Search results for: generalized differential quadrature
984 Isothermal Crystallization Kinetics of Lauric Acid Methyl Ester from DSC Measurements
Authors: Charine Faith H. Lagrimas, Rommel N. Galvan, Rizalinda L. de Leon
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An ongoing study, methyl laurate to be used as a refrigerant in an HVAC system, requires the crystallization kinetics of the said substance. Step-wise and normal forms of Avrami model parameters were used to describe the isothermal crystallization kinetics of methyl laurate at different temperatures from Differential Scanning Calorimetry (DSC) measurements. At 3 °C, parameters showed that methyl laurate exhibits a secondary crystallization. The primary crystallization occurred with instantaneous nuclei and spherulitic growth; followed by a secondary instantaneous nucleation with a lower growth of dimensionality, rod-like. At 4 °C to 6 °C, the exotherms from DSC implied that the system was under the isokinetic range. The kinetics behavior is the same which is instantaneous nucleation with one-dimensional growth. The differences for the isokinetic range temperatures are the activation energies (directly proportional to T) and nucleation rates (inversely proportional to T). From the images obtained during the crystallization of methyl laurate using an optical microscope, it is confirmed that the nucleation and crystal growth modes obtained from the optical microscope are consistent with the parameters from Avrami model.Keywords: Avrami model, isothermal crystallization, lipids kinetics, methyl laurate
Procedia PDF Downloads 342983 Hybrid Inventory Model Optimization under Uncertainties: A Case Study in a Manufacturing Plant
Authors: E. Benga, T. Tengen, A. Alugongo
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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant
Procedia PDF Downloads 382982 Adaptive Backstepping Control of Uncertain Nonlinear Systems with Input Backlash
Authors: Ali Anwar, Hu Qinglei, Li Bo, Muhammad Taha Ali
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In this paper a generic model of perturbed nonlinear systems is considered which is affected by hard backlash nonlinearity at the input. The nonlinearity is modelled by a dynamic differential equation which presents a more precise shape as compared to the existing linear models and is compatible with nonlinear design technique such as backstepping. Moreover, a novel backstepping based nonlinear control law is designed which explicitly incorporates a continuous-time adaptive backlash inverse model. It provides a significant flexibility to control engineers, whereby they can use the estimated backlash spacing value specified on actuators such as gears etc. in the adaptive Backlash Inverse model during the control design. It ensures not only global stability but also stringent transient performance with desired precision. It is also robust to external disturbances upon which the bounds are taken as unknown and traverses the backlash spacing efficiently with underestimated information about the actual value. The continuous-time backlash inverse model is distinguished in the sense that other models are either discrete-time or involve complex computations. Furthermore, numerical simulations are presented which not only illustrate the effectiveness of proposed control law but also its comparison with PID and other backstepping controllers.Keywords: adaptive control, hysteresis, backlash inverse, nonlinear system, robust control, backstepping
Procedia PDF Downloads 461981 Task Evoked Pupillary Response for Surgical Task Difficulty Prediction via Multitask Learning
Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi
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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh
Procedia PDF Downloads 146980 Differential Terrain: A Spectrum in Capitalism Transformation
Authors: Sibo Lu, Zhongkai Qian
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This study endeavors to articulate a spectrum of capitalist transformation from a politico-economic perspective, categorizing the development of capitalism into pre-modern, modern, and post-modern stages while examining the transitions between these states. It critically engages with the concepts of pre-modernity, modernity, and post-modernity, typically aligned with cultural studies, to shed light on their objective changes in the politico-economic realm. Post-modernity, in this context, is associated with the transition to high-value-added services and economic growth in ‘developed’ countries amidst globalization, framing a ‘neoliberal’ economic transformation. The paper scrutinizes the neoliberal economic shifts in the latter half of the 20th century as part of the post-modern state, arguing against viewing post-modernity merely as a cultural or subjective interpretative stance. Instead, it is posited as a concrete politico-economic phase marked by the dominance of post-Fordist systems. Through integrating insights from the political economy with continental philosophy, this research provides a nuanced analysis of capitalism's evolution, challenging conventional class analyses under the capitalist system and fostering a broader understanding of socio-economic paradigms.Keywords: post marxism, critical theory, political economy, capitalism transformation
