Search results for: discrete particle modelling

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: R. Sabre, W. Horrigue, J. C. Simon

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This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: spectral density, stable processes, aliasing, periodogram

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Authors: Vesta Kohlmeier, George C. Dragan, Juergen Orasche, Juergen Schnelle-Kreis, Dietmar Breuer, Ralf Zimmermann

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Aerosols from hazardous semi-volatile organic compounds (SVOC) may occur in workplace air and can simultaneously be found as particle and gas phase. For health risk assessment, it is necessary to collect particles and gases separately. This can be achieved by using a denuder for the gas phase collection, combined with a filter and an adsorber for particle collection. The study focused on the suitability of carbonaceous monolithic multi-channel denuders, so-called Novacarb™-Denuders (MastCarbon International Ltd., Guilford, UK), to achieve gas-particle separation. Particle transmission efficiency experiments were performed with polystyrene latex (PSL) particles (size range 0.51-3 µm), while the time dependent gas phase collection efficiency was analysed for polar and nonpolar SVOC (mass concentrations 7-10 mg/m3) over 2 h at 5 or 10 l/min. The experimental gas phase collection efficiency was also compared with theoretical predictions. For n-hexadecane (C16), the gas phase collection efficiency was max. 91 % for one denuder and max. 98 % for two denuders, while for diethylene glycol (DEG), a maximal gas phase collection efficiency of 93 % for one denuder and 97 % for two denuders was observed. At 5 l/min higher gas phase collection efficiencies were achieved than at 10 l/min. The deviations between the theoretical and experimental gas phase collection efficiencies were up to 5 % for C16 and 23 % for DEG. Since the theoretical efficiency depends on the geometric shape and length of the denuder, flow rate and diffusion coefficients of the tested substances, the obtained values define an upper limit which could be reached. Regarding the particle transmission through the denuders, the use of one denuder showed transmission efficiencies around 98 % for 1-3 µm particle diameters. The use of three denuders resulted in transmission efficiencies from 93-97 % for the same particle sizes. In summary, NovaCarb™-Denuders are well applicable for sampling aerosols of polar/nonpolar substances with particle diameters ≤3 µm and flow rates of 5 l/min or lower. These properties and their compact size make them suitable for use in personal aerosol samplers. This work is supported by the German Social Accident Insurance (DGUV), research contract FP371.

Keywords: gas phase collection efficiency, particle transmission, personal aerosol sampler, SVOC

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Authors: Desmond Agbolade Ademola

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This work aimed to introduce a theory, called Guided Energy Theory of a particle that answered questions that arise from quantum foundation, quantum mechanics theory, and interpretation such as: what is nature of wavefunction? Is mathematical formalism of wavefunction correct? Does wavefunction collapse during measurement? Do quantum physical entanglement and many world interpretations really exist? In addition, is there uncertainty in the physical reality of our nature as being concluded in the Quantum theory? We have been able to show by the fundamental analysis presented in this work that the way quantum mechanics theory, and interpretation describes nature is not correlated with physical reality. Because, we discovered amongst others that, (1) Guided energy theory of a particle fundamentally provides complete physical observable series of quantized measurement of a particle momentum, force, energy e.t.c. in a given distance and time.In contrast, quantum mechanics wavefunction describes that nature has inherited probabilistic and indeterministic physical quantities, resulting in unobservable physical quantities that lead to many worldinterpretation.(2) Guided energy theory of a particle fundamentally predicts that it is mathematically possible to determine precise quantized measurementof position and momentum of a particle simultaneously. Because, there is no uncertainty in nature; nature however naturally guides itself against uncertainty. Contrary to the conclusion in quantum mechanics theory that, it is mathematically impossible to determine the position and the momentum of a particle simultaneously. Furthermore, we have been able to show by this theory that, it is mathematically possible to determine quantized measurement of force acting on a particle simultaneously, which is not possible on the premise of quantum mechanics theory. (3) It is evidently shown by our theory that, guided energy does not collapse, only describes the lopsided nature of a particle behavior in motion. This pretty offers us insight on gradual process of engagement - convergence and disengagement – divergence of guided energy holders which further highlight the picture how wave – like behavior return to particle-like behavior and how particle – like behavior return to wave – like behavior respectively. This further proves that the particles’ behavior in motion is oscillatory in nature. The mathematical formalism of Guided energy theory shows that nature is certainty whereas the mathematical formalism of Quantum mechanics theory shows that nature is absolutely probabilistics. In addition, the nature of wavefunction is the guided energy of the wave. In conclusion, the fundamental mathematical formalism of Quantum mechanics theory is wrong.

