Search results for: Fault Prediction Modeling.

Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine

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Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

Keywords: Coefficient of performance, ejector refrigeration system, exergy efficiency, heat exchangers modeling, moving boundary method.

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: Adult, basal metabolic rate, FAO/WHO/UNU, obesity, prediction equations.

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Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd

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This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.

Keywords: Optimization, reinforced concrete, single-span frames, optimization methods of impact load.

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Authors: A. Saghaei, R. Ghasemi

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Through 1980s, management accounting researchers described the increasing irrelevance of traditional control and performance measurement systems. The Balanced Scorecard (BSC) is a critical business tool for a lot of organizations. It is a performance measurement system which translates mission and strategy into objectives. Strategy map approach is a development variant of BSC in which some necessary causal relations must be established. To recognize these relations, experts usually use experience. It is also possible to utilize regression for the same purpose. Structural Equation Modeling (SEM), which is one of the most powerful methods of multivariate data analysis, obtains more appropriate results than traditional methods such as regression. In the present paper, we propose SEM for the first time to identify the relations between objectives in the strategy map, and a test to measure the importance of relations. In SEM, factor analysis and test of hypotheses are done in the same analysis. SEM is known to be better than other techniques at supporting analysis and reporting. Our approach provides a framework which permits the experts to design the strategy map by applying a comprehensive and scientific method together with their experience. Therefore this scheme is a more reliable method in comparison with the previously established methods.

Keywords: BSC, SEM, Strategy map.

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Authors: Vytautas Galvanauskas, Vykantas Grincas, Rimvydas Simutis

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This paper investigates a possible practical solution for reasonable oxygen supply during the pluripotent stem cells expansion processes, where the stem cells propagate as aggregates in stirred-suspension bioreactors. Low glucose and low oxygen concentrations are preferred for efficient proliferation of pluripotent stem cells. However, strong oxygen limitation, especially inside of cell aggregates, can lead to cell starvation and death. In this research, the oxygen concentration profile inside of stem cell aggregates in a stem cell expansion process was predicted using a modified oxygen diffusion model. This profile can be realized during the stem cells cultivation process by manipulating the oxygen concentration in inlet gas or inlet gas flow. The proposed approach is relatively simple and may be attractive for installation in a real pluripotent stem cell expansion processes.

Keywords: Aggregated stem cells, dissolved oxygen profiles, modeling, stirred-tank, 3D expansion.

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Authors: Muhammad R Ahmed, Xu Huang, Dharmandra Sharma, Hongyan Cui

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An information procuring and processing emerging technology wireless sensor network (WSN) Consists of autonomous nodes with versatile devices underpinned by applications. Nodes are equipped with different capabilities such as sensing, computing, actuation and wireless communications etc. based on application requirements. A WSN application ranges from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. The nodes are deployed independently to cooperatively monitor the physical and environmental conditions. The architecture of WSN differs based on the application requirements and focus on low cost, flexibility, fault tolerance capability, deployment process as well as conserve energy. In this paper we have present the characteristics, architecture design objective and architecture of WSN

Keywords: wireless sensor network, characteristics, architecture

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Authors: Hojjat Saberinejad, Adel Hashiehbaf, Ehsan Afrasiabian

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Among the various cooling processes in industrial applications such as: electronic devices, heat exchangers, gas turbines, etc. Gas turbine blades cooling is the most challenging one. One of the most common practices is using ribbed wall because of the boundary layer excitation and therefore making the ultimate cooling. Vortex formation between rib and channel wall will result in a complicated behavior of flow regime. At the other hand, selecting the most efficient method for capturing the best results comparing to experimental works would be a fascinating issue. In this paper 4 common methods in turbulence modeling: standard k-e, rationalized k-e with enhanced wall boundary layer treatment, k-w and RSM (Reynolds stress model) are employed to a square ribbed channel to investigate the separation and thermal behavior of the flow in the channel. Finally all results from different methods which are used in this paper will be compared with experimental data available in literature to ensure the numerical method accuracy.

Keywords: boundary layer, turbulence, numerical method, rib cooling

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies  the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: Retail stores, Faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition.

