Search results for: lattice discrete element method

Authors: Hadia Rafi

Abstract:

To make any decision in any work/task/project it involves many factors that needed to be looked. The analytic Hierarchy process (AHP) is based on the judgments of experts to derive the required results this technique measures the intangibles and then by the help of judgment and software analysis the comparisons are made which shows how much a certain element/unit leads another. AHP includes how an inconsistent judgment should be made consistent and how the judgment should be improved when possible. The Priority scales are obtained by multiplying them with the priority of their parent node and after that they are added.

Keywords: AHP, priority scales, parent node, software analysis

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Authors: Thomas Yeboah, Gifty Akouko Sarpong

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Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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Authors: D. S. Vardar, A. S. Kipcak, F. T. Senberber, E. M. Derun, S. Piskin, N. Tugrul

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Zinc borate is an important inorganic hydrate borate material, which can be use as a flame retardant agent and corrosion resistance material. This compound can loss its structural water content at higher than 290°C. Due to thermal stability; Zinc Borate can be used as flame reterdant at high temperature process of plastic and gum. In this study, the ultrasonic reaction of zinc borates were studied using hydrozincite (Zn5(CO3)2•(OH)6) and boric acid (H3BO3) raw materials. Before the synthesis raw materials were characterized by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). Ultrasonic method is a new application on the zinc borate synthesis. The synthesis parameters were set to 90°C reaction temperature and 55 minutes of reaction time, with 1:1, 1:2, 1:3, 1:4 and 1:5 molar ratio of starting materials (Zn5(CO3)2•(OH)6 : H3BO3). After the zinc borate synthesis, the products analyzed by XRD and FT-IR. As a result, optimum molar ratio of 1:5 (Zn5(CO3)2•(OH)6:H3BO3) is determined for the synthesis of zinc borates with ultrasonic method.

Keywords: borate, ultrasonic method, zinc borate, zinc borate synthesis

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Authors: Ahmet Kaya

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Quantum mechanism is one of the most important approaches to calculating non-ruin probability. We apply standard Dirac notation to model given Hamiltonians. By using the traditional method and eigenvector basis, non-ruin probability is found for several examples. Also, non-ruin probability is calculated for two different Hamiltonian by using the tensor product. Finally, the path integral method is applied to the examples and comparison is made for stochastic simulations and path integral calculation.

Keywords: quantum physics, Hamiltonian system, path integral, tensor product, ruin probability

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Authors: Qian Zhao, Shi-Qi Liu, Bo Guo, Zhi-Jun Cheng, Xiao-Yue Wu

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Cold standby redundancy is considered to be an effective mechanism for improving system reliability and is widely used in industrial engineering. However, because of the complexity of the reliability structure, there is little literature studying on the residual life of cold standby system consisting of complex components. In this paper, a simulation method is presented to predict the residual life of k-out-of-n cold standby system. In practical cases, failure information of a system is either unknown, partly unknown or completely known. Our proposed method is designed to deal with the three scenarios, respectively. Differences between the procedures are analyzed. Finally, numerical examples are used to validate the proposed simulation method.

Keywords: cold standby system, k-out-of-n, residual life, simulation sampling

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Authors: Hamid Goharnejad, Amir Hossein Eghbali

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Recent investigations have demonstrated the global sea level rise due to climate change impacts. In this study climate changes study the effects of increasing water level in the strait of Hormuz. The probable changes of sea level rise should be investigated to employ the adaption strategies. The climatic output data of a GCM (General Circulation Model) named CGCM3 under climate change scenario of A1b and A2 were used. Among different variables simulated by this model, those of maximum correlation with sea level changes in the study region and least redundancy among themselves were selected for sea level rise prediction by using stepwise regression. One models of Discrete Wavelet artificial Neural Network (DWNN) was developed to explore the relationship between climatic variables and sea level changes. In these models, wavelet was used to disaggregate the time series of input and output data into different components and then ANN was used to relate the disaggregated components of predictors and predictands to each other. The results showed in the Shahid Rajae Station for scenario A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea level rise is among 90 to 105 cm. Furthermore the result showed a significant increase of sea level at the study region under climate change impacts, which should be incorporated in coastal areas management.

