Search results for: hill type muscle model

Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

Procedia PDF Downloads 336

Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

Procedia PDF Downloads 201

Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

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Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

Procedia PDF Downloads 199

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 80

Authors: Pouya Molana, Zeinab Alimohammadi

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Determining wind wave characteristics is essential for implementing projects related to Coastal and Marine engineering such as designing coastal and marine structures, estimating sediment transport rates and coastal erosion rates in order to predict significant wave height (H_s), this study applies the third generation spectral wave model, Mike 21 SW, along with CEM model. For SW model calibration and verification, two data sets of meteorology and wave spectroscopy are used. The model was exposed to time-varying wind power and the results showed that difference ratio mean, standard deviation of difference ratio and correlation coefficient in SW model for H_s parameter are 1.102, 0.279 and 0.983, respectively. Whereas, the difference ratio mean, standard deviation and correlation coefficient in The Choice Experiment Method (CEM) for the same parameter are 0.869, 1.317 and 0.8359, respectively. Comparing these expected results it is revealed that the Choice Experiment Method CEM has more errors in comparison to MIKE 21 SW third generation spectral wave model and higher correlation coefficient does not necessarily mean higher accuracy.

Keywords: MIKE 21 SW, CEM method, significant wave height, difference ratio

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Authors: Sadık Ata, Kevser Dincer

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In this study, performance of proton exchange membrane (PEM) fuel cell was experimentally investigated and modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Coating on the anode side of the PEM fuel cell was accomplished with the spin method by using Yttria-stabilized zirconia (YSZ). Input parameters voltage density (V/cm2), and current density (A/cm2), temperature (°C), time (s); output parameter power density (W/cm2) were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of performance of PEM fuel cell.

Keywords: proton exchange membrane (PEM), fuel cell, rule-based Mamdani-type fuzzy (RMBTF) modeling, yttria-stabilized zirconia (YSZ)

Procedia PDF Downloads 362

Authors: Kazunori Takai, Weng Kaiwei, Sadao Araki, Hideki Yamamoto

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HFC and PFC gases have been commonly and widely used as refrigerant of air conditioner and as etching agent of semiconductor manufacturing process, because of their higher heat of vaporization and chemical stability. On the other hand, HFCs and PFCs gases have the high global warming effect on the earth. Therefore, we have to be decomposed these gases emitted from chemical apparatus like as refrigerator. Until now, disposal of these gases were carried out by using combustion method like as Rotary kiln treatment mainly. However, this treatment needs extremely high temperature over 1000 °C. In the recent year, in order to reduce the energy consumption, a hydrolytic decomposition method using catalyst and plasma decomposition treatment have been attracted much attention as a new disposal treatment. However, the decomposition of fluorine-containing gases under the wet condition is not able to avoid the generation of hydrofluoric acid. Hydrofluoric acid is corrosive gas and it deteriorates catalysts in the decomposition process. Moreover, an additional process for the neutralization of hydrofluoric acid is also indispensable. In this study, the decomposition of C2F6 using zeolite and zeolite/CaO mixture as reactant was evaluated in the dry condition at 923 K. The effect of the chemical structure of zeolite on the decomposition reaction was confirmed by using H-Y, H-Beta, H-MOR and H-ZSM-5. The formation of CaF2 in zeolite/CaO mixtures after the decomposition reaction was confirmed by XRD measurements. The decomposition of C2F6 using zeolite as reactant showed the closely similar behaviors regardless the type of zeolite (MOR, Y, ZSM-5, Beta type). There was no difference of XRD patterns of each zeolite before and after reaction. On the other hand, the difference in the C2F6 decomposition for each zeolite/CaO mixtures was observed. These results suggested that the rate-determining process for the C2F6 decomposition on zeolite alone is the removal of fluorine from reactive site. In other words, the C2F6 decomposition for the zeolite/CaO improved compared with that for the zeolite alone by the removal of the fluorite from reactive site. HMOR/CaO showed 100% of the decomposition for 3.5 h and significantly improved from zeolite alone. On the other hand, Y type zeolite showed no improvement, that is, the almost same value of Y type zeolite alone. The descending order of C2F6 decomposition was MOR, ZSM-5, beta and Y type zeolite. This order is similar to the acid strength characterized by NH3-TPD. Hence, it is considered that the C-F bond cleavage is closely related to the acid strength.

