Search results for: morphology optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4703

Search results for: morphology optimization

3173 Julia-Based Computational Tool for Composite System Reliability Assessment

Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

Abstract:

The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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3172 Multi-Objective Optimization and Effect of Surface Conditions on Fatigue Performance of Burnished Components Made of AISI 52100 Steel

Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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3171 Research on the Optimization of the Facility Layout of Efficient Cafeterias for Troops

Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

Abstract:

BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: layout optimization, dining efficiency, troops’ cafeteria, anylogic simulation, field experiment

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3170 Exploring the Role of IPv6 in Enhancing IoT Communication and Green Network Optimization for Business Sustainability

Authors: Saqib Warsi

Abstract:

The Internet of Things (IoT) has become an essential component of modern communication networks, with IPv6 playing a pivotal role in addressing the challenges posed by the rapidly growing number of connected devices. IPv6 provides an expanded address space, offering a solution to the limitations of IPv4 while enhancing routing efficiency and security. This paper explores the impact of IPv6 in improving IoT communication, focusing on its operational benefits for businesses. Additionally, we examine the integration of green communication principles, which aim to reduce energy consumption and operational costs, thus promoting environmental sustainability and business efficiency. Through qualitative analysis and simulation-based modeling, this paper investigates the benefits of IPv6 in IoT environments and evaluates the role of green communication strategies in optimizing network performance. Traffic measurement tools and network performance simulators were employed to analyze the efficiency, sustainability, and scalability of IPv6 networks. By presenting a comprehensive framework for traffic analysis, modeling, and optimization, this research highlights the potential of combining IPv6 and green communication practices to drive business growth while promoting environmental sustainability. The findings provide valuable insights for businesses adopting more sustainable and efficient communication networks.

Keywords: IPv6, Internet of Things (IoT), green communications, traffic measurement and modeling, network virtualization

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3169 The Role of the Child's Previous Inventory in Verb Overgeneralization in Spanish Child Language: A Case Study

Authors: Mary Rosa Espinosa-Ochoa

Abstract:

The study of overgeneralization in inflectional morphology provides evidence for understanding how a child's mind works when applying linguistic patterns in a novel way. High-frequency inflectional forms in the input cause inappropriate use in contexts related to lower-frequency forms. Children learn verbs as lexical items and new forms develop only gradually, around their second year: most of the utterances that children produce are closely related to what they have previously produced. Spanish has a complex verbal system that inflects for person, mood, and tense. Approximately 200 verbs are irregular, and bare roots always require an inflected form, which represents a challenge for the memory. The aim of this research is to investigate i) what kinds of overgeneralization errors children make in verb production, ii) to what extent these errors are related to verb forms previously produced, and iii) whether the overgeneralized verb components are also frequent in children’s linguistic inventory. It consists of a high-density longitudinal study of a middle-class girl (1;11,24-2;02,24) from Mexico City, whose utterances were recorded almost daily for three months to compile a unique corpus in the Spanish language. Of the 358 types of inflected verbs produced by the child, 9.11% are overgeneralizations. Not only are inflected forms (verbal and pronominal clitics) overgeneralized, but also verbal roots. Each of the forms can be traced to previous utterances, and they show that the child is detecting morphological patterns. Neither verbal roots nor inflected forms are associated with high frequency patterns in her own speech. For example, the child alternates the bare roots of an irregular verb, cáye-te* and cáiga-te* (“fall down”), to express the imperative of the verb cá-e-te (fall down.IMPERATIVE-PRONOMINAL.CLITIC), although cay-ó (PAST.PERF.3SG) is the most frequent form of her previous complete inventory, and the combined frequency of caer (INF), cae (PRES.INDICATIVE.3SG), and caes (PRES.INDICATIVE.2SG) is the same as that of as caiga (PRES.SUBJ.1SG and 3SG). These results provide evidence that a) two forms of the same verb compete in the child’s memory, and b) although the child uses her own inventory to create new forms, these forms are not necessarily frequent in her memory storage, which means that her mind is more sensitive to external stimuli. Language acquisition is a developing process, given the sensitivity of the human mind to linguistic interaction with the outside world.