Keywords: climate change scenarios, sea-level rise, strait of Hormuz, forecasting

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Authors: Livhuwani Muthelo, R. N. Malema, T. M. Mothiba

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Long term exposure to excessive noise in the mining industry increases the risk of noise induced hearing loss, with consequences for employee’s health, productivity and the overall quality of life. Objective: The objective of this study was to investigate the factors that contribute to Noise Induced Hearing Loss amongst employees at the Platinum mine in the Limpopo Province, South Africa. Study method: A qualitative, phenomenological, exploratory, descriptive, contextual design was applied in order to explore and describe the contributory factors. Purposive non-probability sampling was used to select 10 male employees who were diagnosed with NIHL in the year 2014 in four mine shafts, and 10 managers who were involved in a Hearing Conservation Programme. The data were collected using semi-structured one-on-one interviews. A qualitative data analysis of Tesch’s approach was followed. Results: The following themes emerged: Experiences and challenges faced by employees in the work environment, hearing protective device factors and management and leadership factors. Hearing loss was caused by partial application of guidelines, policies, and procedures from the Department of Minerals and Energy. Conclusion: The study results indicate that although there are guidelines, policies, and procedures available, failure in the implementation of one element will affect the development and maintenance of employees hearing mechanism. It is recommended that the mine management should apply the guidelines, policies, and procedures and promptly repair the broken hearing protective devices.

Keywords: employees, factors, noise induced hearing loss, noise exposure

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Authors: Eduardo P. Wiechmann, Jorge A. Henríquez, Pablo E. Aqueveque, Luis G. Muñoz

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PV energy prices are declining rapidly. To take advantage of the benefits of those prices and lower the carbon footprint, operational practices must be modified. Undoubtedly, it challenges the electrowinning practice to operate at constant current throughout the day. This work presents a technology that contributes in providing modulation capacity to the electrode current distribution system. This is to raise the day time dc current and lower it at night. The system is a triple intercell bar that operates in current-source mode. The design is a capping board free dogbone type of bar that ensures an operation free of short circuits, hot swapability repairs and improved current balance. This current-source system eliminates the resetting currents circulating in equipotential bars. Twin auxiliary connectors are added to the main connectors providing secure current paths to bypass faulty or impaired contacts. All system conductive elements are positioned over a baseboard offering a large heat sink area to the ventilation of a facility. The system works with lower temperature than a conventional busbar. Of these attributes, the cathode current balance property stands out and is paramount for day/night modulation and the use of photovoltaic energy. A design based on a 3D finite element method model predicting electric and thermal performance under various industrial scenarios is presented. Preliminary results obtained in an electrowinning facility with industrial prototypes are included.

Keywords: electrowinning, intercell bars, PV energy, current modulation

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Authors: Qurrat-ul-Ain Gulfam, Zbigniew Ficek

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The novel idea to use single atoms as highly reflecting mirrors has recently gained much attention. Usually, to observe the reflective nature of an atom, it is required to couple the atom to an external medium such that a directional spontaneous emission could be realized. We propose an alternative way to achieve the directional emission by considering a system of correlated atoms in free space. It is well known that mutually interacting atoms have a strong tendency to emit the radiation along particular discrete directions. That relieves one from the stingy condition of associating the atomic system to another media and facilitates the experimental implementation to a large degree. Moreover, realistic 3-dimensional collective emission can be taken into account in the dynamics. Two interesting spatial setups have been considered; one where a probe atom is confined in a linear cavity formed by two atomic mirrors and, the other where a probe atom faces a chain of correlated atoms. We observe an evidence of the mirror-like effect in a simple system of a chain of three atoms. The angular distribution of the radiation intensity observed in the far field is greatly affected by the atomic interactions. Hence, suitable directions for enhanced reflectivity can be determined.

Keywords: atom-mirror effect, correlated system, dipole-dipole interactions, intensity

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Authors: Laxman H. Surwase, Lalit V. Sonawane, Bhagwat N. Poul

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A simple stability indicating high performance liquid chromatographic method has been developed for the simultaneous determination of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical dosage form using reverse phase Zorbax Eclipse Plus C8 column (250mm×4.6mm), with mobile phase phosphate buffer (0.05M KH2PO4): acetonitrile (55:45v/v) pH 3.5 adjusted with ortho-phosphoric acid, the flow rate was 1.0 mL/min and the detection was carried at 212 nm. The retention times of Levosalbutamol Sulphate and Ipratropium Bromide were 2.2007 and 2.6611 min respectively. The correlation coefficient of Levosalbutamol Sulphate and Ipratropium Bromide was found to be 0.997 and 0.998.Calibration plots were linear over the concentration ranges 10-100µg/mL for both Levosalbutamol Sulphate and Ipratropium Bromide. The LOD and LOQ of Levosalbutamol Sulphate were 2.520µg/mL and 7.638µg/mL while for Ipratropium Bromide was 1.201µg/mL and 3.640 µg/mL. The accuracy of the proposed method was determined by recovery studies and found to be 100.15% for Levosalbutamol Sulphate and 100.19% for Ipratropium Bromide respectively. The method was validated for accuracy, linearity, sensitivity, precision, robustness, system suitability. The proposed method could be utilized for routine analysis of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical capsule dosage form.