Keywords: hexafluoroethane, zeolite, calcium oxide, decomposition

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Authors: Sibel Celik, Hüseyin Ergin

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The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

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Authors: Moumita Sit, Chaitali Ray

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The present article deals with the free vibration analysis of hybrid laminated composite structures with initial stresses developed in the laminates. Generally initial stresses may be developed in the laminates by temperature and moisture effect. In this study, an eight noded isoparametric plate bending element has been used for the finite element analysis of composite plates. A numerical model has been developed to assess the geometric nonlinear response of composite plates based on higher order shear deformation theory (HSDT) considering the Green–Lagrange type nonlinearity. A computer code based on finite element method (FEM) has also been developed in MATLAB to perform the numerical calculations. To validate the accuracy of the proposed numerical model, the results obtained from the present study are compared with those available in published literature. Effects of the side to thickness ratio, different boundary conditions and initial stresses on the natural frequency of composite plates have been studied. The free vibration analysis of a hollow stiffened hybrid laminated panel has also been carried out considering initial stresses and presented as case study.

Keywords: geometric nonlinearity, higher order shear deformation theory (HSDT), hybrid composite laminate, the initial stress

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Authors: Ashley Wei-Ting Wang, Wen-Yau Hsu

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Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

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Authors: Ahmad Odeh, Ahmad Jrade

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Energy assessment is an evidently significant factor when evaluating the sustainability of structures especially at the early design stage. Today design practices revolve around the selection of material that reduces the operational energy and yet meets their displinary need. Operational energy represents a substantial part of the building lifecycle energy usage but the fact remains that embodied energy is an important aspect unaccounted for in the carbon footprint. At the moment, little or no consideration is given to embodied energy mainly due to the complexity of calculation and the various factors involved. The equipment used, the fuel needed, and electricity required for each material vary with location and thus the embodied energy will differ for each project. Moreover, the method and the technique used in manufacturing, transporting and putting in place will have a significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at helping designers select the construction materials based on their embodied energy. Moreover, this paper presents a systematic approach that uses an efficient method of calculation and ultimately provides new insight into construction material selection. The model is developed in a BIM environment targeting the quantification of embodied energy for construction materials through the three main stages of their life: manufacturing, transportation and placement. The model contains three major databases each of which contains a set of the most commonly used construction materials. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by tools and cranes needed to place an item in its intended location. The model provides designers with sets of all available construction materials and their associated embodied energies to use for the selection during the design process. Through geospatial data and dimensional material analysis, the model will also be able to automatically calculate the distance between the factories and the construction site. To remain within the sustainability criteria set by LEED, a final database is created and used to calculate the overall construction cost based on R.M.S. means cost data and then automatically recalculate the costs for any modifications. Design criteria including both operational and embodied energies will cause designers to revaluate the current material selection for cost, energy, and most importantly sustainability.

Keywords: building information modelling, energy, life cycle analysis, sustainablity

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Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

Procedia PDF Downloads 421

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Kwounghee Choi

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Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

Procedia PDF Downloads 485

Authors: Yongseok Kim, Jeong-Min Lee, Hyunwoo Song, Junghan Yun, Jungin Byun, Jae-Mean Koo, Chang-Sung Seok

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Thermal barrier coating(TBC) is applied for gas turbine components to protect the components from extremely high temperature condition. Since metallic substrate cannot endure such severe condition of gas turbines, delamination of TBC can cause failure of the system. Thus, delamination life of TBC is one of the most important issues for designing the components operating at high temperature condition. Thermal stress caused by thermally grown oxide(TGO) layer is known as one of the major failure mechanisms of TBC. Thermal stress by TGO mainly occurs at the interface between TGO layer and ceramic top coat layer, and it is strongly influenced by the thickness and shape of TGO layer. In this study, Isothermal oxidation is conducted on coin-type TBC specimens prepared by APS(air plasma spray) method. After the isothermal oxidation at various temperature and time condition, the thickness and shape(rumpling shape) of the TGO is investigated, and the test data is processed by numerical analysis. Finally, the test data is arranged into a mathematical prediction model with two variables(temperature and exposure time) which can predict the thickness and rumpling shape of TGO.

