showed that 2W, 3W and 4W are having similar diurnal trend as PM concentrations. This confirms that the 2W, 3W and 4W are the main emission source contributing to ambient PM concentration at SP road. The speed measurement at SP road showed that the average speed of 2W, 3W, 4W, LCV and HCV are 38, 40, 38, 40 and 38 km/hr and 43, 41, 42, 40 and 41 km/hr respectively for the weekdays and weekdays.

Keywords: particulate matter, heterogeneous traffic, fineparticles, coarse particles, vehicle speed, weekend and weekday.

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Authors: S. N. Ekbote, G. K. Padam, Manju Arora

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Electron spin resonance (ESR) spectroscopic investigations of (Bi, Pb)2Sr2Ca2Cu3O10-x (Bi-2223) bulk samples were carried out in both the normal and superconducting states. A broad asymmetric resonance signal with side signals is obtained in the normal state, and all of them disappear in the superconducting state. The temperature and angular orientation effects on these signals suggest that the broad asymmetric signal arises from electron spin resonance of conduction electrons (CESR) and the side signals from exchange interactions as Platzman-Wolff type spin waves. The disappearance of CESR and spin waves in a superconducting state demonstrates the role of exchange interactions in Cooper pair formation.

Keywords: Bi-2223 superconductor, electron spin resonance of conduction electrons, electron spin resonance, Exchange interactions, spin waves.

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Authors: Laima Silina, Ilze Gramatina, Lija Dukalska, Liga Skudra, Tatjana Rakcejeva, Dace Klava, Anita Blija

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The objective of the present study was to determine quality parameters changes of red wine marinade marinated venison during storage. Beef as a control was analysed. Protein, fat, moisture and pH content dynamics as well microbiological quality was analyzed. The meat pieces were marinated in red wine marinade at 4±2ºC temperature for 48±1h. Marinated meat was placed in polypropylene trays, hermetically sealed with high barrier polymer film Multibarrier 60 under modified atmosphere (CO₂ 40%+N₂ 60%) without and with oxygen absorber sachets, as a control packaging in air ambiance packed marinated venison and beef was used. Meat samples were analyzed after 0, 4, 7, 11 and 14 days of storage. During the storage of meat, protein and moisture content significantly (p<0.05) decreased, pH and colony forming units significantly (p<0.05) increased, fat content does not change in all treatments irrespective of the packaging method.

Keywords: Marinating, modified atmosphere, quality, venison.

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.

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Authors: Mohamed Omar

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Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Keywords: Finite element analysis, seismic response, shapesmemory alloy, steel frame, superelasticity

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Authors: Sean Paulsen, Michael Casey

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In this work, we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: Transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training.

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: Aerial robots, Motion primitives, Robotics.

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Authors: Karam Y. Maalawi, Hanan E.M EL-Sayed

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This paper presents an exact analytical model for optimizing stability of thin-walled, composite, functionally graded pipes conveying fluid. The critical flow velocity at which divergence occurs is maximized for a specified total structural mass in order to ensure the economic feasibility of the attained optimum designs. The composition of the material of construction is optimized by defining the spatial distribution of volume fractions of the material constituents using piecewise variations along the pipe length. The major aim is to tailor the material distribution in the axial direction so as to avoid the occurrence of divergence instability without the penalty of increasing structural mass. Three types of boundary conditions have been examined; namely, Hinged-Hinged, Clamped- Hinged and Clamped-Clamped pipelines. The resulting optimization problem has been formulated as a nonlinear mathematical programming problem solved by invoking the MatLab optimization toolbox routines, which implement constrained function minimization routine named “fmincon" interacting with the associated eigenvalue problem routines. In fact, the proposed mathematical models have succeeded in maximizing the critical flow velocity without mass penalty and producing efficient and economic designs having enhanced stability characteristics as compared with the baseline designs.