Procedia PDF Downloads 35979 Modelling and Optimisation of Floating Drum Biogas Reactor
Authors: L. Rakesh, T. Y. Heblekar
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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.Keywords: biogas, floating drum reactor, neural network model, optimization
Procedia PDF Downloads 143978 Effect of Corrugating Bottom Surface on Natural Convection in a Square Porous Enclosure
Authors: Khedidja Bouhadef, Imene Said Kouadri, Omar Rahli
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In this paper numerical investigation is performed to analyze natural convection heat transfer characteristics within a wavy-wall enclosure filled with fluid-saturated porous medium. The bottom wall which has the wavy geometry is maintained at a constant high temperature, while the top wall is straight and is maintained at a constant lower temperature. The left and right walls of the enclosure are both straight and insulated. The governing differential equations are solved by Finite-volume approach and grid generation is used to transform the physical complex domain to a computational regular space. The aim is to examine flow field, temperature distribution and heat transfer evolutions inside the cavity when Darcy number, Rayleigh number and undulations number values are varied. The results mainly indicate that the heat transfer is rather affected by the permeability and Rayleigh number values since increasing these values enhance the Nusselt number; although the exchanges are not highly affected by the undulations number.Keywords: grid generation, natural convection, porous medium, wavy wall enclosure
Procedia PDF Downloads 264977 Very Large Scale Integration Architecture of Finite Impulse Response Filter Implementation Using Retiming Technique
Authors: S. Jalaja, A. M. Vijaya Prakash
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Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.Keywords: carry save adder Karatsuba multiplication, mid range Karatsuba multiplication, modified FFA and transposed filter, retiming
Procedia PDF Downloads 235976 Clustering Color Space, Time Interest Points for Moving Objects
Authors: Insaf Bellamine, Hamid Tairi
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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering
Procedia PDF Downloads 378975 Conversion of Jatropha curcas Oil to Ester Biolubricant Using Solid Catalyst Derived from Saltwater Clam Shell Waste (SCSW)
Authors: Said Nurdin, Fatimah A. Misebah, Rosli M. Yunus, Mohd S. Mahmud, Ahmad Z. Sulaiman
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The discarded clam shell waste, fossil and edible oil as biolubricant feedstocks create environmental impacts and food chain dilemma, thus this work aims to circumvent these issues by using activated saltwater clam shell waste (SCSW) as solid catalyst for conversion of Jatropha curcas oil as non-edible sources to ester biolubricant. The characterization of solid catalyst was done by Differential Thermal Analysis-Thermo Gravimetric Analysis (DTA-TGA), X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Field Emission Scanning Electron Microscopy (FESEM) and Fourier Transformed Infrared Spectroscopy (FTIR) analysis. The calcined catalyst was used in the transesterification of Jatropha oil to methyl ester as the first step, and the second stage was involved the reaction of Jatropha methyl ester (JME) with trimethylolpropane (TMP) based on the various process parameters. The formated biolubricant was analyzed using the capillary column (DB-5HT) equipped Gas Chromatography (GC). The conversion results of Jatropha oil to ester biolubricant can be found nearly 96.66%, and the maximum distribution composition mainly contains 72.3% of triester (TE).Keywords: conversion, Jatropha curcas oil, ester biolubricant, solid catalyst
Procedia PDF Downloads 368974 Synthesis, Characterization and Electrical Studies of Solid Polymer Electrolyte (1-x) PANI-KAg₄I₅.xAl₂O₃
Authors: Rafiuddin