Keywords: inflection, morphology, child language acquisition, Spanish

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3168 The Corrosion Resistance of the 32CrMoV13 Steel Nitriding

Authors: Okba Belahssen, Lazhar Torchane, Said Benramache, Abdelouahed Chala

Abstract:

This paper presents corrosion behavior of the plasma-nitrided 32CrMoV13 steel. Different kinds of samples were tested: non-treated, plasma nitrided samples. The structure of layers was determined by X-ray diffraction, while the morphology was observed by scanning electron microscopy (SEM). The corrosion behavior was evaluated by electrochemical techniques (potentiodynamic curves and electrochemical impedance spectroscopy). The corrosion tests were carried out in acid chloride solution (HCl 1M). Experimental results showed that the nitrides ε-Fe2−3N and γ′-Fe4N present in the white layer are nobler than the substrate but may promote, by galvanic effect, a localized corrosion through open porosity. The better corrosion protection was observed for nitrided sample.

Keywords: plasma-nitrided, 32CrMoV13 steel, corrosion, EIS

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3167 Synthesis of Ion Imprinted Polymer for Removal of Chromium(III) Ion in Environmental Samples

Authors: Elham Moniri, Zohre Moradi

Abstract:

In this study, ion imprinted poly urea-formaldehyde was prepared. The morphology imprinted polymer was studied by scanning electron microscopy. Then, the effects of various parameters on Cr(III) sorption such as pH, contact time were investigated. The optimum pH value for sorption of Cr(III) was 6. The sorption capacity of imprinted poly urea-formaldehyde for Cr(III) were 4 mg.g−1. A Cr(III) removal of 97-98% was obtained. The profile of Cr(III) uptake on this sorbent reflects good accessibility of the chelating sites in the imprinted poly urea-formaldehyde. The developed method was utilized for determination of Cr(III) in environmental water samples by flame atomic absorption spectrometry with satisfactory results.

Keywords: chromium ion, environmental sample, elimination, imprinted poly urea-formaldehyde, polymeric sorbent

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3166 Probabilistic Approach of Dealing with Uncertainties in Distributed Constraint Optimization Problems and Situation Awareness for Multi-agent Systems

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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3165 Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique

Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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3164 Performance Enhancement of Hybrid Racing Car by Design Optimization

Authors: Tarang Varmora, Krupa Shah, Karan Patel

Abstract:

Environmental pollution and shortage of conventional fuel are the main concerns in the transportation sector. Most of the vehicles use an internal combustion engine (ICE), powered by gasoline fuels. This results into emission of toxic gases. Hybrid electric vehicle (HEV) powered by electric machine and ICE is capable of reducing emission of toxic gases and fuel consumption. However to build HEV, it is required to accommodate motor and batteries in the vehicle along with engine and fuel tank. Thus, overall weight of the vehicle increases. To improve the fuel economy and acceleration, the weight of the HEV can be minimized. In this paper, the design methodology to reduce the weight of the hybrid racing car is proposed. To this end, the chassis design is optimized. Further, attempt is made to obtain the maximum strength with minimum material weight. The best configuration out of the three main configurations such as series, parallel and the dual-mode (series-parallel) is chosen. Moreover, the most suitable type of motor, battery, braking system, steering system and suspension system are identified. The racing car is designed and analyzed in the simulating software. The safety of the vehicle is assured by performing static and dynamic analysis on the chassis frame. From the results, it is observed that, the weight of the racing car is reduced by 11 % without compromising on safety and cost. It is believed that the proposed design and specifications can be implemented practically for manufacturing hybrid racing car.