Keywords: Functionally graded materials, pipe flow, optimumdesign, fluid- structure interaction

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Authors: T. Shyam Ramanath, A. Sudharsan, A. Kavitha

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As is needless to say; a majority of accidents, which occur, are due to drunk driving. As such, there is no effective mechanism to prevent this. Here we have designed an integrated system for the same purpose. Alcohol content in the driver-s body is detected by means of an infrared breath analyzer placed at the steering wheel. An infrared cell directs infrared energy through the sample and any unabsorbed energy at the other side is detected. The higher the concentration of ethanol, the more infrared absorption occurs (in much the same way that a sunglass lens absorbs visible light, alcohol absorbs infrared light). Thus the alcohol level of the driver is continuously monitored and calibrated on a scale. When it exceeds a particular limit the fuel supply is cutoff. If the device is removed also, the fuel supply will be automatically cut off or an alarm is sounded depending upon the requirement. This does not happen abruptly and special indicators are fixed at the back to avoid inconvenience to other drivers using the highway signals. Frame work for integration of sensors and control module in a scalable multi-agent system is provided .A SMS which contains the current GPS location of the vehicle is sent via a GSM module to the police control room to alert the police. The system is foolproof and the driver cannot tamper with it easily. Thus it provides an effective and cost effective solution for the problem of drunk driving in vehicles.

Keywords: Global system monitoring, global positioning system.

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Authors: Ashish Saini, A.K. Saxena

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The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.

Keywords: Contingent operation state, Fuzzy rule base, Genetic Algorithms, Optimal Power Flow.

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Authors: Ali Aqa Mohammad Jawad

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Taking a relational approach, this paper analyzes the causal mechanisms associated with successful mobilization and rapid demobilization of the Enlightening Movement in post-2001 Afghanistan. The movement emerged after the state-owned Da Afghan Bereshna Sherkat (DABS) decided to divert the route for the Turkmenistan-Uzbekistan-Tajikistan-Afghanistan-Pakistan (TUTAP) electricity project. The grid was initially planned to go through the Hazara-inhabited province of Bamiyan, according to Afghanistan’s Power Sector Master Plan. The reroute served as an aide-mémoire of historical subordination to other ethno-religious groups for the Hazara community. It was also perceived as deprivation from post-2001 development projects, financed by international aid. This torched the accumulated grievances, which then gave birth to the Enlightening Movement. The movement had a successful mobilization. However, it demobilized after losing much of its mobilizing capabilities through an amalgamation of external and internal relational factors. The successful mobilization yet rapid demobilization constitutes the puzzle of this paper. From the theoretical perspective, this paper is significant as it establishes the applicability of contentious politics theory to protest mobilizations that occurred in Afghanistan, a context-specific, characterized by ethnic politics. Both primary and secondary data are utilized to address the puzzle. As for the primary resources, media coverage, interviews, reports, public media statements of the movement, involved in contentious performances, and data from Social Networking Services (SNS) are used. The covered period is from 2001-2018. As for the secondary resources, published academic articles and books are used to give a historical account of contentious politics. For data analysis, a qualitative comparative historical method is utilized to uncover the causal mechanisms associated with successful mobilization and rapid demobilization of the Movement. In this pursuit, both mobilization and demobilization are considered as larger political processes that could be decomposed to constituent mechanisms. Enlightening Movement’s framing and campaigns are first studied to uncover the associated mechanisms. Then, to avoid introducing some ad hoc mechanisms, the recurrence of mechanisms is checked against another case. Mechanisms qualify as robust if they are “recurrent” in different episodes of contention. Checking the recurrence of causal mechanisms is vital as past contentious events tend to reinforce future events. The findings of this paper suggest that the public sphere in Afghanistan is drastically different from Western democracies known as the birthplace of social movements. In Western democracies, when institutional politics did not respond, movement organizers occupied the public sphere, undermining the legitimacy of the government. In Afghanistan, the public sphere is ethicized. Considering the inter- and intra-relational dynamics of ethnic groups in Afghanistan, the movement reduced to an erosive inter- and intra-ethnic conflict. This undermined the cohesiveness of the movement, which then kicked-off its demobilization process.