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Solid polymer electrolytes have emerged as an area of interest in the field of solid state chemistry owing to their facile and cost-effective synthesis and number of applications in different areas of chemistry, extending over a wide range of temperatures. In the present work, polymer composite solid electrolyte comprising of Polyaniline (PANI) as polymer and potassium silver iodide (KAg4I5) using alumina (Al2O3) of different compositions having the formula (1-x) PANI- KAg4I5. x Al2O3 with x ranging from 0.0 to 0.5 was prepared by solid state reaction method. The structural elucidation and characterization was done by X- Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric- Differential Thermal Analysis (TG-DTA) and Impedance Spectroscopy. The thermal analysis shows a phase transition at 147°C attributed to β-α phase transition of AgI due to the disproportionation of KAg4I5 to AgI and KAg2I3 at temperatures higher than 36°C. The X Ray diffraction analysis also confirms the presence of both AgI and KAg2I3 in the samples. The conductivities recorded over a temperature range of 40-250° C lie in the range of 10-1 to 10-3 S cm-1. Maximum conductivity was seen in the compositon x = 0.4 i.e. 1.84 × 10-2 Scm-1 at 313 K and 1.38 × 10-1 Scm-1 at 513 K, with a minimum activation energy of 0.14 eV.Keywords: polymer solid electrolytes, XRD, DTA, electrical conductivity, impedance spectroscopy
Procedia PDF Downloads 302973 Anthraquinone Labelled DNA for Direct Detection and Discrimination of Closely Related DNA Targets
Authors: Sarah A. Goodchild, Rachel Gao, Philip N. Bartlett
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A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices.Keywords: Anthraquinone, discrimination, DNA detection, electrochemical biosensor
Procedia PDF Downloads 393972 More Precise: Patient-Reported Outcomes after Stroke
Authors: Amber Elyse Corrigan, Alexander Smith, Anna Pennington, Ben Carter, Jonathan Hewitt
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Background and Purpose: Morbidity secondary to stroke is highly heterogeneous, but it is important to both patients and clinicians in post-stroke management and adjustment to life after stroke. The consideration of post-stroke morbidity clinically and from the patient perspective has been poorly measured. The patient-reported outcome measures (PROs) in morbidity assessment help improve this knowledge gap. The primary aim of this study was to consider the association between PRO outcomes and stroke predictors. Methods: A multicenter prospective cohort study assessed 549 stroke patients at 19 hospital sites across England and Wales during 2019. Following a stroke event, demographic, clinical, and PRO measures were collected. Prevalence of morbidity within PRO measures was calculated with associated 95% confidence intervals. Predictors of domain outcome were calculated using a multilevel generalized linear model. Associated P -values and 95% confidence intervals are reported. Results: Data were collected from 549 participants, 317 men (57.7%) and 232 women (42.3%) with ages ranging from 25 to 97 (mean 72.7). PRO morbidity was high post-stroke; 93.2% of the cohort report post-stroke PRO morbidity. Previous stroke, diabetes, and gender are associated with worse patient-reported outcomes across both the physical and cognitive domains. Conclusions: This large-scale multicenter cohort study illustrates the high proportion of morbidity in PRO measures. Further, we demonstrate key predictors of adverse outcomes (Diabetes, previous stroke, and gender) congruence with clinical predictors. The PRO has been demonstrated to be an informative and useful stroke when considering patient-reported outcomes and has wider implications for considerations of PROs in clinical management. Future longitudinal follow-up with PROs is needed to consider association of long-term morbidity.Keywords: morbidity, patient-reported outcome, PRO, stroke
Procedia PDF Downloads 131971 Optimal Continuous Scheduled Time for a Cumulative Damage System with Age-Dependent Imperfect Maintenance
Authors: Chin-Chih Chang
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Many manufacturing systems suffer failures due to complex degradation processes and various environment conditions such as random shocks. Consider an operating system is subject to random shocks and works at random times for successive jobs. When successive jobs often result in production losses and performance deterioration, it would be better to do maintenance or replacement at a planned time. A preventive replacement (PR) policy is presented to replace the system before a failure occurs at a continuous time T. In such a policy, the failure characteristics of the system are designed as follows. Each job would cause a random amount of additive damage to the system, and the system fails when the cumulative damage has exceeded a failure threshold. Suppose that the deteriorating system suffers one of the two types of shocks with age-dependent probabilities: type-I (minor) shock is rectified by a minimal repair, or type-II (catastrophic) shock causes the system to fail. A corrective replacement (CR) is performed immediately when the system fails. In summary, a generalized maintenance model to scheduling replacement plan for an operating system is presented below. PR is carried out at time T, whereas CR is carried out when any type-II shock occurs and the total damage exceeded a failure level. The main objective is to determine the optimal continuous schedule time of preventive replacement through minimizing the mean cost rate function. The existence and uniqueness of optimal replacement policy are derived analytically. It can be seen that the present model is a generalization of the previous models, and the policy with preventive replacement outperforms the one without preventive replacement.Keywords: preventive replacement, working time, cumulative damage model, minimal repair, imperfect maintenance, optimization
