Search results for: diurnal temperature cycle model

Authors: Stefanie Jeanette Huber

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This paper explores the relevance and implications of preferences for housing services on house price fluctuations through the lens of an overlapping generation’s model. The model implies that an economy whose agents have lower preferences for housing services is characterized with lower expenditure shares on housing services and will tend to experience more frequent and more volatile housing bubbles. These model predictions are tested empirically in the companion paper Housing Booms and Busts - Convergences and Divergences across OECD countries. Between 1970 - 2013, countries who spend less on housing services as a share of total income experienced significantly more housing cycles and the associated housing boom-bust cycles were more violent. Finally, the model is used to study the impact of rental subsidies and help-to-buy schemes on rational housing bubbles. Rental subsidies are found to contribute to the control of housing bubbles, whereas help-to- buy scheme makes the economy more bubble-prone.

Keywords: housing bubbles, housing booms and busts, preference for housing services, expenditure shares for housing services, rental and purchase subsidies

Procedia PDF Downloads 283

Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Behzad Ali Khan, M. Zubair Akbar Qureshi

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The article analyzes the Darcy Forchheimer 2D Hybrid ferrofluid. The flow of a Hybrid ferrofluid is made due to an unsteady porous channel. The classical liquid water is treated as a based liquid. The flow in the permeable region is characterized by the Darcy-Forchheimer relation. Heat transfer phenomena are studied during the flow. The transformation of a partial differential set of equations into a strong ordinary differential frame is formed through appropriate variables. The numerical Shooting Method is executed for solving the simplified set of equations. In addition, a numerical analysis (ND-Solve) is utilized for the convergence of the applied technique. The influence of some flow model quantities like Pr (Prandtle number), r (porous medium parameter), F (Darcy-porous medium parameter), Re (Reynolds number), Pe (Peclet number) on velocity and temperature field are scrutinized and studied through sketches. Certain physical factors like f ''(η) (skin friction coefficient) and θ^'(η) (rate of heat transfer) are first derived and then presented through tables.

Keywords: darcy forcheimer, hybrid ferro fluid, porous medium, porous channel

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: Ly. Benbahouche

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Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics. The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments. The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device). Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt

Procedia PDF Downloads 300

Authors: Soudabeh Shemehsavar

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In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

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Authors: Muhanad Al-Jubouri

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A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

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Authors: Traore Papa Touty

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This article presents a numerical method for determining the thermal conductivity of local materials, kapok plaster and tow plaster. It consists of heating the front face of a wall made from these two materials and at the same time insulating its rear face. We simultaneously study the curves of the evolution of the heat flux density as a function of time on the rear face and the evolution of the temperature gradient as a function of time between the heated face and the insulated face. Thermal conductivity is obtained when reaching a steady state when the evolution of the heat flux density and the temperature gradient no longer depend on time. The results showed that the theoretical value of thermal conductivity is obtained when the material has reached its equilibrium state. And the values obtained for different values of the convective exchange coefficients are appreciably equal to the experimental value.

Keywords: thermal conductivity, numerical method, heat exchange coefficient, transitional regime

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Authors: Pablo J. Valverde, Jaime E. Fernandez

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This paper shows under which conditions public corruption can emerge. The theoretical model includes variables such as the public employee wage (w), a control corruption parameter (c), and the group size of interactions (GS) between clusters of public officers and contractors. The system behavior is analyzed using phase diagrams based on combinations of such parameters (c, w, GS). Numerical simulations are implemented in order to contrast analytic results based on Nash equilibria of the theoretical model. Major findings include the functional relationship between wages and network topology, which attempts to reduce the emergence of corrupt behavior.

Keywords: public corruption, game theory, complex systems, Nash equilibrium.

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Authors: Maha Bakakri, Rachid Tadili, Fatiha Lemmini

