Search results for: nonlinear tuned vibration absorber

Authors: Jeet Shende, Leonid Shpanin, Misko Abramiuk, Mattew Goodwin, Nicholas Pickett

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Energy harvesting on board the Unmanned Ariel Vehicle (UAV) is one of the most rapidly growing emerging technologies and consists of the collection of small amounts of energy, for different applications, from unconventional sources that are incidental to the operation of the parent system or device. Different energy harvesting techniques have already been investigated in the multirotor drones, where the energy collected comes from the systems surrounding ambient environment and typically involves the conversion of solar, kinetic, or thermal energies into electrical energy. The energy harvesting from the vibrated propeller using the piezoelectric components inside the propeller has also been proven to be feasible. However, the impact on the UAV flight performance using this technology has not been investigated. In this contribution the impact on the multirotor drone operation has been investigated at different flight control configurations which support the efficient performance of the propeller vibration energy harvesting. The industrially made MANTIS X8-PRO octocopter frame kit was used to explore the octocopter operation which was modelled using SolidWorks 3D CAD package for simulation studies. The octocopter flight control strategy is developed through integration of the SolidWorks 3D CAD software and MATLAB/Simulink simulation environment for evaluation of the octocopter behaviour under different simulated flight modes and octocopter geometries. Analysis of the two modelled octocopter geometries and their flight performance is presented via graphical representation of simulated parameters. The possibility of not using the landing gear in octocopter geometry is demonstrated. The conducted study evaluates the octocopter’s flight control technique and its impact on the energy harvesting mechanism developed on board the octocopter. Finite Element Analysis (FEA) simulation results of the modelled octocopter in operation are presented exploring the performance of the octocopter flight control and structural configurations. Applications of both octocopter structures and their flight control strategy are discussed.

Keywords: energy harvesting, flight control modelling, object modeling, unmanned aerial vehicle

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Authors: Ruichong Zhang, Fadi Sawaged, Lotfi Gargab

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This paper introduces a wave-based approach for system identification of high-rise building structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response functions (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings, and GIRF is then found with the inverse Fourier transformation of GFRF. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found in terms of wave transmission and reflection coefficients, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002. The building is modelled as piecewise continuous layers, with which GFRF is derived as function of such building parameters as impedance, cross-sectional area, and damping. GIRF can then be found in closed form for some special cases and numerically in general. Not only does this study reveal the influential factors of building parameters in wave features of GIRF and GRFR, it also shows some system-identification results, which are consistent with other vibration- and wave-based results. Finally, this paper discusses the effectiveness of the proposed model in system identification.

Keywords: wave-based approach, seismic responses of buildings, wave propagation in structures, construction

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Authors: Susanta Kumar Gachhayat, S. K. Dash

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Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

Keywords: economic load dispatch, ELD, biogeography-based optimization, BBO, ramp rate biogeography-based optimization, RRBBO, valve-point loading, VPL

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Authors: M. A. Anwar, K. Iqbal, M. Razzaq

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Background and Objectives: This numerical study reflects the magnetic field's effect on the reduction of plaque formation due to stenosis in a stenosed bifurcated artery. The entire arterythe wall is assumed as linearly elastic, and blood flow is modeled as a Newtonian, viscous, steady, incompressible, laminar, biomagnetic fluid. Methods: An Arbitrary Lagrangian-Eulerian (ALE) technique is employed to formulate the hemodynamic flow in a bifurcated artery under the effect of the asymmetric magnetic field by two-way Fluid-structure interaction coupling. A stable P2P1 finite element pair is used to discretize thenonlinear system of partial differential equations. The resulting nonlinear system of algebraic equations is solved by the Newton Raphson method. Results: The numerical results for displacement, velocity magnitude, pressure, and wall shear stresses for Reynolds numbers, Re = 500, 1000, 1500, 2000, in the presence of magnetic fields are presented graphically. Conclusions: The numerical results show that the presence of the magnetic field influences the displacement and flows velocity magnitude considerably. The magnetic field reduces the flow separation, recirculation area adjacent to stenosis and gives rise to wall shear stress.