Keywords: levosalbutamol sulphate, ipratropium bromide, RP-HPLC, phosphate buffer, acetonitrile

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Ke Zhang, Yongli Zhu

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Due to rapid load growths in today’s highly electrified societies and the requirement for green energy sources, large-scale wind farm power transmission system is constantly developing. This system is a typical multi-terminal power supply system, whose structure of the network topology of transmission lines is complex. What’s more, it locates in the complex terrain of mountains and grasslands, thus increasing the possibility of transmission line faults and finding the fault location with difficulty after the faults and resulting in an extremely serious phenomenon of abandoning the wind. In order to solve these problems, a fault location method for multi-terminal transmission line based on wind farm characteristics and improved single-ended traveling wave positioning method is proposed. Through studying the zero sequence current characteristics by using the characteristics of the grounding transformer(GT) in the existing large-scale wind farms, it is obtained that the criterion for judging the fault interval of the multi-terminal transmission line. When a ground short-circuit fault occurs, there is only zero sequence current on the path between GT and the fault point. Therefore, the interval where the fault point exists is obtained by determining the path of the zero sequence current. After determining the fault interval, The location of the short-circuit fault point is calculated by the traveling wave method. However, this article uses an improved traveling wave method. It makes the positioning accuracy more accurate by combining the single-ended traveling wave method with double-ended electrical data. What’s more, a method of calculating the traveling wave velocity is deduced according to the above improvements (it is the actual wave velocity in theory). The improvement of the traveling wave velocity calculation method further improves the positioning accuracy. Compared with the traditional positioning method, the average positioning error of this method is reduced by 30%.This method overcomes the shortcomings of the traditional method in poor fault location of wind farm transmission lines. In addition, it is more accurate than the traditional fixed wave velocity method in the calculation of the traveling wave velocity. It can calculate the wave velocity in real time according to the scene and solve the traveling wave velocity can’t be updated with the environment and real-time update. The method is verified in PSCAD/EMTDC.

Keywords: grounding transformer, multi-terminal transmission line, short circuit fault location, traveling wave velocity, wind farm

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Authors: Jeff Letcher, Dennis Tierney, Haider Raad

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Antennas are devices for transmitting and/or receiving signals which make them a necessary component of any wireless system. In this paper, a thermal deposition technique is utilized as a method to fabricate antenna structures on substrates. Thin-film deposition is achieved by evaporating a source material (metals in our case) in a vacuum which allows vapor particles to travel directly to the target substrate which is encased with a mask that outlines the desired structure. The material then condenses back to solid state. This method is used in comparison to screen printing, chemical etching, and ink jet printing to indicate advantages and disadvantages to the method. The antenna created undergoes various testing of frequency ranges, conductivity, and a series of flexing to indicate the effectiveness of the thermal deposition technique. A single band antenna that is operated at 2.45 GHz intended for wearable and flexible applications was successfully fabricated through this method and tested. It is concluded that thermal deposition presents a feasible technique of producing such antennas.

Keywords: thermal deposition, wearable antennas, bluetooth technology, flexible electronics

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: E. Yarar, E. A. Guven, S. Karabay

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In this study, a comprehensive simulation was made for the cold tube drawing with fixed plug. The cold tube drawing process is preferred due to its high surface quality and the high mechanical properties. In drawing processes applied to materials with low plastic deformability, cracks can occur on the surfaces and the process efficiency decreases. The aim of the work is to investigate the effects of different drawing parameters on drawing forces and stresses. In the simulations, optimum conditions were investigated for four different materials, Ti64Al4V, AA5052, AISI4140, and C365. One of the most important parameters for the cold drawing process is the die angle. Three dies were designed for the analysis with semi die angles of 5°, 10°, and 15°. Three different parameters were used for the friction coefficient between die and the material. In the simulations, reduction of area and the drawing speed is kept constant. Drawing is done in one pass. According to the simulation results, the highest drawing forces were obtained in Ti64Al4V. As the semi die angle increases, the drawing forces decrease. The change in semi die angle was most effective on Ti64Al4V. Increasing the coefficient of friction is another effect that increases the drawing forces. The increase in the friction coefficient has also increased in drawing stresses. The increase in die angle also increased the drawing stress distribution for the other three materials outside C365. According to the results of the analysis, it is found that the designed drawing die is suitable for drawing. The lowest drawing stress distribution and drawing forces were obtained for AA5052. Drawing die parameters have a direct effect on the results. In addition, lubricants used for drawing have a significant effect on drawing forces.