Keywords: Enlightening movement, contentious politics, mobilization, demobilization.

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Authors: Shigeyuki Haruyama, Aidil Khaidir Bin Muhamad, Tadayuki Kyoutani, Dai-Heng Chen, Ken Kaminishi

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The product development process has undergone many changes concomitant with world progress in order to produce products that meet customer needs quickly and inexpensively. Analysis-Led Design (ALD) is one of the latest methods in the product development process. It focuses more on up-front engineering, a product quality optimization process that starts early in the conceptual design stage. Product development and manufacturing through ALD utilizes digital tools extensively for design, analysis and product optimization. This study uses computer-aided design (CAD) and finite element method (FEM) simulation to examine the modes of deformation of tubular members under axial loading. A multiple-combination impact absorption tubular member, referred to as a compress–expand member, is proposed as a substitute for the conventional thin-walled cylindrical tube to be used as a vehicle’s crash box. The study of deformation modes is crucial for evaluating the geometrical dimension limits by which a member can absorb energy efficiently.

Keywords: Analysis-led design, axial collapse, tubular member, finite element method, thin-walled cylindrical tube, compress-expand member, deformation modes.

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Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

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Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: Autonomous cars, bottleneck model, activity utility, user equilibrium.

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Authors: H. Mansor, S. B. Mohd Noor

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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.

Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.

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Authors: Mansoor Ahsan, Khalid Rafique, Farrukh Mazhar

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Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.

Keywords: Unmanned aerial vehicle (UAV), autopilot, autonomous controls, PID controler gains tuning, optimization.

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: Analytic Network Process, BOCR, location selection, multi-actor decision making, multi-criteria decision making, real life problem.

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Authors: J. Dumrongsak, A. M. Savill

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Non-premixed turbulent combustion Computational Fluid Dynamics (CFD) has been carried out in a simplified methanefuelled coaxial jet combustor employing Large Eddy Simulation (LES). The objective of this study is to evaluate the performance of LES in modelling non-premixed combustion using a commercial software, FLUENT, and investigate the effects of the grid density and chemistry models employed on the accuracy of the simulation results. A comparison has also been made between LES and Reynolds Averaged Navier-Stokes (RANS) predictions. For LES grid sensitivity test, 2.3 and 6.2 million cell grids are employed with the equilibrium model. The chemistry model sensitivity analysis is achieved by comparing the simulation results from the equilibrium chemistry and steady flamelet models. The predictions of the mixture fraction, axial velocity, species mass fraction and temperature by LES are in good agreement with the experimental data. The LES results are similar for the two chemistry models but influenced considerably by the grid resolution in the inner flame and near-wall regions.

Keywords: Coaxial jet, reacting LES, non-premixed combustion, turbulent flow.

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: Entropy, mathematical, prediction, cardiac, holter, attractor.

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Authors: Hyung T. Kwak, Jun Gao, Yao An, Alfred Kleinhammes, Yue Wu

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Surface wettability is a crucial factor in oil recovery. In oil industry, the rock wettability involves the interplay between water, oil, and solid surface. Therefore, studying the interplay between adsorptions of water and hydrocarbon molecules on solid surface would be very informative for understanding rock wettability. Here we use the in-situ Nuclear Magnetic Resonance (NMR) gas isotherm technique to study competitive adsorptions of water and isopropanol, an intermediate step from hydrocarbons. This in-situ NMR technique obtains information on thermodynamic properties such as the isotherm, molecular dynamics via spin relaxation measurements, and adsorption kinetics such as how fast the system can reach thermal equilibrium after changes of vapor pressures. Using surfaces of silica glass beads, which can be modified from hydrophilic to hydrophobic, we obtained information on the influence of surface hydrophilicity on the state of surface water via obtained thermodynamic and dynamic properties.