Keywords: bifurcation, elastic walls, finite element, wall shear stress,

Procedia PDF Downloads 168

Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

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The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

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Authors: Abderrahmane Kechich, Othmane Abdelkhalek

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Static converters behave as nonlinear loads that inject harmonic currents into the grid and increase the consumption of the inactive power. On the other hand, the increased use of sensitive equipment requires the application of sinusoidal voltages. As a result, the electrical power quality control has become a major concern in the field of power electronics. In this context, the active power conditioner (UPQC) was developed. It combines both serial and parallel structures; the series filter can protect sensitive loads and compensate for voltage disturbances such as voltage harmonics, voltage dips or flicker when the shunt filter compensates for current disturbances such as current harmonics, reactive currents and imbalance. This double feature is that it is one of the most appropriate devices. Calculating parameters is an important step and in the same time it’s not easy for that reason several researchers based on trial and error method for calculating parameters but this method is not easy for beginners researchers especially what about the controller’s parameters, for that reason this paper gives a mathematical way to calculate of almost all of UPQC parameters away from trial and error method. This paper gives also a new approach for calculating of PI regulators parameters for purpose to have a stable UPQC able to compensate for disturbances acting on the waveform of line voltage and load current in order to improve the electrical power quality.

Keywords: UPQC, Shunt active filer, series active filer, PI controller, PWM control, dual-loop control

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Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert

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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.

Keywords: damping, energy-based seismic design, hysteretic energy, input energy

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Authors: Supriya Patibanda, Xiaopeng Gong, Krishna N. Jonnalagadda, Ralph Abrahams

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Yttria stabilized zirconia (YSZ) is used as a top coat in thermal barrier coatings in high-temperature turbine/jet engine applications. The mechanical behaviour of YSZ depends on the microstructural features like crack density and porosity, which are a result of coating method. However, experimentally ascertaining their individual effect is difficult due to the inherent challenges involved like material synthesis and handling. The current work deals with the development of a phenomenological model to replicate the tensile behavior of air plasma sprayed YSZ obtained from experiments. Initially, uniaxial tensile experiments were performed on freestanding YSZ coatings of ~300 µm thick for different crack densities and porosities. The coatings exhibited a nonlinear behavior and also a huge variation in strength values. With the obtained experimental tensile curve as a base and crack density and porosity as prime variables, a phenomenological model was developed using ABAQUS interface with new user material defined employing VUMAT sub routine. The relation between the tensile stress and the crack density was empirically established. Further, a parametric study was carried out to investigate the effect of the individual features on the non-linearity in these coatings. This work enables to generate new coating designs by varying the key parameters and predicting the mechanical properties with the help of a simulation, thereby minimizing experiments.

Keywords: crack density, finite element method, plasma sprayed coatings, VUMAT

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Authors: Indunil Jayatilake, Warna Karunasena

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Fiber Reinforced Polymer (FRP) composites enjoy an array of applications ranging from aerospace, marine and military to automobile, recreational and civil industry due to their outstanding properties. A structural glass fiber reinforced polymer (GFRP) composite sandwich panel made from E-glass fiber skin and a modified phenolic core has been manufactured in Australia for civil engineering applications. One of the major mechanisms of damage in FRP composites is skin-core debonding. The presence of debonding is of great concern not only because it severely affects the strength but also it modifies the dynamic characteristics of the structure, including natural frequency and vibration modes. This paper deals with the investigation of the dynamic characteristics of a GFRP beam with single and multiple debonding by finite element based numerical simulations and analyses using the STRAND7 finite element (FE) software package. Three-dimensional computer models have been developed and numerical simulations were done to assess the dynamic behavior. The FE model developed has been validated with published experimental, analytical and numerical results for fully bonded as well as debonded beams. A comparative analysis is carried out based on a comprehensive parametric investigation. It is observed that the reduction in natural frequency is more affected by single debonding than the equally sized multiple debonding regions located symmetrically to the single debonding position. Thus it is revealed that a large single debonding area leads to more damage in terms of natural frequency reduction than isolated small debonding zones of equivalent area, appearing in the GFRP beam. Furthermore, the extents of natural frequency shifts seem mode-dependent and do not seem to have a monotonous trend of increasing with the mode numbers.

Keywords: debonding, dynamic response, finite element modelling, novel FRP beams

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Authors: Alok Madan, Arshad K. Hashmi

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Performance based design (PBD) is an iterative exercise in which a preliminary trial design of the building structure is selected and if the selected trial design of the building structure does not conform to the desired performance objective, the trial design is revised. In this context, development of a fundamental approach for performance based seismic design of masonry infilled frames with minimum number of trials is an important objective. The paper presents a plastic design procedure based on the energy balance concept for PBD of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames subjected to near-field earthquakes. The proposed energy based plastic design procedure was implemented for trial performance based seismic design of representative masonry infilled reinforced concrete frames with various practically relevant distributions of masonry infill panels over the frame elevation. Non-linear dynamic analyses of the trial PBD of masonry infilled R/C frames was performed under the action of near-field earthquake ground motions. The results of non-linear dynamic analyses demonstrate that the proposed energy method is effective for performance based design of masonry infilled R/C frames under near-field as well as far-field earthquakes.