Procedia PDF Downloads 363970 Assessing the Role of Human Mobility on Malaria Transmission in South Sudan
Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki
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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model
Procedia PDF Downloads 134969 Improvement of Process Competitiveness Using Intelligent Reference Models
Authors: Julio Macedo
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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics
Procedia PDF Downloads 87968 Valorization of Gypsum as Industrial Waste
Authors: Hasna Soli
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The main objective of this work is the extraction of sulfur from gypsum here is industrial waste. Indeed the sulfuric acid production, passing through the following process; melting sulfur, filtration of the liquid sulfur, sulfur combustion to produce SO₂, conversion of SO₂ to SO₃ and SO₃ absorption in water to produce H₂SO₄ product as waste CaSO₄ the anhydrous calcium sulfate. The main objectives of this work are improving the industrial practices and to find other ways to manage these solid wastes. It should also assess the consequences of treatment in terms of training and become byproducts. Firstly there will be a characterization of this type of waste by an X-ray diffraction; to obtain phase solid compositions and chemical analysis; gravimetrically and atomic absorption spectrometry or by ICP. The samples are mineralized in suitable acidic or basic solutions. The elements analyzed are CaO, Sulfide (SO₃), Al₂O₃, Fe₂O₃, MgO, SiO₂. Then an analysis by EDS energy dispersive spectrometry using an Oxford EDX probe and differential thermal and gravimetric analyzes. Gypsum’s valuation will be performed. Indeed, the CaSO₄ will be reused to produce sulfuric acid, which will be reintroduced into the production line. The second approach explored in this work is the thermal utilization of solid waste to remove sulfur as a dilute sulfuric acid solution.Keywords: environment, gypsum, sulfur, waste
Procedia PDF Downloads 295967 The Fabrication and Characterization of Hierarchical Carbon Nanotube/Carbon Fiber/High-Density Polyethylene Composites via Twin-Screw Extrusion
Authors: Chao Hu, Xinwen Liao, Qing-Hua Qin, Gang Wang
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The hierarchical carbon nanotube (CNT)/carbon fiber (CF)/high density polyethylene (HDPE) was fabricated via compound extrusion and injection molding, in which to author’s best knowledge CNT was employed as a nano-coatings on the surface of CF for the first time by spray coating technique. The CNT coatings relative to CF was set at 1 wt% and the CF content relative to the composites varied from 0 to 25 wt% to study the influence of CNT coatings and CF contents on the mechanical, thermal and morphological performance of this hierarchical composites. The results showed that with the rise of CF contents, the mechanical properties, including the tensile properties, flexural properties, and hardness of CNT/CF/HDPE composites, were effectively improved. Furthermore, the CNT-coated composites showed overall higher mechanical performance than the uncoated counterparts. It can be ascribed to the enhancement of interfacial bonding between the CF and HDPE via the incorporation of CNT, which was demonstrated by the scanning electron microscopy observation. Meanwhile, the differential scanning calorimetry data indicated that by the introduction of CNT and CF, the crystallization temperature and crystallinity of HDPE were affected while the melting temperature did not have an obvious alteration.Keywords: carbon fibers, carbon nanotubes, extrusion, high density polyethylene
Procedia PDF Downloads 138966 Harnessing the Benefits and Mitigating the Challenges of Neurosensitivity for Learners: A Mixed Methods Study
Authors: Kaaryn Cater