Keywords: momentum, physical entanglement, wavefunction, uncertainty

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Justice Zakhele Msomi

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Nanoparticles of CdFe2O4 with particle size of about 10 nm have been synthesized by high energy ball milling and co-precipitation processes. The synthesis route appears to have some effects on the properties. The compounds have been characterized by X-ray diffraction, Fourier Transform Infrared (FTIR), transmission electron microscopy (TEM), Mössbauer and magnetization measurements. The XRD pattern of CdFe2O4 provides information about single-phase formation of spinel structure with cubic symmetry. The FTIR measurements between 400 and 4000 cm-1 indicate intrinsic cation vibration of the spinel structure. The Mössbauer spectra were recorded at 4 K and 300 K. The hyperfine fields appear to be highly sensitive on particle size. The evolution of the properties as a function of particle size is also presented.

Keywords: ferrite, nanoparticles, magnetization, Mössbauer

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Authors: Muleya Nqobile, Winston Garira

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We presented a compartmental deterministic multi-scale model which encompass internal plant defensive mechanism and pathogen interaction, then we consider nesting the model into the epidemiological model. The objective was to improve our understanding of the transmission dynamics of within host and between host of Guignardia citricapa Kiely. The inflow of infected class was scaled down to individual level while the outflow was scaled up to average population level. Conceptual model and mathematical model were constructed to display a theoretical framework which can be used for predicting or identify disease pattern.

Keywords: epidemiological model, mathematical modelling, multi-scale modelling, immunological model

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Authors: Praveen Kumar, Nitin Kumar, Hemant Kumar

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The modernization of computer technology and commercial computational fluid dynamic (CFD) simulation has given better detailed results as compared to experimental investigation techniques. CFD techniques are widely used in different field due to its flexibility and performance. Evaluation of pipeline erosion is complex phenomenon to solve by numerical arithmetic technique, whereas CFD simulation is an easy tool to resolve that type of problem. Erosion wear behaviour due to solid–liquid mixture in the slurry pipeline has been investigated using commercial CFD code in FLUENT. Multi-phase Euler-Lagrange model was adopted to predict the solid particle erosion wear in 22.5° pipe bend for the flow of bottom ash-water suspension. The present study addresses erosion prediction in three dimensional 22.5° pipe bend for two-phase (solid and liquid) flow using finite volume method with standard k-ε turbulence, discrete phase model and evaluation of erosion wear rate with varying velocity 2-4 m/s. The result shows that velocity of solid-liquid mixture found to be highly dominating parameter as compared to solid concentration, density, and particle size. At low velocity, settling takes place in the pipe bend due to low inertia and gravitational effect on solid particulate which leads to high erosion at bottom side of pipeline.

Keywords: computational fluid dynamics (CFD), erosion, slurry transportation, k-ε Model

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Authors: Hao-Su Liu, Jun-Qing Lei