Keywords: thermal barrier coating, thermally grown oxide, thermal stress, isothermal oxidation, numerical analysis

Procedia PDF Downloads 342

Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

Procedia PDF Downloads 187

Authors: Davide Gotti, Milan Prodanovic, Sergio Pinilla, David Muñoz-Torrero

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Since its proposal, the Doyle-Fuller-Newman (DFN) lithium-ion battery model has gained popularity in the electrochemical field. In fact, this model provides the user with theoretical support for designing the lithium-ion battery parameters, such as the material particle or the diffusion coefficient adjustment direction. However, the model is mathematically complex as it is composed of several partial differential equations (PDEs) such as Fick’s law of diffusion, the MacInnes and Ohm’s equations, among other phenomena. Thus, to efficiently use the model in a time-domain simulation environment, the selection of the discretization technique is of a pivotal importance. There are several numerical methods available in the literature that can be used to carry out this task. In this study, a comparison between the explicit Euler, Crank-Nicolson, and Chebyshev discretization methods is proposed. These three methods are compared in terms of accuracy, stability, and computational times. Firstly, the explicit Euler discretization technique is analyzed. This method is straightforward to implement and is computationally fast. In this work, the accuracy of the method and its stability properties are shown for the electrolyte diffusion partial differential equation. Subsequently, the Crank-Nicolson method is considered. It represents a combination of the implicit and explicit Euler methods that has the advantage of being of the second order in time and is intrinsically stable, thus overcoming the disadvantages of the simpler Euler explicit method. As shown in the full paper, the Crank-Nicolson method provides accurate results when applied to the DFN model. Its stability does not depend on the integration time step, thus it is feasible for both short- and long-term tests. This last remark is particularly important as this discretization technique would allow the user to implement parameter estimation and optimization techniques such as system or genetic parameter identification methods using this model. Finally, the Chebyshev discretization technique is implemented in the DFN model. This discretization method features swift convergence properties and, as other spectral methods used to solve differential equations, achieves the same accuracy with a smaller number of discretization nodes. However, as shown in the literature, these methods are not suitable for handling sharp gradients, which are common during the first instants of the charge and discharge phases of the battery. The numerical results obtained and presented in this study aim to provide the guidelines on how to select the adequate discretization technique for the DFN model according to the type of application to be performed, highlighting the pros and cons of the three methods. Specifically, the non-eligibility of the simple Euler method for longterm tests will be presented. Afterwards, the Crank-Nicolson and the Chebyshev discretization methods will be compared in terms of accuracy and computational times under a wide range of battery operating scenarios. These include both long-term simulations for aging tests, and short- and mid-term battery charge/discharge cycles, typically relevant in battery applications like grid primary frequency and inertia control and electrical vehicle breaking and acceleration.

Keywords: Doyle-Fuller-Newman battery model, partial differential equations, discretization, numerical methods

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Authors: M. N. A. Abdullah, Pritha Roy, R. R. Shil, D. R. Sarker