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Morocco is one of the few countries that have kept their traditional crafts, despite the competition of modern industry and its impact on manual labor. Therefore the optimization of energy consumption becomes an obligation and this is the purpose of this document. In this work we present some characteristics of the furnace studied, its operating principle and the experimental measurements of the evolutions of the temperatures inside and outside the walls of the furnace, values which will be used later in the calculation of its thermal losses. In order to determine the major source of the thermal losses of the furnace we have established the heat balance of the furnace. The energy consumed, the useful energy and the thermal losses through the walls and the chimney of the furnace are calculated thanks to the experimental measurements which we realized for several firings. The results show that the energy consumption of this type of furnace is very high and that the main source of energy loss is mainly due to the heat losses of the combustion gases that escape from the furnace by the chimney while the losses through the walls are relatively small. it have opted for energy recovery as a solution where we can recover some of the heat lost through the use of a heat exchanger system using a double tube introduced into the flue gas exhaust stack compartment. The study on the heat recovery system is presented and the heat balance inside the exchanger is established. In this paper we also present the numerical modeling of heat transfer by conduction through the walls of the furnace. A numerical model has been established based on the finite volume method and the double scan method. It makes it possible to determine the temperature profile of the furnace and thus to calculate the thermal losses of its walls and to deduce the thermal losses due to the combustion gases. Validation of the model is done using the experimental measurements carried out on the furnace. The results obtained in this work, relating to the energy consumed during the operation of the furnace are important and are part of the energy efficiency framework that has become a key element in global energy policies. It is the fastest and cheapest way to solve energy, environmental and economic security problems.

Keywords: energy cunsumption, energy recovery, modeling, energy eficiency

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Authors: Azizul Baten, Kamrul Hossain, Abdullah-Al-Zabir

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The objective of this study is to develop an appropriate stochastic frontier secondary schools efficiency model by ICT Intervention and to examine the impact of ICT challenges on secondary schools efficiency in the Sylhet division in Bangladesh using stochastic frontier analysis. The Translog stochastic frontier model was found an appropriate than the Cobb-Douglas model in secondary schools efficiency by ICT Intervention. Based on the results of the Cobb-Douglas model, it is found that the coefficient of the number of teachers, the number of students, and teaching ability had a positive effect on increasing the level of efficiency. It indicated that these are related to technical efficiency. In the case of inefficiency effects for both Cobb-Douglas and Translog models, the coefficient of the ICT lab decreased secondary school inefficiency, but the online class in school was found to increase the level of inefficiency. The coefficients of teacher’s preference for ICT tools like multimedia projectors played a contributor role in decreasing the secondary school inefficiency in the Sylhet division of Bangladesh. The interaction effects of the number of teachers and the classrooms, and the number of students and the number of classrooms, the number of students and teaching ability, and the classrooms and teaching ability of the teachers were recorded with the positive values and these have a positive impact on increasing the secondary school efficiency. The overall mean efficiency of urban secondary schools was found at 84.66% for the Translog model, while it was 83.63% for the Cobb-Douglas model. The overall mean efficiency of rural secondary schools was found at 80.98% for the Translog model, while it was 81.24% for the Cobb-Douglas model. So, the urban secondary schools performed better than the rural secondary schools in the Sylhet division. It is observed from the results of the Tobit model that the teacher-student ratio had a positive influence on secondary school efficiency. The teaching experiences of those who have 1 to 5 years and 10 years above, MPO type school, conventional teaching method have had a negative and significant influence on secondary school efficiency. The estimated value of σ-square (0.0625) was different from Zero, indicating a good fit. The value of γ (0.9872) was recorded as positive and it can be interpreted as follows: 98.72 percent of random variation around in secondary school outcomes due to inefficiency.

Keywords: efficiency, secondary schools, ICT, stochastic frontier analysis

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Authors: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Siewchuiang Sia, Gimcheong Tan

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Bacteriophages are the most abundant and genetically diverse living entities on earth; they help in regulating and maintaining microbial diversity and balance in its natural ecosystem. In this study, the infectivity of SFN6B tailed phage was investigated in various water samples. Host bacteria (Shigella flexneri) were spiked in sterilized environmental and domestic water samples, followed by SFN6B treatment. Two incubation conditions were selected for this study, 37 oC and room temperature. S. flexneri and SFN6B viability were monitored hourly for consecutive 7 hours and extended viability study for consecutive 4 days. Absorbance of all bacteria spiked water samples were taken to monitor the bacteria count. Results showed reduction in the absorbance of the SFN6B treated water sample as compared to negative control, indicating reduction in bacterial count either due to negative growth or lysis by the lytic bacteriophage. Consistent with the result, SFN6B titer increases for first two days. However, prolong incubation of these cultures reaches equilibrium, between phage and bacteria. Temperature and water sample source also influence the interaction between S. flexneri and SFN6B. Stronger interaction was observed in 37oC as compared to room temperature, where higher bacteria count and phage titer increase were recorded. Availability of nutrient in water sample also plays a crucial role in the interaction between bacteria and phage. Higher nutrient level, such as lake and river waters were observed to give better infectivity and viability of both bacteria and phage as compared to tab water. It is believed that S. flexneri continue to remain viable and able to grow in the present of SFN6B bacteriophage, but the number was closely regulated by surrounding phages. This allows better understanding of the characteristics of SFN6B that could serve as the basis for future studies and applications.