Keywords: masonry infilled frame, energy methods, near-fault ground motions, pushover analysis, nonlinear dynamic analysis, seismic demand

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Authors: Chrysanthos Maraveas, Argiris Plesias, Garyfalia G. Triantafyllou, Konstantinos Petronikolos

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The current paper presents a structural assessment and proposals for retrofit of the National Youth Foundation Building, an existing reinforced concrete (RC) building in the city of Igoumenitsa, Greece. The building is scheduled to be renovated in order to create a Municipal Cultural Center. The bearing capacity and structural integrity have been investigated in relation to the provisions and requirements of the Greek Retrofitting Code (KAN.EPE.) and European Standards (Eurocodes). The capacity of the existing concrete structure that makes up the two central buildings in the complex (buildings II and IV) has been evaluated both in its present form and after including several proposed architectural interventions. The structural system consists of spatial frames of columns and beams that have been simulated using beam elements. Some RC elements of the buildings have been strengthened in the past by means of concrete jacketing and have had cracks sealed with epoxy injections. Static-nonlinear analysis (Pushover) has been used to assess the seismic performance of the two structures with regard to performance level B1 from KAN.EPE. Retrofitting scenarios are proposed for the two buildings, including type Λ steel bracings and placement of concrete shear walls in the transverse direction in order to achieve the design-specification deformation in each applicable situation, improve the seismic performance, and reduce the number of interventions required.

Keywords: earthquake resistance, pushover analysis, reinforced concrete, retrofit, strengthening

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Authors: Arum Kingsley Chinedu, Ugwuowo Fidelis Ifeanyi, Oranye Henrietta Ebele

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The Poisson regression model (PRM) is a nonlinear model that belongs to the exponential family of distribution. PRM is suitable for studying count variables using appropriate covariates and sometimes experiences the problem of multicollinearity in the explanatory variables and outliers on the response variable. This study aims to address the problem of multicollinearity and outliers jointly in a Poisson regression model. We developed an estimator called the robust modified jackknife PCKL parameter estimator by combining the principal component estimator, modified jackknife KL and transformed M-estimator estimator to address both problems in a PRM. The superiority conditions for this estimator were established, and the properties of the estimator were also derived. The estimator inherits the characteristics of the combined estimators, thereby making it efficient in addressing both problems. And will also be of immediate interest to the research community and advance this study in terms of novelty compared to other studies undertaken in this area. The performance of the estimator (robust modified jackknife PCKL) with other existing estimators was compared using mean squared error (MSE) as a performance evaluation criterion through a Monte Carlo simulation study and the use of real-life data. The results of the analytical study show that the estimator outperformed other existing estimators compared with by having the smallest MSE across all sample sizes, different levels of correlation, percentages of outliers and different numbers of explanatory variables.

Keywords: jackknife modified KL, outliers, multicollinearity, principal component, transformed M-estimator.

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Authors: T. A. Sakr, Hanaa E. Abd-El-Mottaleb

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Outrigger-braced wall systems are commonly used to provide high rise buildings with the required lateral stiffness for wind and earthquake resistance. The existence of outriggers adds to the stiffness and strength of walls as reported by several studies. The effects of different parameters on the elasto-plastic dynamic behavior of outrigger-braced wall systems to earthquakes are investigated in this study. Parameters investigated include outrigger stiffness, concrete strength, and reinforcement arrangement as the main design parameters in wall design. In addition to being significant to the wall behavior, such parameters may lead to the change of failure mode and the delay of crack propagation and consequently failure as the wall is excited by earthquakes. Bi-linear stress-strain relation for concrete with limited tensile strength and truss members with bi-linear stress-strain relation for reinforcement were used in the finite element analysis of the problem. The famous earthquake record, El-Centro, 1940 is used in the study. Emphasis was given to the lateral drift, normal stresses and crack pattern as behavior controlling determinants. Results indicated significant effect of the studied parameters such that stiffer outrigger, higher grade concrete and concentrating the reinforcement at wall edges enhance the behavior of the system. Concrete stresses and cracking behavior are sigbificantly enhanced while lesser drift improvements are observed.