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Alpha-nucleus interaction is obscured because it produces enhanced cross-sections at large scattering angles known as anomaly in large angle scattering (ALAS). ALAS is prominent in the elastic scattering of α-particles as well as in non-elastic processes involving α-particles for incident energies up to 50 MeV and for targets of mass A ≤ 50. The Woods-Saxon type of optical model potential fails to describe the processes in a consistent manner. Folded potential is a good candidate and often used to construct the potential which is derived from the microscopic as well as semi-microscopic folding calculations. The present work reports the analyses of the elastic scattering of α-particles from ²⁴Mg and ²⁸Si at Eα=22-100 MeV and 14.4-120 MeV incident energies respectively in terms of the modified single-folded (MSF) potential. To derive the MSF potential, we take the view that the nucleons in the target nuclei ²⁴Mg and ²⁸Si are primarily in α-like clusters and the rest of the time in unclustered nucleonic configuration. The MSF potential, found in this study, does not need any renormalization over the whole range of incident α energies, and the renormalization factor has been found to be exactly 1 for both the targets. The best-fit parameters yield 4Aα = 21 and AN = 3 for α-²⁴Mg potential, and 4Aα = 26 and AN = 2 for α-²⁸Si potential in time-average pictures. The root-mean-square radii of both ²⁴Mg and ²⁸Si are also deduced, and the results obtained from this work agree well with the outcomes of other studies.

Keywords: elastic scattering, optical model, folded potential, renormalization

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Authors: Tareq Oshan

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Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

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Authors: Wipharat Saimo, Benjawan Thumthanaruk, Panida Banjongsinsiri, Nowwapan Noojuy

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Thai northern style sausage (sai-ou) is originally cuisine made of chili paste, pork, and lard. It always serves with curry paste, vegetable, and rice. The meat and lard ingredients used can be substituted by Shiitake mushroom (Lentinus edodes) and King oyster (Pleurotus eryngii) mushroom (50:50 w/w) which is suitable for all people, especially vegetarians. However, the texture of mushroom type sai-ou had no homogenous texture due to no adhesiveness property of mushroom. Therefore, this research aimed to study the ratio of hydrocolloids (konjac flour (0-100%), konjac gel (0-100%) and Citri-fi®100 FG (0-2%)) on the physicochemical properties mushroom type sai-ou. The mixture design was applied by using Minitab 16 software. Nine formula were designed for the test. The values of moisture content and water activity of nine formula were ranged from 66.25-72.17% and 0.96-0.97. The pH values were 5.44-5.89. The optimal ratio of konjac flour, konjac gel and Citri-fi®100 FG (74.75:24.75:0.5 (w/w)) yielded the highest texture profiles (hardness, springiness, cohesiveness, gumminess and chewiness) as well as color parameters (L*, a* and b*). Sensory results showed had higher acceptability scores in term of overall liking with the level of ‘like moderately’ (5.9 on 7 pointed scale). The mushroom type sai-ou sausage could be an alternative food for health-conscious consumers.

Keywords: Citri-fi® 100 FG, konjac flour, konjac gel, Thai northern style sausages

Procedia PDF Downloads 228

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Arian Amirnia, Atena Taheri, Mohammadreza Arabi, Mahmud Fotuhi-Firuzabad

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Ferroresonance effects cause overvoltage in medium voltage transformers and isolators used in electrical networks. Ferroresonance effects are nonlinear and occur between the network capacitor and the nonlinear inductance of the voltage transformer during saturation. This phenomenon is unwanted for transformers since it causes overheating, introduction of high dynamic forces in primary coils, and rise of voltage in primary coils for the voltage transformer. Furthermore, it results in electrical and thermal failure of the transformer. Expansion of distribution lines, design of the transformer in smaller sizes, and the increase of harmonics in distribution networks result in an increase of ferroresonance. There is limited literature available to improve the effects of ferroresonance; therefore, optimizing its effects for voltage transformers is of great importance. In this study, comprehensive modeling of a medium voltage block-type voltage transformer is performed. In addition, a recent model is proposed to improve the performance of voltage transformers during the occurrence of ferroresonance using damping oscillations. Also, transformer design optimization is presented in this study to show further improvements in the performance of the voltage transformer. The recently proposed model is experimentally tested and verified on a medium voltage transformer in the laboratory, and simulation results show a large reduction of the effects of ferroresonance.