Keywords: design optimization, hybrid racing car, simulation, vehicle, weight reduction

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3163 Research on Pilot Sequence Design Method of Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing System Based on High Power Joint Criterion

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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3162 Optimization of Hot Metal Charging Circuit in a Steel Melting Shop Using Industrial Engineering Techniques for Achieving Manufacturing Excellence

Authors: N. Singh, A. Khullar, R. Shrivastava, I. Singh, A. S. Kumar

Abstract:

Steel forms the basis of any modern society and is essential to economic growth. India’s annual crude steel production has seen a consistent increase over the past years and is poised to grow to 300 million tons per annum by 2030-31 from current level of 110-120 million tons per annum. Steel industry is highly capital-intensive industry and to remain competitive, it is imperative that it invests in operational excellence. Due to inherent nature of the industry, there is large amount of variability in its supply chain both internally and externally. Production and productivity of a steel plant is greatly affected by the bottlenecks present in material flow logistics. The internal logistics constituting of transport of liquid metal within a steel melting shop (SMS) presents an opportunity in increasing the throughput with marginal capital investment. The study was carried out at one of the SMS of an integrated steel plant located in the eastern part of India. The plant has three SMS’s and the study was carried out at one of them. The objective of this study was to identify means to optimize SMS hot metal logistics through application of industrial engineering techniques. The study also covered the identification of non-value-added activities and proposed methods to eliminate the delays and improve the throughput of the SMS.

Keywords: optimization, steel making, supply chain, throughput enhancement, workforce productivity

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3161 High Performance Ceramic-Based Phthalonitrile Micro and Nanocomposites

Authors: M. Derradji, W. B. Liu

Abstract:

The current work discusses the effects of adding various types of ceramic fillers on the curing behavior, thermal, mechanical, anticorrosion, and UV shielding properties of the bisphenol-A based phthalonitrile resins. The effects of different ceramic filler contents and sizes as well as their surface treatments are also discussed in terms of their impact on the morphology and mechanisms of enhancement. The synergistic effect obtained by these combinations extends the use of the phthalonitrile resins to more exigent applications such as aerospace and military. The presented results reveal the significant advantages that can be obtained from the preparation of hybrid materials based on phthalonitrile resins and open the way for further research in the field.

Keywords: mechanical properties, particle reinforced composites, polymer matrix composites (PMCs), thermal properties

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3160 A Syntactic Approach to Applied and Socio-Linguistics in Arabic Language in Modern Communications

Authors: Adeyemo Abduljeeel Taiwo

Abstract:

This research is an attempt that creates a conducive atmosphere of a phonological and morphological compendium of Arabic language in Modern Standard Arabic (MSA) for modern day communications. The research is carried out with the chief aim of grammatical analysis of the two broad fields of Arabic linguistics namely: Applied and Socio-Linguistics. It draws a pictorial record of Applied and Socio-Linguistics in Arabic phonology and morphology. Thematically, it postulates and contemplates to a large degree, the theory of concord in contemporary modern Arabic language acquisition. It utilizes an analytical method while it portrays Arabic as a Semitic language that promotes linguistics and syntax among the scholars of the fields.

Keywords: Arabic language, applied linguistics, socio-linguistics, modern communications

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3159 Thermal Analysis and Optimization of a High-Speed Permanent Magnet Synchronous Motor with Toroidal Windings

Authors: Yuan Wan, Shumei Cui, Shaopeng Wu

Abstract:

Toroidal windings were taken advantage of to reduce of axial length of the motor, so as to match the applications that have severe restrictions on the axial length. But slotting in the out edge of the stator will decrease the heat-dissipation capacity of the water cooling of the housing. Besides, the windings in the outer slots will increase the copper loss, which will further increase the difficult for heat dissipation of the motor. At present, carbon-fiber composite retaining sleeve are increasingly used to be mounted over the magnets to ensure the rotor strength at high speeds. Due to the poor thermal conductivity of carbon-fiber sleeve, the cooling of the rotor becomes very difficult, which may result in the irreversible demagnetization of magnets for the excessively high temperature. So it is necessary to analyze the temperature rise of such motor. This paper builds a computational fluid dynamic (CFD) model of a toroidal-winding high-speed permanent magnet synchronous motor (PMSM) with water cooling of housing and forced air cooling of rotor. Thermal analysis was carried out based on the model and the factors that affects the temperature rise were investigated. Then thermal optimization for the prototype was achieved. Finally, a small-size prototype was manufactured and the thermal analysis results were verified.