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This study introduces the theory of modified particle swarm optimizer and its application in time-domain expressions for bridge self-excited aerodynamic forces. Based on the indicial function expression and the rational function expression in time-domain expression for bridge self-excited aerodynamic forces, the characteristics of the two methods, i.e. the modified particle swarm optimizer and conventional search method, are compared in flutter derivatives’ fitting process. Theoretical analysis and numerical results indicate that adopting whether the indicial function expression or the rational function expression, the fitting flutter derivatives obtained by modified particle swarm optimizer have better goodness of fit with ones obtained from experiment. As to the flutter derivatives which have higher nonlinearity, the self-excited aerodynamic forces, using the flutter derivatives obtained through modified particle swarm optimizer fitting process, are much closer to the ones simulated by the experimental. The modified particle swarm optimizer was used to recognize the parameters of time-domain expressions for flutter derivatives of an actual long-span highway-railway truss bridge with double decks at the wind attack angle of 0°, -3° and +3°. It was found that this method could solve the bounded problems of attenuation coefficient effectively in conventional search method, and had the ability of searching in unboundedly area. Accordingly, this study provides a method for engineering industry to frequently and efficiently obtain the time-domain expressions for bridge self-excited aerodynamic forces.

Keywords: time-domain expressions, bridge self-excited aerodynamic forces, modified particle swarm optimizer, long-span highway-railway truss bridge

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Authors: Baha Hasan, Jan Wikander

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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

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Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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Authors: Roman Marsalek

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In this paper, snow samples containing dust particles from several sampling points around the city of Ostrava were analyzed. The pH values of sampled snow were measured and solid particles analyzed. Particle size, zeta potential and content of selected heavy metals were determined in solid particles. The pH values of most samples lay in the slightly acid region. Mean values of particle size ranged from 290.5 to 620.5 nm. Zeta potential values varied between -5 and -26.5 mV. The following heavy metal concentration ranges were found: copper 0.08-0.75 mg/g, lead 0.05-0.9 mg/g, manganese 0.45-5.9 mg/g and iron 25.7-280.46 mg/g. The highest values of copper and lead were found in the vicinity of busy crossroads, and on the contrary, the highest levels of manganese and iron were detected close to a large steelworks. The proportion between pH values, zeta potentials, particle sizes and heavy metal contents was established. Zeta potential decreased with rising pH values and, simultaneously, heavy metal content in solid particles increased. At the same time, higher metal content corresponded to lower particle size.

Keywords: dust, snow, zeta potential, particles size distribution, heavy metals

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Authors: A. Terfous, Y. Liu, A. Ghenaim, P. A. Garambois

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With increasing urbanization worldwide, it is crucial to sustainably manage sediment flows in urban networks and especially in stormwater detention basins. One key aspect is to propose optimized designs for detention tanks in order to best reduce flood peak flows and in the meantime settle particles. It is, therefore, necessary to understand complex flows patterns and sediment deposition conditions in stormwater detention basins. The aim of this paper is to study flow structure and particle deposition pattern for a given tank geometry in view to control and maximize sediment deposition. Both numerical simulation and experimental works were done to investigate the flow and sediment distribution in a storm tank with a cavity. As it can be indicated, the settle distribution of the particle in a rectangular tank is mainly determined by the flow patterns and the bed shear stress. The flow patterns in a rectangular tank differ with different geometry, entrance flow rate and the water depth. With the changing of flow patterns, the bed shear stress will change respectively, which also play an influence on the particle settling. The accumulation of the particle in the bed changes the conditions at the bottom, which is ignored in the investigations, however it worth much more attention, the influence of the accumulation of the particle on the sedimentation should be important. The approach presented here is based on the resolution of the Reynolds averaged Navier-Stokes equations to account for turbulent effects and also a passive particle transport model. An analysis of particle deposition conditions is presented in this paper in terms of flow velocities and turbulence patterns. Then sediment deposition zones are presented thanks to the modeling with particle tracking method. It is shown that two recirculation zones seem to significantly influence sediment deposition. Due to the possible overestimation of particle trap efficiency with standard wall functions and stick conditions, further investigations seem required for basal boundary conditions based on turbulent kinetic energy and shear stress. These observations are confirmed by experimental investigations processed in the laboratory.

Keywords: storm sewers, sediment deposition, numerical simulation, experimental investigation

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: I. Badhrees

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This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of laser in the Liquid Argon Time Projection Chamber. The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432 pb. The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.

