Search results for: experimental model

Authors: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

Procedia PDF Downloads 136

Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

Procedia PDF Downloads 149

Authors: Roly B. Bayo-Ang

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This research investigated the effect of science intervention modules in Filipino and in English on mastery of content (MOC) and conceptual understanding of Grade 9 students in Chemistry. Analysis of content mastery scores revealed a significant difference in the mean scores of the control and experimental group, t (46) = -2.14, p < 0.05. The experimental group achieved an MPS of > 75% in three of the five lessons while none in the control group. Analysis of the pretest and posttest scores of the control group in the test for conceptual understanding (TCU) showed no significant difference, t (18), =1.44, p > 0.05, while pretest and posttest scores of experimental group revealed significant difference, t (29) = -5.08, p < 0.05. Comparison of posttest scores of control and experimental group revealed no significant difference t (42) =1.67, p > 0.05. Performance in TCU and MOC of the control group are not significantly correlated, r (17) =.307, p > 0.05; but significantly correlated, r (27) =.571, p < 0.05, for the experimental group. The intervention module in Filipino promotes conceptual understanding and mastery of content than the module in English.

Keywords: action research, conceptual understanding, mastery of content, Filipino module

Procedia PDF Downloads 336

Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Boubaker Fezzani, Ridha Ben Cheikh, Tarek Rouissi

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In this work the original ADM1, implemented in the simulation software package MATLAB/Simulink, was modified and adapted and applied to reproduce the experimental results of the mesophilic anaerobic digestion of Esperto paper industry wastewater in a batch digester. The data set from lab-scale experiment runs were used to calibrate and validate the model. The simulations’ results indicated that the modified ADM1 was able to predict reasonably well the steady state results of gas flows, methane and carbon dioxide contents, pH and total volatile fatty acids (TVFA) observed with all influents concentrations.

Keywords: anaerobic digestion, mathematical modelling, Simulation, ADM1, batch digester, esparto paper industry effluent, mesophilic temperature

Procedia PDF Downloads 405

Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

Procedia PDF Downloads 521

Authors: Hamid Chaikhy, Mouna Essaadi, Aziz El Afia

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This paper presents an experimental implementation of a new direct torque control strategy of induction machine called twelve sectors direct torque control strategy (12_DTC) using DSPACE TMS 320F2812.The aim of this work is to give an experimental performance analysis of 12_DTC in term of torque, currents distortions and stator flux, to validate simulation results obtained in previous works.

Keywords: 12_DTC, DSPACE TMS 320F2812 torque, stator flux, currents distortions, experimental performance analysis

Procedia PDF Downloads 393

Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Nisha Deopa, A. S. Rao

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Lithium Lead Alumino Borate (LiPbAlB) glasses doped with different Dy3+ ions concentration were synthesized to investigate their viability in solid state lighting (SSL) technology by melt quenching techniques. From the absorption spectra, bonding parameters (ð) were investigated to study the nature of bonding between Dy3+ ions and its surrounding ligands. Judd-Ofelt (J-O) intensity parameters (Ω = 2, 4, 6), estimated from the experimental oscillator strengths (fex) of the absorption spectral features were used to evaluate the radiative parameters of different transition levels. From the decay curves, experimental lifetime (τex) were measured and coupled with the radiative lifetime to evaluate the quantum efficiency of the as-prepared glasses. As Dy3+ ions concentration increases, decay profile changes from exponential to non-exponential through energy transfer mechanism (ETM) in turn decreasing experimental lifetime. In order to investigate the nature of ETM, non-exponential decay curves were fitted to Inkuti–Hirayama (I-H) model which further confirms dipole-dipole interaction. Among all the emission transition, 4F9/2  6H15/2 transition (483 nm) is best suitable for lasing potentialities. By exciting titled glasses in n-UV to blue regions, CIE chromaticity coordinates and Correlated Color Temperature (CCT) were calculated to understand their capability in cool white light generation. From the evaluated radiative parameters, CIE co-ordinates, quantum efficiency and confocal images it was observed that glass B (0.5 mol%) is a potential candidate for developing w-LEDs and lasers.