Keywords: bacteriophage, Shigella flexneri, infection, microbial diversity

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Authors: Ozgu Hafizoglu

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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

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Authors: A. Bayat, R. Bello-Mendoza, D. G. Wareham

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Two major categories of green waste are fruit and vegetable (FV) waste and garden and yard (GY) waste. Although, anaerobic digestions (AD) is able to manage FV waste; there is less confidence in the conditions for AD to handle GY wastes (grass, leaves, trees and bush trimmings); mainly because GY contains lignin and other recalcitrant organics. GY in the dry state (TS ≥ 15 %) can be digested at mesophilic temperatures; however, little methane data has been reported under thermophilic conditions, where conceivably better methane yields could be achieved. In addition, it is suspected that at lower solids concentrations, the methane yield could be increased. As such, the aim of this research is to find the temperature and solids concentration conditions that produce the most methane; under two different temperature regimes (mesophilic, thermophilic) and three solids states (i.e. 'dry', 'semi-dry' and 'wet'). Twenty liters of GY waste was collected from a public park located in the northern district in Tehran. The clippings consisted of freshly cut grass as well as dry branches and leaves. The GY waste was chopped before being fed into a mechanical blender that reduced it to a paste-like consistency. An initial TS concentration of approximately 38 % was achieved. Four hundred mL of anaerobic inoculum (average total solids (TS) concentration of 2.03 ± 0.131 % of which 73.4% were volatile solid (VS), soluble chemical oxygen demand (sCOD) of 4.59 ± 0.3 g/L) was mixed with the GY waste substrate paste (along with distilled water) to achieve a TS content of approximately 20 %. For comparative purposes, approximately 20 liters of FV waste was ground in the same manner as the GY waste. Since FV waste has a much higher natural water content than GY, it was dewatered to obtain a starting TS concentration in the dry solid-state range (TS ≥ 15 %). Three samples were dewatered to an average starting TS concentration of 32.71 %. The inoculum was added (along with distilled water) to dilute the initial FV TS concentrations down to semi-dry conditions (10-15 %) and wet conditions (below 10 %). Twelve 1-L batch bioreactors were loaded simultaneously with either GY or FV waste at TS solid concentrations ranging from 3.85 ± 1.22 % to 20.11 ± 1.23 %. The reactors were sealed and were operated for 30 days while being immersed in water baths to maintain a constant temperature of 37 ± 0.5 °C (mesophilic) or 55 ± 0.5 °C (thermophilic). A maximum methane yield of 115.42 (L methane/ kg VS added) was obtained for the GY thermophilic-wet AD combination. Methane yield was enhanced by 240 % compared to the GY waste mesophilic-dry condition. The results confirm that high temperature regimes and small solids concentrations are conditions that enhance methane yield from GY waste. A similar trend was observed for the anaerobic digestion of FV waste. Furthermore, a maximum value of VS (53 %) and sCOD (84 %) reduction was achieved during the AD of GY waste under the thermophilic-wet condition.

Keywords: anaerobic digestion, thermophilic, mesophilic, total solids concentration

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Authors: Yoonsuh Jung, Steven N. MacEachern

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Check loss function is used to define quantile regression. In the prospect of cross validation, it is also employed as a validation function when underlying truth is unknown. However, our empirical study indicates that the validation with check loss often leads to choosing an over estimated fits. In this work, we suggest a modified or L2-adjusted check loss which rounds the sharp corner in the middle of check loss. It has a large effect of guarding against over fitted model in some extent. Through various simulation settings of linear and non-linear regressions, the improvement of check loss by L2 adjustment is empirically examined. This adjustment is devised to shrink to zero as sample size grows.