Keywords: thermal analysis, temperature rise, toroidal windings, high-speed PMSM, CFD

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3158 Test Suite Optimization Using an Effective Meta-Heuristic BAT Algorithm

Authors: Anuradha Chug, Sunali Gandhi

Abstract:

Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

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3157 Polymer Advancement with Poly(High Internal Phase Emulsion) Poly(S/DVB) Modified via Layer-by-Layer for CO2 Adsorption

Authors: Saifon Chongthub

Abstract:

The purpose of this research is to synthesize adsorbent foam for CO2 adsorption. The polymer was prepared from poly High Internal Phase Emulsion (PolyHIPE) using styrene as monomer and divinylbenzene as comonomer. Its morphology was determined by Scanning Electron Microscopy (SEM). To further increased CO2 adsorption of the prepared polyHIPE, the layer by layer (LbL) technique was applied, which alternated polyelectrolyte injection between layers of Poly(styrenesulfonate) (PSS) and Poly(diallyldimetyl-ammonium chloride)(PDADMAC) as primary layer, and layers of PSS and polyetyleneimine (PEI) as secondary layer.

Keywords: high internal phase emulsion, polyHIPE, surface modification, layer by layer technique, CO2 adsorption

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3156 Investigation of NiO/V₂O₅ Powder Composite as Cathode Material for Lithium-Ion Batteries

Authors: Katia Ayouz-Chebout, Fatima Boudeffar, Maha Ayat, Malika Berouaken, Chafiaa Yaddaden, Saloua Merazga, Nouredine Gabouze

Abstract:

Transition metal oxide composites have been widely reported in energy storage and conversion systems. In this regard, an attempt has been made to synthesize NiO@V₂O₅ nanocomposite. The structures and morphology of synthesized powder are investigated by X-ray diffraction, scanning electron microscope (SEM), and Attenuated Total Reflection (ATR). The electrochemical properties and performances as cathode electrodes based on active material NiO@V₂O₅ were studied by cyclic voltammetry (CV), between potential bias [0.01V to 3V], with scanning speed of 0,1mVs⁻¹, the galvanostatic charge/discharge (CDG) for 100 cycles was also measured.

Keywords: composite nanobelts, vanadium pentoxide, nickel oxide, Li-ion batteries

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3155 Optimal 3D Deployment and Path Planning of Multiple Uavs for Maximum Coverage and Autonomy

Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

Abstract:

Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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3154 The Synthesis of AgInS₂/SnS₂ Nanocomposites with Enhanced Photocatalytic Degradation of Norfloxacin

Authors: Mingmei Zhang, Xinyong Li

Abstract:

AgInS₂/SnS₂ (AIS) nanocomposites were synthesized by a simple hydrothermal method. The morphology and composition of the fabricated AIS nanocomposites were investigated by field-emission scanning electron microscopy (SEM), X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). Moreover, the as-prepared AIS photocatalysts exhibited excellent photocatalytic activities for the degradation of Norfloxacin (NOR), mainly due to its high optical absorption and separation efficiency of photogenerated electron-hole pairs, as evidenced by UV–vis diffusion reflection spectra (DRS) and Surface photovoltage (SPV) spectra. Furthermore, the interfacial charges transfer mechanism was also discussed by DFT calculations.