Keywords: outrigger, shear wall, earthquake, nonlinear

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Authors: H. R. Vosoughifar, Seyedeh Zeinab. Hosseininejad, Nahid Shabazi, Seyed Mohialdin Hosseininejad

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In recent years, structure designers advocate further application of energy absorption devices for lateral loads damping. The Un-bonded Braced Frame (UBF) system is one of the efficient damping systems, which is made of a smart combination of steel and concrete or mortar. In this system, steel bears the earthquake-induced axial force as compressive or tension forces without loss of strength. Concrete or mortar around the steel core acts as a constraint for brace and prevents brace buckling during seismic axial load. In this study, the optimal bracing system in the high-rise structures has been evaluated considering the seismic stress distribution in the connections. An actual 18-story structure was modeled using the proper Finite Element (FE) software where braced with UBF, Eccentrically Braced Frames (EBF) and Concentrically Braced Frame (CBF) systems. Nonlinear static pushover and time-history analyses are then performed so that the acquired results demonstrate that the UBF system reduces drift values in the high-rise buildings. Further statistical analyses show that there is a significant difference between the drift values of UBF system compared with those resulted from the EBF and CBF systems. Hence, the seismic stress distribution in the connections of the proposed structure which braced with UBF system was investigated.

Keywords: optimal bracing system, high-rise structure, finite element analysis (FEA), seismic stress

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Authors: Meysam Naeimi, Zili Li, Roumen Petrov, Rolf Dollevoet, Jilt Sietsma, Jun Wu

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The substantial similarity of fatigue mechanism in a new test rig for rolling contact fatigue (RCF) has been investigated. A new reduced-scale test rig is designed to perform controlled RCF tests in wheel-rail materials. The fatigue mechanism of the rig is evaluated in this study using a combined finite element-fatigue prediction approach. The influences of loading conditions on fatigue crack initiation have been studied. Furthermore, the effects of some artificial defects (squat-shape) on fatigue lives are examined. To simulate the vehicle-track interaction by means of the test rig, a three-dimensional finite element (FE) model is built up. The nonlinear material behaviour of the rail steel is modelled in the contact interface. The results of FE simulations are combined with the critical plane concept to determine the material points with the greatest possibility of fatigue failure. Based on the stress-strain responses, by employing of previously postulated criteria for fatigue crack initiation (plastic shakedown and ratchetting), fatigue life analysis is carried out. The results are reported for various loading conditions and different defect sizes. Afterward, the cyclic mechanism of the test rig is evaluated from the operational viewpoint. The results of fatigue life predictions are compared with the expected number of cycles of the test rig by its cyclic nature. Finally, the estimative duration of the experiments until fatigue crack initiation is roughly determined.

Keywords: fatigue, test rig, crack initiation, life, rail, squats

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Authors: Mukhtiar Singh, Sumeet Nagar

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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.

Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem

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Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

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Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Leo Laine, Morgan Johansson

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To meet the civilizations future needs for safe living and low environmental footprint, the engineers designing the complex systems of tomorrow will need efficient ways to model and optimize these systems for their intended purpose. For example, a civil defence shelter and its subsystem components needs to withstand, e.g. airblast and ground shock from decided design level explosion which detonates with a certain distance from the structure. In addition, the complex civil defence shelter needs to have functioning air filter systems to protect from toxic gases and provide clean air, clean water, heat, and electricity needs to also be available through shock and vibration safe fixtures and connections. Similar complex building systems can be found in any concentrated living or office area. In this paper, the authors use a multidomain modelling language called Modelica to model a concrete wall as a single degree of freedom (SDOF) system with elastoplastic properties with the implemented option of plastic hardening. The elastoplastic model was developed and implemented in the open source tool OpenModelica. The simulation model was tested on the case with a transient equivalent reflected pressure time history representing an airblast from 100 kg TNT detonating 15 meters from the wall. The concrete wall is approximately regarded as a concrete strip of 1.0 m width. This load represents a realistic threat on any building in a city like area. The OpenModelica model results were compared with an Excel implementation of a SDOF model with an elastic-plastic spring using simple fixed timestep central difference solver. The structural displacement results agreed very well with each other when it comes to plastic displacement magnitude, elastic oscillation displacement, and response times.