Keywords: Competitive adsorption, nuclear magnetic resonance, wettability.

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Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

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In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

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The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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Authors: N. Dumitru, S. Dumitru, C. Copilusi, N. Ploscaru

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On this research, experimental analyses have been performed in order to determine the oil pump mechanism dynamics and stability from an oil unit mechanical structure. The experimental tests were focused on the vibrations which occur inside of the rod element during functionality of the oil pump unit. The oil pump mechanism dynamic parameters were measured and also determined through numerical computations. Entire research is based on the oil pump unit mechanical system virtual prototyping. For a complete analysis of the mechanism, the frequency dynamic response was identified, mainly for the mechanism driven element, based on two methods: processing and virtual simulations with MSC Adams aid and experimental analysis. In fact, through this research, a complete methodology is presented where numerical simulations of a mechanism with deformed elements are developed on a dynamic mode and these can be correlated with experimental tests.

Keywords: Modal dynamic analysis, oil pump, vibrations, flexible elements, frequency response.

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Authors: Md. Khademul Islam Molla, Akimasa Sumi, M. Sayedur Rahman

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The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Keywords: Empirical mode decomposition, instantaneous frequency, Hilbert spectrum, Chi-square distribution, anthropogenic impact.

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Authors: G. Santamato, M. Solazzi, A. Frisoli

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Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: Pantograph models, phase-plots, structural health monitoring, vibration-based condition monitoring.

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Authors: Seong-Su Jeon, Seong-Jin Kim, Goon-Cherl Park

Abstract:

In this study, direct numerical simulation for the bubble condensation in the subcooled boiling flow was performed. The main goal was to develop the CFD modeling for the bubble condensation and to evaluate the accuracy of the VOF model with the developed CFD modeling. CFD modeling for the bubble condensation was developed by modeling the source terms in the governing equations of VOF model using UDF. In the modeling, the amount of condensation was determined using the interfacial heat transfer coefficient obtained from the bubble velocity, liquid temperature and bubble diameter every time step. To evaluate the VOF model using the CFD modeling for the bubble condensation, CFD simulation results were compared with SNU experimental results such as bubble volume and shape, interfacial area, bubble diameter and bubble velocity. Simulation results predicted well the behavior of the actual condensing bubble. Therefore, it can be concluded that the VOF model using the CFD modeling for the bubble condensation will be a useful computational fluid dynamics tool for analyzing the behavior of the condensing bubble in a wide range of the subcooled boiling flow.

Keywords: Bubble condensation, CFD modeling, Subcooled boiling flow, VOF model.

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Authors: Eugene Grichuk, Margarita Kuzmina, Eduard Manykin

Abstract:

A network of coupled stochastic oscillators is proposed for modeling of a cluster of entangled qubits that is exploited as a computation resource in one-way quantum computation schemes. A qubit model has been designed as a stochastic oscillator formed by a pair of coupled limit cycle oscillators with chaotically modulated limit cycle radii and frequencies. The qubit simulates the behavior of electric field of polarized light beam and adequately imitates the states of two-level quantum system. A cluster of entangled qubits can be associated with a beam of polarized light, light polarization degree being directly related to cluster entanglement degree. Oscillatory network, imitating qubit cluster, is designed, and system of equations for network dynamics has been written. The constructions of one-qubit gates are suggested. Changing of cluster entanglement degree caused by measurements can be exactly calculated.

Keywords: network of stochastic oscillators, one-way quantumcomputations, a beam of polarized light.

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Authors: W. P. Hu, J. V. Kumar, Jeffrey J. P. Tsai

Abstract:

The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.

Keywords: Nonpeptide inhibitor, Src SH2 domain, LibDock, molecular dynamics simulation.

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Authors: Ajoy Kumar Das, Prasenjit Dey

Abstract:

Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nanoparticles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: Forced convection, Square cylinder, nanofluid, neural network.

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