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People vary in how they perceive, process, and react to internal, external, social, and emotional environmental factors; some are more sensitive than others. Compassionate people have a highly reactive nervous system and are more impacted by positive and negative environmental conditions (Differential Susceptibility). Further, some sensitive individuals are disproportionately able to benefit from positive and supportive environments without necessarily suffering negative impacts in less supportive environments (Vantage Sensitivity). Environmental sensitivity is underpinned by physiological, genetic, and personality/temperamental factors, and the phenotypic expression of high sensitivity is Sensory Processing Sensitivity. The hallmarks of Sensory Processing Sensitivity are deep cognitive processing, emotional reactivity, high levels of empathy, noticing environmental subtleties, a tendency to observe new and novel situations, and a propensity to become overwhelmed when over-stimulated. Several educational advantages associated with high sensitivity include creativity, enhanced memory, divergent thinking, giftedness, and metacognitive monitoring. High sensitivity can also lead to some educational challenges, particularly managing multiple conflicting demands and negotiating low sensory thresholds. A mixed methods study was undertaken. In the first quantitative study, participants completed the Perceived Success in Study Survey (PSISS) and the Highly Sensitive Person Scale (HSPS-12). Inclusion criteria were current or previous postsecondary education experience. The survey was presented on social media, and snowball recruitment was employed (n=365). The Excel spreadsheets were uploaded to the statistical package for the social sciences (SPSS)26, and descriptive statistics found normal distribution. T-tests and analysis of variance (ANOVA) calculations found no difference in the responses of demographic groups, and Principal Components Analysis and the posthoc Tukey calculations identified positive associations between high sensitivity and three of the five PSISS factors. Further ANOVA calculations found positive associations between the PSISS and two of the three sensitivity subscales. This study included a response field to register interest in further research. Respondents who scored in the 70th percentile on the HSPS-12 were invited to participate in a semi-structured interview. Thirteen interviews were conducted remotely (12 female). Reflexive inductive thematic analysis was employed to analyse data, and a descriptive approach was employed to present data reflective of participant experience. The results of this study found that compassionate students prioritize work-life balance; employ a range of practical metacognitive study and self-care strategies; value independent learning; connect with learning that is meaningful; and are bothered by aspects of the physical learning environment, including lighting, noise, and indoor environmental pollutants. There is a dearth of research investigating sensitivity in the educational context, and these studies highlight the need to promote widespread education sector awareness of environmental sensitivity, and the need to include sensitivity in sector and institutional diversity and inclusion initiatives.Keywords: differential susceptibility, highly sensitive person, learning, neurosensitivity, sensory processing sensitivity, vantage sensitivity
Procedia PDF Downloads 65965 A Particle Swarm Optimal Control Method for DC Motor by Considering Energy Consumption
Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu
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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control
Procedia PDF Downloads 163964 Towards a Rigorous Analysis for a Supercritical Particulate Process
Authors: Yousef Bakhbakhi
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Crystallization with supercritical fluids (SCFs), as a developed technology to produce particles of micron and sub-micron size with narrow size distribution, has found appreciable importance as an environmentally friendly technology. Particle synthesis using SCFs can be achieved employing a number of special processes involving solvent and antisolvent mechanisms. In this study, the compressed antisolvent (PCA) process is utilized as a model to analyze the theoretical complexity of crystallization with supercritical fluids. The population balance approach has proven to be an effectual technique to simulate and predict the particle size and size distribution. The nucleation and growth mechanisms of the particles formation in the PCA process is investigated using the population balance equation, which describes the evolution of the particle through coalescence and breakup levels with time. The employed mathematical population balance model contains a set of the partial differential equation with algebraic constraints, which demands a rigorous numerical approach. The combined Collocation and Galerkin finite element method are proposed as a high-resolution technique to solve the dynamics of the PCA process.Keywords: particle formation, particle size and size distribution, PCA, supercritical carbon dioxide
Procedia PDF Downloads 197963 Utilization of a Composite of Oil Ash, Scoria, and Expanded Perlite with Polyethylene Glycol for Energy Storage Systems