Keywords: optimization, voltage transformer, ferroresonance, modeling, damper

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Alvaro Jose Cordova, Hsuan Teh Hu

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The use of concrete masonry constructions in developing countries has become very frequent, especially for domestic purpose. Most of them with asymmetric wall configurations in plan resulting in significant torsional actions when subjected to seismic loads. The study consisted on the finding of a material model for hollow unreinforced concrete masonry and a validation with experimental data found in literature. Numerical simulations were performed to 20 buildings with variations in wall distributions and heights. Results were analyzed by inspection and with a non-linear static method. The findings revealed that eccentricities as well as structure rigidities have a strong influence on the overall response of concrete masonry buildings. In addition, slab rotations depicted more accurate information about the torsional behavior than maximum versus average displacement ratios. The failure modes in low buildings were characterized by high tensile strains in the first floor. Whereas in tall buildings these strains were lowered significantly by higher compression stresses due to a higher self-weight. These tall buildings developed multiple plastic hinges along the height. Finally, the non-linear static analysis exposed a brittle response for all masonry assemblies. This type of behavior is undesired in any construction and the need for a material model for reinforced masonry is pointed out.

Keywords: concrete damaged plasticity, concrete masonry, macro-modeling, nonlinear static analysis, torsional capacity

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Authors: K. M. Anusha, R. Krishnaveni

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Crossing a decade of the 21st century, the paradigm of human resources can be seen evolving with the strategic gene induced into it. There seems to be a radical shift descending as the corporate sector calls on its HR team to become strategic rather than administrative. This transferal eventually requires the metrics employed by these HR teams not to be just operationally reactive but to be aligned to an evidence-based strategic thinking. Realizing the growing need for a prescriptive metric model for effective HR analytics, this study has designed a conceptual framework for a basic metric model that can assist IT-HRM professionals to transition to a practice of evidence-based decision-making to enhance organizational performance.

Keywords: metric model, evidence based HR, HR analytics, strategic HR practices, IT sector

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Authors: Jinhyun Ryu, Chengliang Xie, Nal Ae Yoon, Dong Hoon Lee, Gu Seob Roh, Hyun Joon Kim, Gyeong Jae Cho, Wan Sung Choi, Sang Soo Kang

Abstract:

Type 2 diabetes is a heterogeneous group of metabolic disorders featured by a deficit in or loss of insulin activity to maintain normal glucose homeostasis. Mainly, it results from the compromised insulin secretion and/or reduced insulin activity. The frequency of type 2 diabetes (T2D) has been increased rapidly in recent decades with the increase in the trend of obesity due to life style and food habit. Obesity is considered to be the primary risk factor for the development of insulin resistance and thereby developing T2D. Traditionally naturally occurring fruits, vegetables etc. are being used to treat many pathogenic conditions. In this study, we tried to find out the effect of a popularly used vegetable in Bangladesh and several other Asian countries, ‘bitter melon’ on high fat diet induced T2D. To investigate the effect, we used 70% ethanol extract of bitter melon (BME) as dietary supplement with chow. BME was found to attenuate the high fat diet (HFD) induced body weight and total fat mass significantly. We also observed that BME reduced the insulin resistance induced by HFD effectively. Furthermore, dietary supplementation of BME was highly effective in increasing insulin sensitivity, and reducing the hepatic fat and obesity. These results indicate that BME could be effective to attenuate T2D and could be a preventive measure against T2D.

Keywords: bitter melon, obesity, type 2 diabetes, high fat diet

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Authors: Nikolaos Reppas, Yilin Gui

Abstract:

A dual-porosity finite element-code will be presented for the stability analysis of the wellbore during CO₂ injection. An elastoplastic damage response will be considered to the model. The Finite Element Method (FEM) will be validated using experimental results from literature or from experiments that are planned to be undertaken at Newcastle University. The main target of the research paper is to present a constitutive model that can help industries to safely store CO₂ in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elastoplastic damage Thermo-Hydraulic-Mechanical (THM) model will determine the pressure and temperature of the injected CO₂ as well as the size of the radius of the wellbore that can make the Carbon Capture and Storage (CCS) procedure more efficient.