Keywords: energy transfer, glasses, J-O parameters, photoluminescence

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

Procedia PDF Downloads 152

Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Ella Quigley, Kevin Tinkham

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Fire performance is a crucial aspect to consider when designing cladding products, and testing this performance is extremely expensive. Appropriate use of numerical simulation of fire performance has the potential to reduce the total number of fire tests required when designing a product by eliminating poor-performing design ideas early in the design phase. Due to the complexity of fire and the large spectrum of failures it can cause, multi-disciplinary models are needed to capture the complex fire behavior and its structural effects on its surroundings. Working alongside Tata Steel U.K., the authors have focused on completing a coupled CFD-FEA simulation model suited to test Polyisocyanurate (PIR) based sandwich panel products to gain confidence before costly experimental standards testing. The sandwich panels are part of a thermally insulating façade system primarily for large non-domestic buildings. The work presented in this paper compares two coupling methodologies of a replicated physical experimental standards test LPS 1181-1, carried out by Tata Steel U.K. The two coupling methodologies that are considered within this research are; one-way and two-way. A one-way coupled analysis consists of importing thermal data from the CFD solver into the FEA solver. A two-way coupling analysis consists of continuously importing the updated changes in thermal data, due to the fire's behavior, to the FEA solver throughout the simulation. Likewise, the mechanical changes will also be updated back to the CFD solver to include geometric changes within the solution. For CFD calculations, a solver called Fire Dynamic Simulator (FDS) has been chosen due to its adapted numerical scheme to focus solely on fire problems. Validation of FDS applicability has been achieved in past benchmark cases. In addition, an FEA solver called ABAQUS has been chosen to model the structural response to the fire due to its crushable foam plasticity model, which can accurately model the compressibility of PIR foam. An open-source code called FDS-2-ABAQUS is used to couple the two solvers together, using several python modules to complete the process, including failure checks. The coupling methodologies and experimental data acquired from Tata Steel U.K are compared using several variables. The comparison data includes; gas temperatures, surface temperatures, and mechanical deformation of the panels. Conclusions are drawn, noting improvements to be made on the current coupling open-source code FDS-2-ABAQUS to make it more applicable to Tata Steel U.K sandwich panel products. Future directions for reducing the computational cost of the simulation are also considered.

Keywords: fire engineering, numerical coupling, sandwich panels, thermo fluids

Procedia PDF Downloads 89

Authors: Sharon Li, Zhonghang Xia

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Post-database search is an essential phase in peptide identification using tandem mass spectrometry (MS/MS) to refine peptide-spectrum matches (PSMs) produced by database search engines. These engines frequently face difficulty differentiating between correct and incorrect peptide assignments. Despite advances in statistical and machine learning methods aimed at improving the accuracy of peptide identification, challenges remain in selecting critical features for these models. In this study, two machine learning models—a random forest tree and a support vector machine—were applied to three datasets to enhance PSMs. SHAP values were utilized to determine the significance of each feature within the models. The experimental results indicate that the random forest model consistently outperformed the SVM across all datasets. Further analysis of SHAP values revealed that the importance of features varies depending on the dataset, indicating that a feature's role in model predictions can differ significantly. This variability in feature selection can lead to substantial differences in model performance, with false discovery rate (FDR) differences exceeding 50% between different feature combinations. Through SHAP value analysis, the most effective feature combinations were identified, significantly enhancing model performance.

Keywords: peptide identification, SHAP value, feature selection, random forest tree, support vector machine

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Qiong Rao, Xiongqi Peng

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In this work, multi-walled carbon nanotubes (MWCNTs) and graphene nanoplates (GNPs) were dispersed into epoxy adhesive to investigate their synergy effects on the shear properties, mode I and mode II fracture toughness of unidirectional composite bonded joints. Testing results showed that the incorporation of MWCNTs and GNPs significantly improved the shear strength, the mode I and mode II fracture toughness by 36.6%, 45% and 286%, respectively. In addition, the fracture surfaces of the bonding area as well as the toughening mechanism of nanofillers were analyzed. Finally, a nonlinear cohesive/friction coupled model for delamination analysis of adhesive layer under shear and normal compression loadings was proposed and implemented in ABAQUS/Explicit via user subroutine VUMAT.

Keywords: nanofillers, adhesive joints, fracture toughness, cohesive zone model

Procedia PDF Downloads 133

Authors: Waziralilah N. Fathiah, A. Aminudin, U. Alyaa Hashim, T. Vikneshvaran D. Shakirah Shukor

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This paper presents the experimental analysis conducted on a structure borne noise in a rectangular enclosure prototype made by joining of sheet aluminum metal and plywood. The study is significant as many did not realized the annoyance caused by structural borne-noise. In this study, modal analysis is carried out to seek the structure’s behaviour in order to identify the characteristics of enclosure in frequency domain ranging from 0 Hz to 200 Hz. Here, numbers of modes are identified and the characteristic of mode shape is categorized. Modal experiment is used to diagnose the structural behaviour while microphone is used to diagnose the sound. Spectral testing is performed on the enclosure. It is acoustically excited using shaker and as it vibrates, the vibrational and noise responses sensed by tri-axis accelerometer and microphone sensors are recorded respectively. Experimental works is performed on each node lies on the gridded surface of the enclosure. Both experimental measurement is carried out simultaneously. The modal experimental results of the modal modes are validated by simulation performed using MSC Nastran software. In pursuance of reducing the structure borne-noise, mitigation method is used whereby the stiffener plates are perpendicularly placed on the sheet aluminum metal. By using this method, reduction in structure borne-noise is successfully made at the end of the study.