Authors: Khaled Own Mohaisen, Md. Hasan Zahir, Salah U. Al-Dulaijan, Shamsad Ahmad, Mohammed Maslehuddin
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Shape-stabilized phase change materials (ss-PCMs) for energy storage systems were developed using perlite, scoria, and oil ash as a carrier, with polyethylene glycol (PEG) with a molecular weight of 6000 as phase change material (PCM). Physical mixing using simple impregnation of ethanol evaporation technique method was carried out to fabricate the form stabilized PCM. The fabricated PCMs prevent leakage, reduce the supercooling effect and minimize recalescence problems of the PCM. The differential scanning calorimetry (DSC) results show that perlite composite (ExPP) has the highest latent heat of melting and freezing values of (141.6 J/g and 143.7 J/g) respectively, compared with oil ash (OAP) and scoria (SCP) composites. Moreover, ExPP has the highest impregnation ratio, energy storage efficiency, and energy storage capacity compared with OAP and SCP. However, OAP and SCP have higher thermal conductivity values compared to ExPP composites which accelerate the thermal storage response in the composite. These results were confirmed with DSC, and the characteristic of the PCMs was investigated by using XRD and FE-SEM techniques.Keywords: expanded perlite, oil ash, scoria, energy storage material
Procedia PDF Downloads 90962 Carbonation and Mechanical Performance of Reactive Magnesia Based Formulations
Authors: Cise Unluer
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Reactive MgO hydrates to form brucite (Mg(OH)2, magnesium hydroxide), which can then react with CO2 and additional water to form a range of strength providing hydrated magnesium carbonates (HMCs) within cement-based formulations. The presented work focuses on the use of reactive MgO in a range of concrete mixes, where it carbonates by absorbing CO2 and gains strength accordingly. The main goal involves maximizing the amount of CO2 absorbed within construction products, thereby reducing the overall environmental impact of the designed formulations. Microstructural analyses including scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetry/differential thermal analysis (TG/DTA) are used in addition to porosity, permeability and unconfined compressive strength (UCS) testing to understand the performance mechanisms. XRD Reference Intensity Ratio (RIR), acid digestion and TG/DTA are utilized to quantify the amount of CO2 sequestered, with the goal of achieving 100% carbonation through careful mix design, leading to a range of carbon neutral products with high strengths. As a result, samples stronger than those containing Portland cement (PC) were produced, revealing the link between the mechanical performance and microstructural development of the developed formulations with the amount of CO2 sequestered.Keywords: carbonation, compressive strength, reactive MgO cement, sustainability
Procedia PDF Downloads 180961 Fatigue Life Estimation Using N-Code for Drive Shaft of Passenger Vehicle
Authors: Tae An Kim, Hyo Lim Kang, Hye Won Han, Seung Ho Han
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The drive shaft of passenger vehicle has its own function such as transmitting the engine torque from the gearbox and differential gears to the wheels. It must also compensate for all variations in angle or length resulting from manoeuvring and deflection for perfect synchronization between joints. Torsional fatigue failures occur frequently at the connection parts of the spline joints in the end of the drive shaft. In this study, the fatigue life of a drive shaft of passenger vehicle was estimated by using the finite element analysis. A commercial software of n-Code was applied under twisting load conditions, i.e. 0~134kgf•m and 0~188kgf•m, in which the shear strain range-fatigue life relationship considering Signed Shear method, Smith-Watson-Topper equation, Neuber-Hoffman Seeger method, size sensitivity factor and surface roughness effect was taken into account. The estimated fatigue life was verified by a twisting load test of the real drive shaft in a test rig. (Human Resource Training Project for Industry Matched R & D, KIAT, N036200004).Keywords: drive shaft, fatigue life estimation, passenger vehicle, shear strain range-fatigue life relationship, torsional fatigue failure
Procedia PDF Downloads 275960 Implementation of State-Space and Super-Element Techniques for the Modeling and Control of Smart Structures with Damping Characteristics
Authors: Nader Ghareeb, Rüdiger Schmidt
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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.Keywords: damping coefficients, finite element analysis, super-element, state-space model
Procedia PDF Downloads 320959 Investigating the performance of machine learning models on PM2.5 forecasts: A case study in the city of Thessaloniki