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Authors: Moaz H. Ali, M. N. M. Ansari

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This paper presents a study the effect of nose radius (Rz-mm) on cutting force components and temperatures during the machining simulation in an orthogonal cutting process for titanium alloy (Ti-6Al-4V). The cutting process was performed at various nose radiuses (Rz-mm) while the depth of cut (d-mm), feed rate (fmm/ tooth) and cutting speed (vc-m/ min) were remained constant. The main cutting force (Fc), feed cutting force (Ft) and temperatures were estimated by using finite element modeling (FEM) through ABAQUS/EXPLICIT software and the simulation was developed the two-dimension via an orthogonal cutting process during machining titanium alloy (Ti-6Al-4V). The results led to the conclusion that the nose radius (Rz-mm) has affected directly on the cutting force components. However, temperature gave no indication or has no significant relation with nose radius during machining titanium alloy (Ti-6Al-4V). Hence, any increase or decrease in the nose radius (Rzmm) during machining operation led to effect on the cutting forces and thus it will be effective on surface finish, quality, and quantity of products.

Keywords: Finite element modeling (FEM), nose radius, cutting force, temperature, titanium alloy (Ti-6Al-4V).

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Authors: Mohamed H. S. Mohamed, Yang Xiao-zong, Liu Hong-wei, Wu Zhi-bo

Abstract:

The reliability of distributed systems and computer networks have been modeled by a probabilistic network or a graph G. Computing the residual connectedness reliability (RCR), denoted by R(G), under the node fault model is very useful, but is an NP-hard problem. Since it may need exponential time of the network size to compute the exact value of R(G), it is important to calculate its tight approximate value, especially its lower bound, at a moderate calculation time. In this paper, we propose an efficient algorithm for reliability lower bound of distributed systems with unreliable nodes. We also applied our algorithm to several typical classes of networks to evaluate the lower bounds and show the effectiveness of our algorithm.

Keywords: Distributed systems, probabilistic network, residual connectedness reliability, lower bound.

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Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida

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This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

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There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: Artificial neural network, ANN, high performance concrete, rebound hammer, strength prediction.

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Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: E-learning system, gamification, motivation, social comparison, visualization.

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Authors: Karima Qayumi, Alex Norta

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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.

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Authors: P. V. V. Rama Rao, B. Kali Prasanna, Y. T. R. Palleswari

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Renewable energy is derived from natural processes that are replenished constantly. Included in the definition is electricity and heat generated from solar, wind, ocean, hydropower, biomass, geothermal resources, and bio-fuels and hydrogen derived from renewable resources. Each of these sources has unique characteristics which influence how and where they are used. This paper presents the modeling the simulation of solar and hydro hybrid energy sources in MATLAB/SIMULINK environment. It simulates all quantities of Hybrid Electrical Power system (HEPS) such as AC output current of the inverter that injected to the load/grid, load current, grid current. It also simulates power output from PV and Hydraulic Turbine Generator (HTG), power delivered to or from grid and finally power factor of the inverter for PV, HTG and grid. The proposed circuit uses instantaneous p-q (real-imaginary) power theory.

Keywords: Photovoltaic Array, Hydraulic Turbine Generator, Electrical Utility (EU), Hybrid Electrical Power Supply.

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: Time-series clustering, feature extraction, hoax prediction, geospatial events.

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Authors: A. Nicknam, N. Eftekhari, A. Mazarei, M. Ganjvar

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This article presents an alternative collapse capacity intensity measure in the three elements form which is influenced by the spectral ordinates at periods longer than that of the first mode period at near and far source sites. A parameter, denoted by β, is defined by which the spectral ordinate effects, up to the effective period (2T1), on the intensity measure are taken into account. The methodology permits to meet the hazard-levelled target extreme event in the probabilistic and deterministic forms. A MATLAB code is developed involving OpenSees to calculate the collapse capacities of the 8 archetype RC structures having 2 to 20 stories for regression process. The incremental dynamic analysis (IDA) method is used to calculate the structure’s collapse values accounting for the element stiffness and strength deterioration. The general near field set presented by FEMA is used in a series of performing nonlinear analyses. 8 linear relationships are developed for the 8structutres leading to the correlation coefficient up to 0.93. A collapse capacity near field prediction equation is developed taking into account the results of regression processes obtained from the 8 structures. The proposed prediction equation is validated against a set of actual near field records leading to a good agreement. Implementation of the proposed equation to the four archetype RC structures demonstrated different collapse capacities at near field site compared to those of FEMA. The reasons of differences are believed to be due to accounting for the spectral shape effects.