Keywords: enclosure, modal analysis, sound analysis, structure borne-noise

Procedia PDF Downloads 435

Authors: Basavaraj Vadavadagi, Satishkumar Shekhawat

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Interstitial free steels posses better formability and have many applications in automotive industries. Forming limit diagrams (FLDs) indicate the formability of materials which can be determined by experimental and finite element (FE) simulations. FLDs were determined experimentally by LDH test, utilizing optical strain measurement system for measuring the strains in different width specimens and by FE simulations in Interstitial Free (IF) and Interstitial Free High Strength (IFHS) steels. In this study, the experimental and FE simulated FLDs are compared and also the stress based FLDs were investigated.

Keywords: forming limit diagram, limiting dome height, optical strain measurement, interstitial

Procedia PDF Downloads 230

Authors: Hsin Lee, Hsuan Lee

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Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.

Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases

Procedia PDF Downloads 72

Authors: H. Namazi, H. T. N. Kuan

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Fick's first law relates the diffusive flux to the concentration field, by postulating that the flux goes from regions of high concentration to regions of low concentration, with a magnitude that is proportional to the concentration gradient (spatial derivative). It is clear that the diffusion of flux cannot be instantaneous and should be some time delay in this propagation. But Fick’s first law doesn’t consider this delay which results in some errors especially when there is a considerable time delay in the process. In this paper, we introduce a time delay to Fick’s first law. By this modification, we consider that the diffusion of flux cannot be instantaneous. In order to verify this claim an application sample in fluid diffusion is discussed and the results of modified Fick’s first law, Fick’s first law and the experimental results are compared. The results of this comparison stand for the accuracy of the modified model. The modified model can be used in any application where the time delay has considerable value and neglecting its effect reflects in undesirable results.

Keywords: Fick's first law, flux, diffusion, time delay, modified Fick’s first law

Procedia PDF Downloads 407

Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

Procedia PDF Downloads 646

Authors: Yanyan Zhang, Ziyu Diao, Zhentao Liu, Ruidong Yan

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The wear character of the main bearing is one of the critical indicators for the overhaul of an internal combustion engine, and the aim of this paper is to reveal the dynamic wear mechanism of the main bearings. A numerical simulation model combined multi-body dynamic equations of the engine, the average Reynolds equations of the bearing lubricant, asperity contact and wear model of the joint surfaces were established under typical operating conditions. The wear results were verified by experimental data, and then the influence of operating conditions, bearing clearance and cylinder pressure on the wear character of selected main bearings were analyzed. The results show that the contribution degree of different working conditions on the wear profile and depth of each bearing is obviously different, and the increase of joint clearance or cylinder pressure will accelerate the wear. The numerical model presented can be used to wear prognosis for joints and provide guidance for optimization design of sliding bearings.

Keywords: dynamic simulation, multi-body dynamics, sliding bearing, surface wear

Procedia PDF Downloads 148

Authors: O. Mauroner, L. Le, S. Best

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Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: advertising effectiveness, augmented reality, brand communication, brand recall

Procedia PDF Downloads 302

Authors: Uzu-Kuei Hsu, Chang-Hsien Tai, Kai-Wun Jin

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When sinters are filled into the cooler from the sintering machine, and the non-uniform distribution of the sinters leads to uneven cooling. This causes the temperature difference of the sinters leaving the cooler to be so large that it results in the conveyors being deformed by the heat. The present work applies CFD method to investigate the thermo flowfield phenomena in a sinter cooler by the Porous Media Model. Using the obtained experimental data to simulate porosity (Ε), permeability (κ), inertial coefficient (F), specific heat (Cp) and effective thermal conductivity (keff) of the sinter packed beds. The physical model is a similar geometry whose Darcy numbers (Da) are similar to the sinter cooler. Using the Cooling Index (CI) and Uniformity Index (UI) to analyze the thermo flowfield in the sinter packed bed obtains the cooling performance of the sinter cooler.