Authors: Alexandros Pournaras, Anastasia Papadopoulou, Serafim Kontos, Anastasios Karakostas
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The air quality of modern cities is an important concern, as poor air quality contributes to human health and environmental issues. Reliable air quality forecasting has, thus, gained scientific and governmental attention as an essential tool that enables authorities to take proactive measures for public safety. In this study, the potential of Machine Learning (ML) models to forecast PM2.5 at local scale is investigated in the city of Thessaloniki, the second largest city in Greece, which has been struggling with the persistent issue of air pollution. ML models, with proven ability to address timeseries forecasting, are employed to predict the PM2.5 concentrations and the respective Air Quality Index 5-days ahead by learning from daily historical air quality and meteorological data from 2014 to 2016 and gathered from two stations with different land use characteristics in the urban fabric of Thessaloniki. The performance of the ML models on PM2.5 concentrations is evaluated with common statistical methods, such as R squared (r²) and Root Mean Squared Error (RMSE), utilizing a portion of the stations’ measurements as test set. A multi-categorical evaluation is utilized for the assessment of their performance on respective AQIs. Several conclusions were made from the experiments conducted. Experimenting on MLs’ configuration revealed a moderate effect of various parameters and training schemas on the model’s predictions. Their performance of all these models were found to produce satisfactory results on PM2.5 concentrations. In addition, their application on untrained stations showed that these models can perform well, indicating a generalized behavior. Moreover, their performance on AQI was even better, showing that the MLs can be used as predictors for AQI, which is the direct information provided to the general public.Keywords: Air Quality, AQ Forecasting, AQI, Machine Learning, PM2.5
Procedia PDF Downloads 77958 Causes for the Precession of the Perihelion in the Planetary Orbits
Authors: Kwan U. Kim, Jin Sim, Ryong Jin Jang, Sung Duk Kim
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It is Leverrier that discovered the precession of the perihelion in the planetary orbits for the first time in the world, while it is Einstein that explained the astronomical phenomenom for the first time in the world. The amount of the precession of the perihelion for Einstein’s theory of gravitation has been explained by means of the inverse fourth power force(inverse third power potential) introduced totheory of gravitation through Schwarzschild metric However, the methodology has a serious shortcoming that it is impossible to explain the cause for the precession of the perihelion in the planetary orbits. According to our study, without taking the cause for the precession of the perihelion, 6 methods can explain the amount of the precession of the perihelion discovered by Leverrier. Therefore, the problem of what caused the perihelion to precess in the planetary orbits must be solved for physics because it is a profound scientific and technological problem for a basic experiment in construction of relativistic theory of gravitation. The scientific solution to the problem proved that Einstein’s explanation for the planetary orbits is a magic made by the numerical expressions obtained from fictitious gravitation introduced to theory of gravitation and wrong definition of proper time The problem of the precession of the perihelion seems solved already by means of general theory of relativity, but, in essence, the cause for the astronomical phenomenon has not been successfully explained for astronomy yet. The right solution to the problem comes from generalized theory of gravitation. Therefore, in this paper, it has been shown that by means of Schwarzschild field and the physical quantities of relativistic Lagrangian redflected in it, fictitious gravitation is not the main factor which can cause the perihelion to precess in the planetary orbits. In addition to it, it has been shown that the main factor which can cause the perihelion to precess in the planetary orbits is the inverse third power force existing really in the relativistic region in the Solar system.Keywords: inverse third power force, precession of the perihelion, fictitious gravitation, planetary orbits
Procedia PDF Downloads 12957 Applying the Crystal Model to Different Nuclear Systems
Authors: A. Amar