Keywords: cold tube drawing, drawing force, drawing stress, semi die angle

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Authors: Sandra Juradin, Lidia Karla Vranjes

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The environmental impact of the components of concrete is considerable. The paper presents the influence of ground clay brick filler on the properties of self-compacting lightweight concrete (SCLC). In the manufacture and transport of clay bricks, product damage may occur. The filler was obtained by milling the damaged clay brick and sieved under the 0.04 mm size. The composition of each of SCLC mixture was determined according to the CBI method and compared with EFNARC (European Association) criteria. Self-compacting lightweight concrete has been tested in a fresh (slump flow method, visual assessment of stability, T50 time, V-funnel method, L-box method and J-ring) and hardened state (compressive strengths and dynamic modulus of elasticity). Mixtures with this filler had good results of compressive strength, but in fresh state the mixtures were sticky. All results were analyzed and compared with previous studies.

Keywords: CBI methods, ground clay brick, self-compacting lightweight concrete, silica fume

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Authors: Suresh Palla

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This research paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by novel selective dissolution method. Types of cement samples investigated include OPC with fly ash as performance improver, OPC with slag as performance improver, PPC, PSC and Composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this novel selective dissolution method can be successfully used for estimation of OPC and SCMs contents in different types of cements.

Keywords: selective dissolution method , fly ash, ggbfs slag, edta

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Authors: Robert L. Williamson

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A 'token economy' refers to a method of positive behaviour support whereby ‘tokens’ are delivered to students as a reward for exhibiting specific behaviours. Students later exchange tokens to ‘purchase’ items of interest. Unfortunately, implementation fidelity can be problematic as some find physical delivery of tokens while teaching difficult. This project developed and tested a prototype, iPad-based tool that enabled teachers to deliver and track tokens electronically. Using an alternating treatment design, any differences in on-task individual and/or group behaviours between the virtual versus physical token delivery systems were examined. Results indicated that while students and teachers preferred iPad-based implementation, no significant difference was found concerning on-task behaviours of students between the two methodologies. Perhaps more interesting was that the teacher found implementation of both methods problematic and suggested a second person was most effective in implementing a token economy method. This would represent a significant cost to the effective use of such a method. Further research should focus on the use of a lay volunteer regarding method implementation fidelity and associated outcomes of the method.

Keywords: positive behaviour support, inclusion, token economy, applied behaviour analysis

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Authors: Rakesh Kumar, A. K. Ghosh

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The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Lukas Reznak, Maria Reznakova

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Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

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Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

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Authors: E. Krasnova, E. Bulgakova, V. Shchemelinin

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The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field.

Keywords: speaker identification, acoustic-spectrographic method, non-native speech, performance evaluation

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Authors: Abdelkader Hachemi, Boualem Remini

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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.

Keywords: seawater intrusion, sharp interface, coastal aquifer, algeria

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Authors: Chaouki Ghenai

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Computational Fluid Dynamic analysis of co-combustion of coal/biomass waste fuel blends is presented in this study. The main objective of this study is to investigate the effects of biomass portions (0%, 10%, 20%, 30%: weight percent) blended with coal and oxygen concentrations (21% for air, 35%, 50%, 75% and 100 % for pure oxygen) on the combustion performance and emissions. The goal is to reduce the air emissions from power plants coal combustion. Sub-bituminous Nigerian coal with calorific value of 32.51 MJ/kg and sawdust (biomass) with calorific value of 16.68 MJ/kg is used in this study. Coal/Biomass fuel blends co-combustion is modeled using mixture fraction/pdf approach for non-premixed combustion and Discrete Phase Modeling (DPM) to predict the trajectories and the heat/mass transfer of the fuel blend particles. The results show the effects of oxygen concentrations and biomass portions in the coal/biomass fuel blends on the gas and particles temperatures, the flow field, the devolitization and burnout rates inside the combustor and the CO2 and NOX emissions at the exit from the combustor. The results obtained in the course of this study show the benefits of enriching combustion air with oxygen and blending biomass waste with coal for reducing the harmful emissions from coal power plants.