Keywords: AIS nanocomposites, electron-hole pairs, charges transfer, DFTcaculations

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3153 Human Coronary Sinus Venous System as a Target for Clinical Procedures

Authors: Wiesława Klimek-Piotrowska, Mateusz K. Hołda, Mateusz Koziej, Katarzyna Piątek, Jakub Hołda

Abstract:

Introduction: The coronary sinus venous system (CSVS), which has always been overshadowed by the coronary arterial tree, has recently begun to attract more attention. Since it is a target for clinicians the knowledge of its anatomy is essential. Cardiac resynchronization therapy, catheter ablation of cardiac arrhythmias, defibrillation, perfusion therapy, mitral valve annuloplasty, targeted drug delivery, and retrograde cardioplegia administration are commonly used therapeutic methods involving the CSVS. The great variability in the course of coronary veins and tributaries makes the diagnostic and therapeutic processes difficult. Our aim was to investigate detailed anatomy of most common clinically used CSVS`s structures: the coronary sinus with its ostium, great cardiac vein, posterior vein of the left ventricle, middle cardiac vein and oblique vein of the left atrium. Methodology: This is a prospective study of 70 randomly selected autopsied hearts dissected from adult humans (Caucasian) aged 50.1±17.6 years old (24.3% females) with BMI=27.6±6.7 kg/m2. The morphology of the CSVS was assessed as well as its precise measurements were performed. Results: The coronary sinus (CS) with its ostium was present in all hearts. The mean CS ostium diameter was 9.9±2.5mm. Considered ostium was covered by its valve in 87.1% with mean valve height amounted 5.1±3.1mm. The mean percentage coverage of the CS ostium by the valve was 56%. The Vieussens valve was present in 71.4% and was unicuspid in 70%, bicuspid in 26% and tricuspid in 4% of hearts. The great cardiac vein was present in all cases. The oblique vein of the left atrium was observed in 84.3% of hearts with mean length amounted 20.2±9.3mm and mean ostium diameter 1.4±0.9mm. The average length of the CS (from the CS ostium to the Vieussens valve) was 31.1±9.5mm or (from the CS ostium to the ostium of the oblique vein of the left atrium) 28.9±10.1mm and both were correlated with the heart weight (r=0.47; p=0.00 and r=0.38; p=0.006 respectively). In 90.5% the ostium of the oblique vein of the left atrium was located proximally to the Vieussens valve, in remaining cases was distally. The middle cardiac vein was present in all hearts and its valve was noticed in more than half of all the cases (52.9%). The posterior vein of the left ventricle was observed in 91.4% of cases. Conclusions: The CSVS is vastly variable and none of basic hearts parameters is a good predictor of its morphology. The Vieussens valve could be a significant obstacle during CS cannulation. Caution should be exercised in this area to avoid coronary sinus perforation. Because of the higher incidence of the presence of the oblique vein of the left atrium than the Vieussens valve, the vein orifice is more useful in determining the CS length.

Keywords: cardiac resynchronization therapy, coronary sinus, Thebesian valve, Vieussens valve

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3152 Mechanism of Failure of Pipeline Steels in Sour Environment

Authors: Abhishek Kumar

Abstract:

X70 pipeline steel was electrochemically charged with hydrogen for different durations in order to find crack nucleation and propagation sites. After 3 hours charging, suitable regions for crack initiation and propagation were found. These regions were studied by OM, SEM, EDS and later Vicker hardness test was done. The results brought out that HIC cracks nucleated from regions rich of inclusions and further propagated through the segregation area of some elements, such as manganese, carbon, silicon and sulfur. It is worth-mentioning that all these potential sites for crack nucleation and propagation appeared at the centre of cross section of the specimens. Additionally, cracked area has harder phase than the non-cracked area which was confirmed by hardness test.

Keywords: X70 steel, morphology of inclusions, SEM/EDS/OM, simulation, statistical data

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3151 Bioinspired Green Synthesis of Magnetite Nanoparticles Using Room-Temperature Co-Precipitation: A Study of the Effect of Amine Additives on Particle Morphology in Fluidic Systems

Authors: Laura Norfolk, Georgina Zimbitas, Jan Sefcik, Sarah Staniland

Abstract:

Magnetite nanoparticles (MNP) have been an area of increasing research interest due to their extensive applications in industry, such as in carbon capture, water purification, and crucially, the biomedical industry. The use of MNP in the biomedical industry is rising, with studies on their effect as Magnetic resonance imaging contrast agents, drug delivery systems, and as hyperthermic cancer treatments becoming prevalent in the nanomaterial research community. Particles used for biomedical purposes must meet stringent criteria; the particles must have consistent shape and size between particles. Variation between particle morphology can drastically alter the effective surface area of the material, making it difficult to correctly dose particles that are not homogeneous. Particles of defined shape such as octahedral and cubic have been shown to outperform irregular shaped particles in some applications, leading to the need to synthesize particles of defined shape. In nature, highly homogeneous MNP are found within magnetotactic bacteria, a unique bacteria capable of producing magnetite nanoparticles internally under ambient conditions. Biomineralisation proteins control the properties of the MNPs, enhancing their homogeneity. One of these proteins, Mms6, has been successfully isolated and used in vitro as an additive in room-temperature co-precipitation reactions (RTCP) to produce particles of defined mono-dispersed size & morphology. When considering future industrial scale-up it is crucial to consider the costs and feasibility of an additive, as an additive that is not readily available or easily synthesized at a competitive price will not be sustainable. As such, additives selected for this research are inspired by the functional groups of biomineralisation proteins, but cost-effective, environmentally friendly, and compatible with scale-up. Diethylenetriamine (DETA), triethylenetetramine (TETA), tetraethylenepentamine (TEPA), and pentaethylenehexamine (PEHA) have been successfully used in RTCP to modulate the properties of particles synthesized, leading to the formation of octahedral nanoparticles with no use of organic solvents, heating, or toxic precursors. By extending this principle to a fluidic system, ongoing research will reveal whether the amine additives can also exert morphological control in an environment which is suited toward higher particle yield. Two fluidic systems have been employed; a peristaltic turbulent flow mixing system suitable for the rapid production of MNP, and a macrofluidic system for the synthesis of tailored nanomaterials under a laminar flow regime. The presence of the amine additives in the turbulent flow system in initial results appears to offer similar morphological control as observed under RTCP conditions, with higher proportions of octahedral particles formed. This is a proof of concept which may pave the way to green synthesis of tailored MNP on an industrial scale. Mms6 and amine additives have been used in the macrofluidic system, with Mms6 allowing magnetite to be synthesized at unfavourable ferric ratios, but no longer influencing particle size. This suggests this synthetic technique while still benefiting from the addition of additives, may not allow additives to fully influence the particles formed due to the faster timescale of reaction. The amine additives have been tested at various concentrations, the results of which will be discussed in this paper.

Keywords: bioinspired, green synthesis, fluidic, magnetite, morphological control, scale-up

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3150 A Digital Twin Approach to Support Real-time Situational Awareness and Intelligent Cyber-physical Control in Energy Smart Buildings

Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

Abstract:

Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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3149 Optimization of Lercanidipine Nanocrystals Using Design of Experiments Approach

Authors: Dolly Gadhiya, Jayvadan Patel, Mihir Raval

Abstract:

Lercanidipine hydrochloride is a calcium channel blockers used for treating angina pectoris and hypertension. Lercanidipine is a BCS Class II drug having poor aqueous solubility. Absolute bioavailability of Lercanidipine is very low and the main reason ascribed for this is poor aqueous solubility of the drug. Design and formulatation of nanocrystals by media milling method was main focus of this study. In this present study preliminary optimization was carried out with one factor at a time (OFAT) approach. For this different parameters like size of milling beads, amount of zirconium beads, types of stabilizer, concentrations of stabilizer, concentrations of drug, stirring speeds and milling time were optimized on the basis of particle size, polydispersity index and zeta potential. From the OFAT model different levels for above parameters selected for Plackett - Burman Design (PBD). Plackett-Burman design having 13 runs involving 6 independent variables was carried out at higher and lower level. Based on statistical analysis of PBD it was found that concentration of stabilizer, concentration of drug and stirring speed have significant impact on particle size, PDI, zeta potential value and saturation solubility. These experimental designs for preparation of nanocrystals were applied successfully which shows increase in aqueous solubility and dissolution rate of Lercanidipine hydrochloride.