Keywords: Collapse capacity, fragility analysis, spectral shape effects, IDA method.

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Authors: Sachin Kumar, Vasilis Sotiris, Michael Pecht

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With increasing complexity in electronic systems there is a need for system level anomaly detection and fault isolation. Anomaly detection based on vector similarity to a training set is used in this paper through two approaches, one the preserves the original information, Mahalanobis Distance (MD), and the other that compresses the data into its principal components, Projection Pursuit Analysis. These methods have been used to detect deviations in system performance from normal operation and for critical parameter isolation in multivariate environments. The study evaluates the detection capability of each approach on a set of test data with known faults against a baseline set of data representative of such “healthy" systems.

Keywords: Mahalanobis distance, Principle components, Projection pursuit, Health assessment, Anomaly.

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Authors: Charbel Geryes Aoun, Loic Lagadec

Abstract:

A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g. Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple-views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: Smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS.

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Authors: M. A. Ghorbani, M. Pasbani Khiavi

Abstract:

In this paper, the dam-reservoir interaction is analyzed using a finite element approach. The fluid is assumed to be incompressible, irrotational and inviscid. The assumed boundary conditions are that the interface of the dam and reservoir is vertical and the bottom of reservoir is rigid and horizontal. The governing equation for these boundary conditions is implemented in the developed finite element code considering the horizontal and vertical earthquake components. The weighted residual standard Galerkin finite element technique with 8-node elements is used to discretize the equation that produces a symmetric matrix equation for the damreservoir system. A new boundary condition is proposed for truncating surface of unbounded fluid domain to show the energy dissipation in the reservoir, through radiation in the infinite upstream direction. The Sommerfeld-s and perfect damping boundary conditions are also implemented for a truncated boundary to compare with the proposed far end boundary. The results are compared with an analytical solution to demonstrate the accuracy of the proposed formulation and other truncated boundary conditions in modeling the hydrodynamic response of an infinite reservoir.

Keywords: Reservoir, finite element, truncated boundary, hydrodynamic pressure

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

Abstract:

This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.

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Authors: Rida B. Arieby

Abstract:

This study deals with the experimental investigation and theoretical modeling of Semi crystalline polymeric materials with a rubbery amorphous phase (HDPE) subjected to a uniaxial cyclic tests with various maximum strain levels, even at large deformation. Each cycle is loaded in tension up to certain maximum strain and then unloaded down to zero stress with N number of cycles. This work is focuses on the measure of the volume strain due to the phenomena of damage during this kind of tests. On the basis of thermodynamics of relaxation processes, a constitutive model for large strain deformation has been developed, taking into account the damage effect, to predict the complex elasto-viscoelastic-viscoplastic behavior of material. A direct comparison between the model predictions and the experimental data show that the model accurately captures the material response. The model is also capable of predicting the influence damage causing volume variation.

Keywords: Cyclic test, large strain, polymers semi-crystalline, Volume strain, Thermodynamics of Irreversible Processes.

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Authors: Hamidreza Babaali, Alireza Mojtahedi, Nasim Soori, Saba Soori

Abstract:

Hydraulic jump is one of the effective ways of energy dissipation in stilling basins that the ‎energy is highly dissipated by jumping. Adverse slope surface at the end stilling basin is ‎caused to increase energy dissipation and stability of the hydraulic jump. In this study, the adverse slope ‎has been added to end of United States Bureau of Reclamation (USBR) II stilling basin in hydraulic model of Nazloochay dam with scale 1:40, and flow simulated into stilling basin using Flow-3D ‎software. The numerical model is verified by experimental data of water depth in ‎stilling basin. Then, the parameters of water level profile, Froude Number, pressure, air ‎entrainment and turbulent dissipation investigated for discharging 300 m³/s using K-Ɛ and Re-Normalization Group (RNG) turbulence ‎models. The results showed a good agreement between numerical and experimental model‎ as ‎numerical model can be used to optimize of stilling basins.‎

Keywords: Experimental and numerical modeling, end adverse slope, flow ‎parameters, USBR II Stilling Basin.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: Miroslav Popelka, Jakub Nožička

Abstract:

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, Real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software.