Keywords: ATLAS, CERN, KACST, LArTPC, particle physics

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Authors: Ding Jue, Li Jiahua, Lei Zhidi, Weng Peifen, Li Xiaowei

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With the rapid development of national modern industry, people begin to pay attention to environmental pollution and harm caused by industrial dust. Based on above, a numerical study on the dedusting technology of industrial environment was conducted. The dynamic models of multicomponent particles collision and coagulation, breakage and deposition are developed, and the interaction of water droplet and aerosol particle in 2-Dimension flow field was researched by Eulerian-Lagrangian method and Multi-Monte Carlo method. The effects of the droplet scale, movement speed of droplet and the flow field structure on scavenging efficiency were analyzed. The results show that under the certain condition, 30μm of droplet has the best scavenging efficiency. At the initial speed 1m/s of droplets, droplets and aerosol particles have more time to interact, so it has a better scavenging efficiency for the particle.

Keywords: water droplet, aerosol particle, collision and coagulation, multi-monte carlo method

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Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

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This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Fuzhang Zhao

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Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: diversification search, intensification search, optimal weighting, particle swarm optimization

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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Authors: Shamik Hazra, Sushanta Mitra, Ashis Sen

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Despite growing interest of microparticle manipulation in non-Newtonian fluids, combined effect of viscoelasticity and shear thinning on particle lateral position is not well understood. We performed experiments with rigid microparticles of 15 µm diamater in popular Shear thinning viscoelastic (STVE) liquid poyethylene oxide (PEO) of different molecular weights (MW) and concentrations (c), for Reynolds number (Re) < 1. Microparticles in an STVE liquid revealed four different migration regimes: original streamline (OS), bimodal (BM), centre migration (CM) and defocusing (DF), depending upon the Re and c and interplay of different forces is also elucidated. Our investigation will be helpful to select proper polymer concentration to achieve desired particle focusing inside microchannel.

Keywords: lateral migration, microparticle, polyethylene oxide, shear thinning, viscoelasticity

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Authors: Rashi Rajput, Manisha Singh

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Escitalopram oxalate (ETP), an FDA approved antidepressant drug from the category of SSRI (selective serotonin reuptake inhibitor) and is used in treatment of general anxiety disorder (GAD), major depressive disorder (MDD).When taken orally, it is metabolized to S-demethylcitalopram (S-DCT) and S-didemethylcitalopram (S-DDCT) in the liver with the help of enzymes CYP2C19, CYP3A4 and CYP2D6. Hence, causing side effects such as dizziness, fast or irregular heartbeat, headache, nausea etc. Therefore, targeted and sustained drug delivery will be a helpful tool for increasing its efficacy and reducing side effects. The present study is designed for formulating mucoadhesive nanoparticle formulation for the same Escitalopram loaded polymeric nanoparticles were prepared by ionic gelation method and characterization of the optimised formulation was done by zeta average particle size (93.63nm), zeta potential (-1.89mV), TEM (range of 60nm to 115nm) analysis also confirms nanometric size range of the drug loaded nanoparticles along with polydispersibility index of 0.117. In this research, we have studied the in vitro drug release profile for ETP nanoparticles, through a semi permeable dialysis membrane. The three important characteristics affecting the drug release behaviour were – particle size, ionic strength and morphology of the optimised nanoparticles. The data showed that on increasing the particle size of the drug loaded nanoparticles, the initial burst was reduced which was comparatively higher in drug. Whereas, the formulation with 1mg/ml chitosan in 1.5mg/ml tripolyphosphate solution showed steady release over the entire period of drug release. Then this data was further validated through mathematical modelling to establish the mechanism of drug release kinetics, which showed a typical linear diffusion profile in optimised ETP loaded nanoparticles.