Keywords: cross-validation, model selection, quantile regression, tuning parameter selection

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Authors: Shihab Ibrahim

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Geopolymer binders as an alternative binder system to ordinary Portland cement are the focus of the past 2 decades of researches. In order to eliminate CO2 emission by cement manufacturing and utilizing construction waste as a source material, clean waste clay bricks which are the waste from Levent Brick factory was activated with a mixture of sodium hydroxide and sodium silicate solution. 12 molarity of sodium hydroxide solution was used and the ratio of sodium silicate to sodium hydroxide was 2.5. Alkaline solution to clay brick powder ratio of 0.35, 0.4, 0.45, and 0.5 was studied. Alkaline solution to powder ratio of 0.4 was found to be optimum ratio to have the same workability as ordinary Portland cement paste. Compressive strength of the clay brick based geopolymer paste samples was evaluated under different curing temperatures and curing durations. One day compressive strength of 57.3 MPa after curing at 85C for 24 hours was obtained which was higher than 7 days compressive strength of ordinary Portland cement paste. The highest compressive strength 71.4 MPa was achieved at seventh day age for the geopolymer paste samples cured at 85C for 24 hours. It was found that 8 hour curing at elevated temperature 85C, is sufficient to get 96% of total strength. 37.4 MPa strength at seventh day of clay brick based geopolymer sample cured at room temperature was achieved. Water absorption around 10% was found for clay brick based geopolymer samples cured at different temperatures with compare to 9.14% water absorption of ordinary Portland cement paste. The clay brick based geopolymer binder can have the potentiality to be used as an alternative binder to Portland cement in a case that the heat treatment provided. Further studies are needed in order to produce the binder in a way that can harden and gain strength without any elevated curing.

Keywords: construction and demolition waste, geopolymer, clay brick, compressive strength.

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Authors: Mueller Jann, Hoffmann Christian Hugo

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Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

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Authors: Kalimi Trinadh, Corinne Nouveau, A. S. Khanna, Karanveer S. Aneja, K. Ram Mohan Rao

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This study concerns improving the corrosion resistance of low alloy steel after plasma nitriding performed at variable time and temperature. Nitriding carried out in the temperature range of 450-550ᵒC for a various time period of 1-8 hrs. at 500Pa in a glow discharge plasma of H₂ and N₂ (80:20). The substrate was kept biased negatively at 250V. Following nitriding the X-ray diffraction studies shown that the phases formed were mainly γ′ (Fe₄N) and ε (Fe₂₋₃N). The ε (Fe₂₋₃N) phase found to be the dominating phase. Cross sections of the samples under scanning electron microscope point analyses revealed the presence of nitrogen in the surface region. For the assessment of corrosion resistance property, potentiodynamic polarization tests were performed in 3.5% NaCl solution. It has been shown that the plasma nitriding significantly improved the corrosion resistance when compared to the as-received steel. Furthermore, it has also been found that nitriding for 6h has more corrosion resistance than nitriding for the 8h duration. The hardness of the nitrided samples was measured by Vicker’s microhardness tester. The hardness of the nitrided steel was found to be improved much above the hardness of the steel in the as-received condition. It was found to be around two-fold of the initial hardness.

Keywords: corrosion, steel, plasma nitriding, X-ray diffraction

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Authors: JoonHo Lee, KyoJin An, JunSu Kim, Young-Chul Park

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In this study, the fluid flow characteristics and performance numerical study through CFD model of the Non-split quick coupling for flow control in hydraulic system equipment for the aerospace business group focused to predict. In this study, we considered turbulence models for the application of Computational Fluid Dynamics for the CFD model of the Non-split Quick Coupling for aerospace business. In addition to this, the adequacy of the CFD model were verified by comparing with standard value. Based on this analysis, accurate the fluid flow characteristics can be predicted. It is, therefore, the design of the fluid flow characteristic contribute the reliability for the Quick Coupling which is required in industries on the basis of research results.

Keywords: CFD, FEM, quick coupling, turbulence

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: primavera P6, SQL, Power BI, EVM, integration management

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Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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Authors: Tuğçe Kiper Elibol, İbrahim Uslan, Mehmet Ali Guler, Murat Buyuk, Uğur Yolum