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Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

Abstract:

Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, Moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine.

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Authors: Moghiman Mohammad, Amiri Maryam, Amiri Amirhosein

Abstract:

The present paper develops and validates a numerical procedure for the calculation of turbulent combustive flow in converging and diverging ducts and throuh simulation of the heat transfer processes, the amount of production and spread of Nox pollutant has been measured. A marching integration solution procedure employing the TDMA is used to solve the discretized equations. The turbulence model is the Prandtl Mixing Length method. Modeling the combustion process is done by the use of Arrhenius and Eddy Dissipation method. Thermal mechanism has been utilized for modeling the process of forming the nitrogen oxides. Finite difference method and Genmix numerical code are used for numerical solution of equations. Our results indicate the important influence of the limiting diverging angle of diffuser on the coefficient of recovering of pressure. Moreover, due to the intense dependence of Nox pollutant to the maximum temperature in the domain with this feature, the Nox pollutant amount is also in maximum level.

Keywords: Converging and Diverging Duct, Combustion, Diffuser, Diverging Angle, Nox

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Authors: Z. A. Ahmad Noor Syukri, A. J. Nawal Aswan, S. V. Wong

Abstract:

The motorcycle has become one of the most common type of vehicles used on the road, particularly in the Asia region, including Malaysia, due to its size-convenience and affordable price. This study focuses only on crashes involving motorcycles with passenger cars consisting 43 real world crashes obtained from in-depth crash investigation process from June 2016 till July 2017. The study collected and analyzed vehicle and site parameters obtained during crash investigation and injury information acquired from the patient-treating hospital. The investigation team, consisting of two personnel, is stationed at the Emergency Department of the treatment facility, and was dispatched to the crash scene once receiving notification of the related crashes. The injury information retrieved was coded according to the level of severity using the Abbreviated Injury Scale (AIS) and classified into different body regions. The data revealed that weekend crashes were significantly higher for the night time period and the crash occurrence was the highest during morning hours (commuting to work period) for weekdays. Bad weather conditions play a minimal effect towards the occurrence of motorcycle – passenger vehicle crashes and nearly 90% involved motorcycles with single riders. Riders up to 25 years old are heavily involved in crashes with passenger vehicles (60%), followed by 26-55 year age group with 35%. Male riders were dominant in each of the age segments. The majority of the crashes involved side impacts, followed by rear impacts and cars outnumbered the rest of the passenger vehicle types in terms of crash involvement with motorcycles. The investigation data also revealed that passenger vehicles were the most at-fault counterpart (62%) when involved in crashes with motorcycles and most of the crashes involved situations whereby both of the vehicles are travelling in the same direction and one of the vehicles is in a turning maneuver. More than 80% of the involved motorcycle riders had sustained yellow severity level during triage process. The study also found that nearly 30% of the riders sustained injuries to the lower extremities, while MAIS level 3 injuries were recorded for all body regions except for thorax region. The result showed that crashes in which the motorcycles were found to be at fault were more likely to occur during night and raining conditions. These types of crashes were also found to be more likely to involve other types of passenger vehicles rather than cars and possess higher likelihood in resulting higher ISS (>6) value to the involved rider. To reduce motorcycle fatalities, it first has to understand the characteristics concerned and focus may be given on crashes involving passenger vehicles as the most dominant crash partner on Malaysian roads.

Keywords: Motorcycle crash, passenger vehicle, in-depth crash investigation, injury mechanism.

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Authors: Yung-Yuan Hsu

Abstract:

The primary objective of this paper was to construct a “kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools.

Keywords: Three-axis machine tool, Geometric error, HTM, Error measuring

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