Keywords: Lercanidipine hydrochloride, nanocrystals, OFAT, Plackett Burman

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3148 Chitosan-Whey Protein Isolate Core-Shell Nanoparticles as Delivery Systems

Authors: Zahra Yadollahi, Marjan Motiei, Natalia Kazantseva, Petr Saha

Abstract:

Chitosan (CS)-whey protein isolate (WPI) core-shell nanoparticles were synthesized through self-assembly of whey protein isolated polyanions and chitosan polycations in the presence of tripolyphosphate (TPP) as a crosslinker. The formation of this type of nanostructures with narrow particle size distribution is crucial for developing delivery systems since the functional characteristics highly depend on their sizes. To achieve this goal, the nanostructure was optimized by varying the concentrations of WPI, CS, and TPP in the reaction mixture. The chemical characteristics, surface morphology, and particle size of the nanoparticles were evaluated.

Keywords: whey protein isolated, chitosan, nanoparticles, delivery system

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3147 MHD Boundary Layer Flow of a Nanofluid Past a Wedge Shaped Wick in Heat Pipe

Authors: Ziya Uddin

Abstract:

This paper deals with the theoretical and numerical investigation of magneto-hydrodynamic boundary layer flow of a nano fluid past a wedge shaped wick in heat pipe used for the cooling of electronic components and different type of machines. To incorporate the effect of nanoparticle diameter, concentration of nanoparticles in the pure fluid, nano thermal layer formed around the nanoparticle and Brownian motion of nano particles etc., appropriate models are used for the effective thermal and physical properties of nano fluids. To model the rotation of nano particles inside the base fluid, microfluidics theory is used. In this investigation ethylene glycol (EG) based nanofluids, are taken into account. The non-linear equations governing the flow and heat transfer are solved by using a very effective particle swarm optimization technique along with Runge-Kutta method. The values of heat transfer coefficient are found for different parameters involved in the formulation viz. nanoparticle concentration, nanoparticle size, magnetic field and wedge angle etc. It is found that the wedge angle, presence of magnetic field, nanoparticle size and nanoparticle concentration etc. have prominent effects on fluid flow and heat transfer characteristics for the considered configuration.

Keywords: nanofluids, wedge shaped wick, heat pipe, numerical modeling, particle swarm optimization, nanofluid applications, Heat transfer

Procedia PDF Downloads 393
3146 Optimizing and Evaluating Performance Quality Control of the Production Process of Disposable Essentials Using Approach Vague Goal Programming

Authors: Hadi Gholizadeh, Ali Tajdin

Abstract:

To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression

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3145 Review of the Model-Based Supply Chain Management Research in the Construction Industry

Authors: Aspasia Koutsokosta, Stefanos Katsavounis

Abstract:

This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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3144 Ta-doped Nb2O5: Synthesis and Photocatalytic Activity

Authors: Mahendrasingh J. Pawar, M. D. Gaoner

Abstract:

Ta-doped Nb2O5 (Ta content 0.5-2% mole fraction) nanoparticles in the range of 20-40 nm were synthesized by combustion technique. The crystalline phase, morphology and size of the nanoparticles were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and UV-vis spectroscopy. The specific surface area of the nanoparticles was measured by nitrogen adsorption (BET analysis). The undoped Nb2O5 nanoparticles were found to have the particles size in the range of 50−80 nm. The photocatalytic performance of the samples was characterized by degrading 20 mg/L toluene under UV−Vis irradiation. The results show that the Ta-doped Nb2O5 nanoparticles exhibit a significant increase in photocatalytic performance over the undoped Nb2O5 nanoparticles, and the Nb2O5 nanoparticles doped with 1.5% Ta and calcined at 450°C show the best photocatalytic performance.

Keywords: Nb2O5, Ta-doped Nb2O5, photodegradation of Toluene, combustion method

Procedia PDF Downloads 569