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According to the FAA report, 142603 bird strikes were reported for a period of 24 years, between 1990 – 2013. Bird strike with aerospace structures not only threaten the flight security but also cause financial loss and puts life in danger. The statistics show that most of the bird strikes are happening with the nose and the leading edge of the wings. Also, a substantial amount of bird strikes is absorbed by the jet engines and causes damage on blades and engine body. Crash proof designs are required to overcome the possibility of catastrophic failure of the airplane. Using computational methods for bird strike analysis during the product development phase has considerable importance in terms of cost saving. Clearly, using simulation techniques to reduce the number of reference tests can dramatically affect the total cost of an aircraft, where for bird strike often full-scale tests are considered. Therefore, development of validated numerical models is required that can replace preliminary tests and accelerate the design cycle. In this study, to verify the simulation parameters for a bird strike analysis, several different numerical options are studied for an impact case against a primitive structure. Then, a representative bird mode is generated with the verified parameters and collided against the leading edge of a training aircraft wing, where each structural member of the wing was explicitly modeled. A nonlinear explicit dynamics finite element code, LS-DYNA was used for the bird impact simulations. SPH methodology was used to model the behavior of the bird. Dynamic behavior of the wing superstructure was observed and will be used for further design optimization purposes.

Keywords: bird impact, bird strike, finite element modeling, smoothed particle hydrodynamics

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Authors: Fatima Ammari, Meriem Chenouf

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Synthesis of gold nano particles has attracted much attention since the pioneering discovery of the high catalytic activity of supported gold nano particles in the reaction of CO oxidation at low temperature. In this research field, we used Na-montmorillonite for gold nanoparticles stabilization; different loading percentage 1, 2 and 5%. The gold nano particles were obtained using chemical reduction method using NaBH4 as reductant agent. The obtained gold nano particles Au-mont stabilized in Na-montmorillonite were used as catalysts for reduction of 4-nitrophenol to aminophenol with sodium borohydride at room temperature. The UV-Vis results confirm directly the gold nano particles formation. The XRD and N2 adsorption results showed the formation of gold nano particles in the pores of montmorillonite with an average size of 5 nm obtained on samples with 2%Au-mont. The gold particles size increased with the increase of gold loading percentage. The reduction reaction of 4-nitrophenol into 4-aminophenol with NaBH4 catalyzed by Au-Na-montmorillonite catalyst exhibits remarkably a high activity; the reaction was completed within 9 min for 1Au-mont and within 3 min for 2Au-mont.

Keywords: chemical reduction, gold, montmorillonite, nano particles, 4-nitrophenol

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Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

Abstract:

Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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Authors: Mikhail Gritskevich, Sebastian Hohenstein

Abstract:

The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer

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Authors: Paolo Pietro Biancone

Abstract:

The spread of Islamic financial instruments is an opportunity to offer integration for the immigrant population and to attract, through the specific products, the richness of sovereign funds from the "Arab" countries. However, it is important to consider the possibility of comparing a traditional finance model, which in recent times has given rise to many doubts, with an "alternative" finance model, where the ethical aspect arising from religious principles is very important.

Keywords: banks, Europe, Islamic finance, Italy

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Júlia Vilafranca Molero, Cinta Gascon, Arianna Vitiello, Tina Baloh

Abstract:

It has long been recognized that the creation of any teaching content can be enhanced if the development process follows a pre-defined approach, which is often referred to as an instructional design methodology. These methodologies typically define a number of stages, or phases, that an educator should undertake to help ensure the quality of the final teaching content that is developed. In this paper, we present an instructional design methodology that is focused specifically on the introduction of blended resources into a heretofore bricks-and-mortar course. To achieve this, research was undertaken concerning a range of models of instructional design, as well as literature covering some of the key challenges and “pain points” of blending. Following this, our model, the BL-5D model, is presented, which incorporates some key questions at each stage of this five-stage methodology to guide the development process. Finally, a discussion of some of the key themes and issues that have been uncovered in this work is presented, as well as a template for a blended learning case study that emerged from this approach.

Keywords: blended learning, challenges of blended learning, design methodologies, instructional design

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Authors: Jia-Jang Wu

Abstract:

The objective of this research is to develop a general technique so that one may predict the dynamic behaviour of a three-dimensional scale crane model subjected to time-dependent moving point forces by means of conventional finite element computer packages. To this end, the whole scale crane model is divided into two parts: the stationary framework and the moving substructure. In such a case, the dynamic responses of a scale crane model can be predicted from the forced vibration responses of the stationary framework due to actions of the four time-dependent moving point forces induced by the moving substructure. Since the magnitudes and positions of the moving point forces are dependent on the relative positions between the trolley, moving substructure and the stationary framework, it can be found from the numerical results that the time histories for the moving speeds of the moving substructure and the trolley are the key factors affecting the dynamic responses of the scale crane model.

Keywords: moving load, moving substructure, dynamic responses, forced vibration responses

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Authors: M. Veeresham

Abstract:

The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties

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