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The angular distributions of the nuclear systems under consideration have been analyzed in the framework of the optical model (OM), where the real part was taken in the crystal model form. A crystal model (CM) has been applied to deuteron elastically scattered by ⁶,⁷Li and ⁹Be. A crystal model (CM) + distorted-wave Born approximation (DWBA) + dynamic polarization potential (DPP) potential has been applied to deuteron elastically scattered by ⁶,⁷Li and 9Be. Also, a crystal model has been applied to ⁶Li elastically scattered by ¹⁶O and ²⁸Sn in addition to the ⁷Li+⁷Li system and the ¹²C(alpha,⁸Be) ⁸Be reaction. The continuum-discretized coupled-channels (CDCC) method has been applied to the ⁷Li+⁷Li system and agreement between the crystal model and the continuum-discretized coupled-channels (CDCC) method has been observed. In general, the models succeeded in reproducing the differential cross sections at the full angular range and for all the energies under consideration.Keywords: optical model (OM), crystal model (CM), distorted-wave born approximation (DWBA), dynamic polarization potential (DPP), the continuum-discretized coupled-channels (CDCC) method, and deuteron elastically scattered by ⁶, ⁷Li and ⁹Be
Procedia PDF Downloads 79956 Financing Innovation: Differences across National Innovation Systems
Authors: Núria Arimany Serrat, Xavier Ferràs Hernández, Petra A. Nylund, Eric Viardot
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Innovation is an increasingly important antecedent to firm competitiveness and growth. Successful innovation, however, requires a significant financial commitment and the means of financing accessible to the firm may affect its ability to innovate. The access to equity financing such as venture capital has been connected to innovativeness for young firms. For established enterprises, debt financing of innovation may be a more realistic option. Continuous innovation and growth would otherwise require a constant increase of equity. We, therefore, investigate the relation between debt financing and innovation for large firms and hypothesize that those firms that carry more debt will be more innovative. The need for debt financing of innovation may be reduced for very profitable firms, which can finance innovation with cash flow. We thus hypothesize a moderating effect of profitability on the relationship between debt financing and innovation. We carry out an empirical investigation using a longitudinal data set including 167 large European firms over five years, resulting in 835 firm years. We apply generalized least squares (GLS) regression with fixed firm effects to control for firm heterogeneity. The findings support our hypotheses and we conclude that access to debt finding is an important antecedent of innovation, with profitability as a moderating factor. The results do however differ across national innovation systems and we find a strong relationship for British, Dutch, French, and Italian firms but not for German and Spanish entities. We discuss differences in the national systems of innovation and financing which contextualize the variations in the findings and thus make a nuanced contribution to the research in innovation financing. The cross-country differences calls for differentiated advice to managers, institutions, and researchers depending on the national context.Keywords: innovation, R&D, national innovation systems, financing
Procedia PDF Downloads 531955 Modelling of Pipe Jacked Twin Tunnels in a Very Soft Clay
Authors: Hojjat Mohammadi, Randall Divito, Gary J. E. Kramer
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Tunnelling and pipe jacking in very soft soils (fat clays), even with an Earth Pressure Balance tunnel boring machine (EPBM), can cause large ground displacements. In this study, the short-term and long-term ground and tunnel response is predicted for twin, pipe-jacked EPBM 3 meter diameter tunnels with a narrow pillar width. Initial modelling indicated complete closure of the annulus gap at the tail shield onto the centrifugally cast, glass-fiber-reinforced, polymer mortar jacking pipe (FRP). Numerical modelling was employed to simulate the excavation and support installation sequence, examine the ground response during excavation, confirm the adequacy of the pillar width and check the structural adequacy of the installed pipe. In the numerical models, Mohr-Coulomb constitutive model with the effect of unloading was adopted for the fat clays, while for the bedrock layer, the generalized Hoek-Brown was employed. The numerical models considered explicit excavation sequences and different levels of ground convergence prior to support installation. The well-studied excavation sequences made the analysis possible for this study on a very soft clay, otherwise, obtaining the convergency in the numerical analysis would be impossible. The predicted results indicate that the ground displacements around the tunnel and its effect on the pipe would be acceptable despite predictions of large zones of plastic behaviour around the tunnels and within the entire pillar between them due to excavation-induced ground movements.Keywords: finite element modeling (FEM), pipe-jacked tunneling, very soft clay, EPBM
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