Keywords: ionic gelation, mucoadhesive nanoparticle, semi-permeable dialysis membrane, zeta potential

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Authors: Alica Miller

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A semiflow is a triple consisting of a Hausdorff topological space $X$, a commutative topological monoid $T$ and a continuous monoid action of $T$ on $X$. The acting monoid $T$ is usually either the discrete monoid $\N_0$ of nonnegative integers (in which case the semiflow can be defined as a pair $(X,f)$ consisting of a phase space $X$ and a continuous function $f:X\to X$), or the monoid $\R_+$ of nonnegative real numbers (the so-called one-parameter monoid). However, it turns out that there are real-life situations where it is useful to consider the acting monoids that are a combination of discrete and continuous monoids. That, for example, happens, when we are observing certain dynamical system at discrete moments, but after some time realize that it would be beneficial to continue our observations in real time. The acting monoid in that case would be $T=\{0, t_0, 2t_0, \dots, (n-1)t_0\} \cup [nt_0,\infty)$ with the operation and topology induced from real numbers. This partly explains the motivation for the level of generality which is pursued in our research. We introduce the PSP monoids, which include all but ``pathological'' monoids, and most of our statements hold for them. The topic of our presentation are some recent results about chaos-related properties in semiflows, indecomposability and sensitivity of semiflows in the described general context.

Keywords: chaos, indecomposability, PSP monoids, semiflow, sensitivity

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Authors: Wheyming Tina Song, Chi-Hao Hong

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In this study, we investigate the effect of a new boarding policy - short stay, on the overcrowding efficiency in emergency department (ED). The decision variables are no. of short stay beds for least acuity ED patients. The performance measurements used are national emergency department overcrowding score (NEDOCS) and ED retention rate (the percentage that patients stay in ED over than 48 hours in one month). Discrete event simulation (DES) is used as an analysis tool to evaluate the strategy. Also, common random number (CRN) technique is applied to enhance the simulation precision. The DES model was based on a census of 6 months' patients who were treated in the ED of the National Taiwan University Hospital Yunlin Branch. Our results show that the new short-stay boarding significantly impacts both the NEDOCS and ED retention rate when the no. of short stay beds is more than three.

Keywords: emergency department (ED), common random number (CRN), national emergency department overcrowding score (NEDOCS), discrete event simulation (DES)

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Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

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In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

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Authors: Partha Sarathi Majee, S. Bhattacharyya

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Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: debye length, double layer polarization, electrophoresis, mobility reversal, soft particle

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Authors: Pratibha, Jyoti Kori

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Particles in industry, harvesting, coal mines, etc. may not necessarily be spherical in shape. In general, it is difficult to find perfectly spherical particle. The prediction of movement and deposition of non spherical particle in distinct airway generation is much more difficult as compared to spherical particles. Moreover, there is extensive inflexibility in deposition between ducts of a particular generation and inside every alveolar duct since particle concentrations can be much bigger than the mean acinar concentration. Consequently, a large number of particles fail to be exhaled during expiration. This study presents a mathematical model for the movement and deposition of those non-spherical particles by using particle aspect ratio and shape factor. We analyse the pulsatile behavior underneath sinusoidal wall oscillation due to periodic breathing condition through a non-Darcian porous medium or inside pulmonary region. Since the fluid is viscous and Newtonian, the generalized Navier-Stokes equation in two-dimensional coordinate system (r, z) is used with boundary-layer theory. Results are obtained for various values of Reynolds number, Womersley number, Forchsheimer number, particle aspect ratio and shape factor. Numerical computation is done by using finite difference scheme for very fine mesh in MATLAB. It is found that the overall air velocity is significantly increased by changes in aerodynamic diameter, aspect ratio, alveoli size, Reynolds number and the pulse rate; while velocity is decreased by increasing Forchheimer number.