Keywords: airblast from explosives, elastoplastic spring model, Modelica modelling language, SDOF, structural response of concrete structure

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

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Authors: Pola Goldberg Oppenheimer, Stephan Hofmann, Sumeet Mahajan

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Owing to its fingerprint molecular specificity and high sensitivity, surface-enhanced Raman scattering (SERS) is an established analytical tool for chemical and biological sensing capable of single-molecule detection. A strong Raman signal can be generated from SERS-active platforms given the analyte is within the enhanced plasmon field generated near a noble-metal nanostructured substrate. The key requirement for generating strong plasmon resonances to provide this electromagnetic enhancement is an appropriate metal surface roughness. Controlling nanoscale features for generating these regions of high electromagnetic enhancement, the so-called SERS ‘hot-spots’, is still a challenge. Significant advances have been made in SERS research, with wide-ranging techniques to generate substrates with tunable size and shape of the nanoscale roughness features. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for miniaturised sensing devices. Carbon nanotubes (CNTs) have been concurrently, a topic of extensive research however, their applications for plasmonics has been only recently beginning to gain interest. CNTs can provide low-cost, large-active-area patternable substrates which, coupled with appropriate functionalization capable to provide advanced SERS-platforms. Herein, advanced methods to generate CNT-based SERS active detection platforms will be discussed. First, a novel electrohydrodynamic (EHD) lithographic technique will be introduced for patterning CNT-polymer composites, providing a straightforward, single-step approach for generating high-fidelity sub-micron-sized nanocomposite structures within which anisotropic CNTs are vertically aligned. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements with each of the EHD-CNTs individual structural units functioning as an isolated sensor. Further, gold-functionalized VACNTFs are fabricated as SERS micro-platforms. The dependence on the VACNTs’ diameters and density play an important role in the Raman signal strength, thus highlighting the importance of structural parameters, previously overlooked in designing and fabricating optimized CNTs-based SERS nanoprobes. VACNTs forests patterned into predesigned pillar structures are further utilized for multiplex detection of bio-analytes. Since CNTs exhibit electrical conductivity and unique adsorption properties, these are further harnessed in the development of novel chemical and bio-sensing platforms.

Keywords: carbon nanotubes (CNTs), EHD patterning, SERS, vertically aligned carbon nanotube forests (VACNTF)

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Authors: Mostafa Aminzadeh, Min Deng

Abstract:

Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

Abstract:

Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Mohammad A. Bani-Khaled

Abstract:

In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Torsten Mielitz, Dietmar Schulz, York C. Roth

Abstract:

Market forecasts show a significant increase in the demand for aircraft within the next two decades and production rates will be adapted accordingly. Improvements and optimizations in the industrial system are becoming more important to cope with future challenges in manufacturing and assembly. Highest quality standards have to be met for aerospace parts, whereas cost effective production in industrial systems and methodologies are also a key driver. A look at other industries like e.g., automotive shows well established processes to streamline existing manufacturing systems. In this paper, the implementation of 'PULL' principles in an existing manufacturing process chain for a large scale composite part is presented. A nonlinear extrapolation based on 'Little's Law' showed a risk of a significant increase of parts needed in the process chain to meet future demand. A project has been set up to mitigate the risk whereas the methodology has been changed from a traditional milestone approach in the beginning towards an agile way of working in the end in order to facilitate immediate benefits in the shop-floor. Finally, delivery rates could be increased avoiding more semi-finished parts in the process chain (work in progress & inventory) by the successful implementation of the 'PULL' philosophy in the shop-floor between the work stations. Lessons learned during the running project as well as implementation and operations phases are discussed in order to share best practices.

Keywords: aerospace composite part manufacturing, PULL principles, shop-floor implementation, lessons learned

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Authors: Pradeepa Teegala, Ramreddy Chetteti

Abstract:

This work emphasizes the effects of heat generation/absorption and Joule heating on chemically reacting micropolar fluid flow over a truncated cone with convective boundary condition. For this complex fluid flow problem, the similarity solution does not exist and hence using non-similarity transformations, the governing fluid flow equations along with related boundary conditions are transformed into a set of non-dimensional partial differential equations. Several authors have applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The influence of pertinent parameters namely Biot number, Joule heating, heat generation/absorption, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, spectral quasilinearization method

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Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

Abstract:

Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

Abstract:

In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Balgaisha Mukanova, Natalya Glazyrina, Sergey Glazyrin

Abstract:

The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.

Keywords: direct problem, multiparametric optimization, optimization parameters, water treatment

Procedia PDF Downloads 383