Keywords: co-combustion, coal, biomass, fuel blends, CFD, air emissions

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Authors: R. B. Ogunrinde, C. C. Jibunoh

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In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t.

Keywords: spectral decomposition, linear RHS, homogeneous linear systems, eigenvalues of the Jacobian

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Authors: Salah Aguib, Noureddine Chikh, Abdelmalek Khabli, Abdelkader Nour, Toufik Djedid, Lallia Kobzili

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This study presents the behavior of a hybrid smart sandwich plate with a magnetorheological elastomer core. In order to improve the vibrational behavior of the plate, the pseudo‐fibers formed by the effect of the magnetic field on the elastomer charged by the ferromagnetic particles are oriented at 45° with respect to the direction of the magnetic field at 0°. Ritz's approach is taken to solve the physical problem. In order to verify and compare the results obtained by the Ritz approach, an analysis using the finite element method was carried out. The rheological property of the MRE material at 0° and at 45° are determined experimentally, The studied elastomer is prepared by a mixture of silicone oil, RTV141A polymer, and 30% of iron particles of total mixture, the mixture obtained is mixed for about 15 minutes to obtain an elastomer paste with good homogenization. In order to develop a magnetorheological elastomer (MRE), this paste is injected into an aluminum mold and subjected to a magnetic field. In our work, we have chosen an ideal percentage of filling of 30%, to obtain the best characteristics of the MRE. The mechanical characteristics obtained by dynamic mechanical viscoanalyzer (DMA) are used in the two numerical approaches. The natural frequencies and the modal damping of the sandwich plate are calculated and discussed for various magnetic field intensities. The results obtained by the two methods are compared. These off‐axis anisotropic MRE structures could open up new opportunities in various fields of aeronautics, aerospace, mechanical engineering and civil engineering.

Keywords: hybrid smart sandwich plate, vibratory behavior, FEM, Ritz approach, MRE

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Authors: Xun Li, Haojie Wang

Abstract:

Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

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Authors: Vincent Iacobellis, Kamran Behdinan

Abstract:

A finite element cohesive zone model is used to predict the temperature dependent material properties of a polyimide matrix composite with unidirectional carbon fiber arrangement. The cohesive zone parameters have been obtained from previous research involving an atomistic-to-continuum multiscale simulation of the fiber-matrix interface using the bridging cell multiscale method. The goal of the research was to both investigate the effect of temperature change on the composite behavior with respect to transverse loading as well as the validate the use of cohesive parameters obtained from atomistic-to-continuum multiscale modeling to predict fiber-matrix interfacial cracking. From the multiscale model cohesive zone parameters (i.e. maximum traction and energy of separation) were obtained by modeling the interface between the coarse-grained polyimide matrix and graphite based carbon fiber. The cohesive parameters from this simulation were used in a cohesive zone model of the composite microstructure in order to predict the properties of the macroscale composite with respect to changes in temperature ranging from 21 ˚C to 316 ˚C. Good agreement was found between the microscale RUC model and experimental results for stress-strain response, stiffness, and material strength at low and high temperatures. Examination of the deformation of the composite through localized crack initiation at the fiber-matrix interface also agreed with experimental observations of similar phenomena. Overall, the cohesive zone model was shown to be both effective at modeling the composite properties with respect to transverse loading as well as validated the use of cohesive zone parameters obtained from the multiscale simulation.

Keywords: cohesive zone model, fiber-matrix interface, microscale damage, multiscale modeling

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Authors: Lei Qi, Rongxin Yan, Lichen Sun

Abstract:

With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

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Authors: Mayada Attia Ibrahim

Abstract:

Evaluating and developing the electroplating production process is a key challenge in this type of process. The process is influenced by several factors such as process parameters, process costs, and production environments. Analyzing and optimizing all these factors together requires extensive analytical techniques that are not available in real-case industrial entities. This paper presents a practice-based framework for the evaluation and optimization of some of the crucial factors that affect the costs and production times associated with this type of process, energy costs, material costs, and product flow times. The proposed approach uses Design of Experiments, Discrete-Event Simulation, and Theory of Constraints were respectively used to identify the most significant factors affecting the production process and simulate a real production line to recognize the effect of these factors and assign possible bottlenecks. Several scenarios are generated as corrective strategies for improving the production line. Following that, data envelopment analysis CCR input-oriented DEA model is used to evaluate and optimize the suggested scenarios.

Keywords: electroplating process, simulation, design of experiment, performance optimization, theory of constraints, data envelopment analysis

Procedia PDF Downloads 83