Keywords: deposition, interstitial lung diseases, non-Darcian medium, numerical simulation, shape factor

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Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Chin Ren Jie, Yip Chun Chieh

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The utilization of industrial by-products, such as steel slag in cementitious materials, not only mitigates environmental impact but also enhances material properties. This study investigates the dual influence of steel slag particle size on the compressive strength and carbonation efficiency of cementitious composites. Through a systematic experimental approach, steel slag particles were incorporated into cement at varying sizes, and the resulting composites were subjected to mechanical and carbonation tests. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) are conducted in this paper. The findings reveal a positive correlation between increased particle size and compressive strength, attributed to the improved interfacial transition zone and packing density. Conversely, smaller particle sizes exhibited enhanced carbonation efficiency, likely due to the increased surface area facilitating the carbonation reaction. The presence of higher silica and calcium content in finer particles was confirmed by EDX, which contributed to the accelerated carbonation process. This study underscores the importance of particle size optimization in designing sustainable cementitious materials with balanced mechanical performance and carbon sequestration potential. The insights gained from the advanced analytical techniques offer a comprehensive understanding of the mechanisms at play, paving the way for the strategic use of steel slag in eco-friendly construction practices.

Keywords: steel slag, carbonation efficiency, particle size enhancement, compressive strength

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Authors: N. A. Zainuddin, I. Norhuda, I. S. Adeib, A. N. Mustapa, S. H. Sarijo

Abstract:

Recently, RESS (Rapid Expansion Supercritical Solution) method has been used by researchers to produce fine particles for pharmaceutical drug substances. Since RESS technology acknowledges a lot of benefits compare to conventional method of ginger extraction, it is suggested to use this method to explore particle formation of bioactive compound from powder ginger. The objective of this research is to produce direct solid oil particles formation from ginger rhizome which contains valuable compounds by using RESS-CO₂ process. RESS experiments were carried using extraction pressure of 3000, 4000, 5000, 6000 and 7000psi and at different extraction temperature of 40, 45, 50, 55, 60, 65 and 70°C for 40 minutes extraction time and contant flowrate (24ml/min). From the studies conducted, it was found that at extraction pressure 5000psi and temperature 40°C, the smallest particle size obtained was 2.22μm on 99 % reduction from the original size of 370μm.

Keywords: particle size, RESS, solid oil particle, supercritical carbon dioxide,

Procedia PDF Downloads 307

Authors: Carola Cappa

Abstract:

Chickpea cooking water (known as aquafaba, AF) is a “waste” product having interesting technological properties exploitable for sustainable plant-based food applications that can encounter a larger consumers demand. Different process conditions to obtain AF were defined; the addition of hydrocolloid (i.e., guar gum) and lactic acid to improve the techno-functionalities of aquafaba was explored, and the effects of these ingredients on the foaming properties and the quality of plant-based target confectionery products were investigated. Meringues having a solid foam structure and a simple formulation (i.e., foaming agent and sugar) and chocolate mousse were chosen as target foods. The effects of the sugar particle size reduction on the empirical and fundamental rheological properties of the foaming agent and of the mousse were evaluated. The treatment did not significantly change the viscosity of the system, while the overrun and foam stability were affected by sugar particle size, and mousse with coarse sugar was characterized by a higher consistency, confirming the importance of the particle size of the ingredients on the texture of the final product. This study proved that AF, a recycled “waste” product, possesses interesting techno-functionalities properties further enhanced by adding lactic acid and modulable according to ingredient particle size; these AF results are useable for plant-based food applications.

Keywords: foaming properties, foam stability, foam texture, particle size, acidification, aquafaba

Procedia PDF Downloads 42

Authors: Nima E. Gorji

Abstract:

The performance and characteristics of a hybrid heterojunction single-walled carbon nanotube and GaAs solar cell is modelled and numerically simulated using AMPS-1D device simulation tool. The device physics and performance parameters with different junction parameters are analysed. The results suggest that the open-circuit voltage changes very slightly by changing the work function, acceptor and donor density while the other electrical parameters reach to an optimum value. Increasing the concentration of a discrete defect density in the absorber layer decreases the electrical parameters. The current-voltage characteristics, quantum efficiency, band gap and thickness variation of the photovoltaic response will be quantitatively considered.

Keywords: carbon nanotube, GaAs, hybrid solar cell, AMPS-1D modelling

Procedia PDF Downloads 302