Keywords: carbon capture and storage, Wellbore stability, elastoplastic damage response for rock, constitutive THM model, fully coupled thermo-hydraulic-mechanical model

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Authors: N. Guo, C. Xu, Z. C. Yang

Abstract:

In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: Osagbai Joshua Eriki, Ngozi Agunwamba, Alice Hill, Lorna Almond, Maniya Duffy, Devashini Naidoo, David Ho, Raman Deo

Abstract:

Aims: To evaluate the baseline eating pattern in a psychiatric hospital through quantifying purchases of food and drink items at the hospital shop and to implement a traffic light healthy eating labeling system. Method: A electronic till with reporting capabilities was purchased. A two-week period of baseline data collection was conducted. Thereafter, a system for labeling items based on the nutritional value of the food items at the hospital shop was implemented. Green labeling represented the items with the lowest calories and red the most. Further data was collated on the number and types of items purchased by patients according to the category, and the initial effectiveness of the system was evaluated. Result: Despite the implementation of the traffic light system, the red category had the highest number of items purchased by patients, highlighting the importance of promoting healthy eating choices. However, the study also showed that the system was effective in promoting healthy options, as the number of items purchased from the green category increased during the study period. Conclusion: The implementation of a traffic light labeling system for items sold at the hospital shop offers a promising approach to promoting healthy eating habits and choices. This is likely to contribute to a toolkit of measures when considering the multifactorial challenges that obesity and weight issues pose for long-stay psychiatric inpatients

Keywords: mental health, nutrition, food, healthy

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Authors: Jma Hannan, Prawej Ansari, Yasser H. A. Abdel-Wahab, Peter R. Flatt

Abstract:

Spirulina platensis (SP, Blue-green algae) have been accepted as a supplement for the treatment of pre and post-diabetes. The present study investigated the effects of butanol fraction from ethanol extract of S. platensis on insulin release from BRIN BD11 cells, isolated mouse islets, and perfused rat pancreas, as well as glucose homeostasis in type 2 diabetic rats and their molecular pathways. In a dose-dependent manner, S. platensis increased insulin release from mouse islets and pancreatic β-cells. The extract also elevated insulin release in perfused rat pancreas. Glucose, isobutylmethylxanthine, tolbutamide, and a depolarizing concentration of KCl significantly potentiated insulin release from BRIN BD11 cells. The effect of diazoxide and verapamil, as well as the absence of extracellular Ca2+ showed a reduction in insulin secretion. When administered orally together with glucose (2.5g/kg bw), S. platensis extract improved fasting and postprandial blood glucose in type 2 diabetes. These data suggest that the anti-diabetic activity of S. platensis is partly mediated by insulin secretion via the KATP channel-dependent pathway/the intracellular cAMP pathway.

Keywords: Insulin, glucose, S. platensis, type 2 diabetes, medicinal plants

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Authors: S. J. Shahidzadeh Tabatabaei, A. M. Fattahi

Abstract:

Modal analysis of an FGM plate containing the ceramic phase of Al2O3 and metal phase of stainless steel 304 was performed using ABAQUS, with the assumptions that the material has an elastic mechanical behavior and its Young modulus and density are varying in thickness direction. For this purpose, a subroutine was written in FORTRAN and linked with ABAQUS. First, a simulation was performed in accordance to other researcher’s model, and then after comparing the obtained results, the accuracy of the present study was verified. The obtained results for natural frequency and mode shapes indicate good performance of user-written subroutine as well as FEM model used in present study. After verification of obtained results, the effect of clamping condition and the material type (i.e. the parameter n) was investigated. In this respect, finite element analysis was carried out in fully clamped condition for different values of n. The results indicate that the natural frequency decreases with increase of n, since with increase of n, the amount of ceramic phase in FGM plate decreases, while the amount of metal phase increases, leading to decrease of the plate stiffness and hence, natural frequency, as the Young modulus of Al2O3 is equal to 380 GPa and the Young modulus of stainless steel 304 is equal to 207 GPa.

Keywords: FGM plates, modal analysis, natural frequency, finite element method

Procedia PDF Downloads 342