Keywords: porous media, sinter, cooling index (CI), uniformity index (UI), CFD

Procedia PDF Downloads 402

Authors: Mikkel Snorre Wilms Boysen

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From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

Procedia PDF Downloads 322

Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 125

Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Bertakalswa Hermawati

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In Indonesia, from 2007 until 2013, the prevalence of overnutrition in children under five years and school age tends to increase. Clean and Health Life Behavior of school children supporting nutrition status still below the determined target. On the other side, school institution is an ideal place to educate and form health behavior, that should be initiated as early as possible (Early Age Education/PAUD level). The objective of this research was to find out the effectivity of education model through partnership with school institution in urban region, city of Semarang, Central Java Province, Indonesia. The research used quantitative approach supported with qualitative data. The population consist of all mother having school children of ages 3-5 years within the research region; sampling technique was purposive sampling, as many as 237 mothers. Research instrument was Clean and Health Life Behavior evaluation questionaire, and video as education media. The research used experimental design. Data analysis used effectivity criteria from Sugiyono and 2 paired sampel t test. Education model optimalization in the effort to improve nutrition status indicates t test result with signification < 0.05 (there was significant effect before and after model intervention), with effectivity test result of 79% (effective), but still below expected target which is 80%. Education model need to be utilized and optimallized the implementation so that expected target reached.

Keywords: nutrition status, early age education, clean dan health life behavior, education model

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Authors: Amina Bouhaouche, Zineb Kaoua, Lila Lahreche, Sid Ali Kaoua, Kamel Daoud

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The objective of this study is to present a novel approach for analyzing the solid dispersion and mixing performance by a numerical simulation method using solid works software of a monodisperse particles for a large span of time reached 20 minutes. To assure the viability of a numerical simulation, an experimental study of a binary mixture of monodiperse particles taken as free flowing material in a V blender was developed on the basis of relative standard deviation curves, and the arrangement of the particles in the vessel. The experimental results were discussed and compared to the numerical simulation results.

Keywords: non-cohesive material, solid mixing, solid works, v-blender

Procedia PDF Downloads 390

Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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Authors: Maria Lazari, Lorenzo Sanavia

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Mechanics of unsaturated soils has been an active field of research in the last decades. Efficient constitutive models that take into account the partial saturation of soil are necessary to solve a number of engineering problems e.g. instability of slopes and cuts due to heavy rainfalls. A large number of constitutive models can now be found in the literature that considers fundamental issues associated with the unsaturated soil behaviour, like the volume change and shear strength behaviour with suction or saturation changes. Partially saturated soils may either expand or collapse upon wetting depending on the stress level, and it is also possible that a soil might experience a reversal in the volumetric behaviour during wetting. Shear strength of soils also changes dramatically with changes in the degree of saturation, and a related engineering problem is slope failures caused by rainfall. There are several states of the art reviews over the last years for studying the topic, usually providing a thorough discussion of the stress state, the advantages, and disadvantages of specific constitutive models as well as the latest developments in the area of unsaturated soil modelling. However, only a few studies focused on the coupling between partial saturation states and time effects on the behaviour of geomaterials. Rate dependency is experimentally observed in the mechanical response of granular materials, and a viscoplastic constitutive model is capable of reproducing creep and relaxation processes. Therefore, in this work an elasto-viscoplastic constitutive model for unsaturated soils is proposed and validated on the basis of experimental data. The model constitutes an extension of an existing elastoplastic strain-hardening constitutive model capable of capturing the behaviour of variably saturated soils, based on energy conjugated stress variables in the framework of superposed continua. The purpose was to develop a model able to deal with possible mechanical instabilities within a consistent energy framework. The model shares the same conceptual structure of the elastoplastic laws proposed to deal with bonded geomaterials subject to weathering or diagenesis and is capable of modelling several kinds of instabilities induced by the loss of hydraulic bonding contributions. The novelty of the proposed formulation is enhanced with the incorporation of density dependent stiffness and hardening coefficients in order to allow the modeling of the pycnotropy behaviour of granular materials with a single set of material constants. The model has been implemented in the commercial FE platform PLAXIS, widely used in Europe for advanced geotechnical design. The algorithmic strategies adopted for the stress-point algorithm had to be revised to take into account the different approach adopted by PLAXIS developers in the solution of the discrete non-linear equilibrium equations. An extensive comparison between models with a series of experimental data reported by different authors is presented to validate the model and illustrate the capability of the newly developed model. After the validation, the effectiveness of the viscoplastic model is displayed by numerical simulations of a partially saturated slope failure of the laboratory scale and the effect of viscosity and degree of saturation on slope’s stability is discussed.

Keywords: PLAXIS software, slope, unsaturated soils, Viscoplasticity

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Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Adesola O. Orimoloye, Mohammed N. Kajama, Edward Gobina

Abstract:

Gas permeation of Oxygen [O2] and Nitrogen [N2] were investigated at room temperature using 15 and 6000nm pore diameter tubular commercial alumina ceramic membranes with pressure values ranging 1.00 to 2.50 bar. The flow rates of up to 2.59 and 2.77 l/min were achieved for O2 and N2 respectively. The ratio of O2/N2 flow rates were used to compute the O2/N2 selectivity. The experimental O2/N2 selectivity obtained for 15 nm was 1.05 while the 6000 nm indicated 0.95.

Keywords: gas separation, nitrogen, oxygen, selectivity

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