Search results for: simultaneous perturbation stochastic approximation

Authors: Chokri Slim

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The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.

Keywords: stationarity, cointegration, dynamic models, causality, VECM models

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Muhammad Umair, Tanveer Hussain, Khubab Shaker, Yasir Nawab, Muhammad Maqsood, Madeha Jabbar

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The term comfort is defined as 'the absence of unpleasantness or discomfort' or 'a neutral state compared to the more active state'. Comfort mainly is of three types: sensorial (tactile) comfort, psychological comfort and thermo-physiological comfort. Thermophysiological comfort is determined by the air permeability and moisture management properties of the garment. The aim of this study was to investigate the effect of weave structure and picking sequence on the comfort properties of woven fabrics. Six woven fabrics with two different weave structures i.e. 1/1 plain and 3/1 twill and three different picking sequences: (SPI, DPI, 3PI) were taken as input variables whereas air permeability, wetting time, wicking behavior and overall moisture management capability (OMMC) of fabrics were taken as response variables and a comparison is made of the effect of weave structure and picking sequence on the response variables. It was found that fabrics woven in twill weave design and with simultaneous triple pick insertion (3PI) give significantly better air permeability, shorter wetting time and better water spreading rate, as compared to plain woven fabrics and those with double pick insertion (DPI) or single pick insertion (SPI). It could be concluded that the thermophysiological comfort of woven fabrics may be significantly improved simply by selecting a suitable weave design and picking sequence.

Keywords: air permeability, picking sequence, thermophysiological comfort, weave design

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Authors: A. Parra Parra, M. Vlasova, P. A. Marquez, M. Kakazey, M. C. Resendiz Gonzalez

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The work of water treatment plants from various sources of pollution includes a biological treatment stage using activated sludge. Due to the large volume of toxic activated sludge waste (WAS) generated and soil contamination during its storage, WAS disposal technologies are being continuously developed. The most common is the carbonization of WAS. The carbonization products are various forms of ordered and disordered carbon material having different reactivity. The aim of this work was to study the reduction process of Fe₂O₃ mixed with activated sludge waste (WAS). It could be assumed that the simultaneous action of the WAS thermal decomposition process, accompanied by the formation of reactive nano-carbon, with carbothermal reduction of the Fe₂O₃, will permit intensify reduction of metal oxide up to stage of metal and iron carbide formation. The studies showed that the temperature treatment in the region of (800-1000) °C for 1 hour under conditions of oxygen deficiency is accompanied by the occurrence of reactions: Fe₂O₃ → Fe₃O₄ → FeO → Fe, which are typical for the metallurgical process of iron smelting, but less energy-intensive. Depending on the ratio of the WAS - Fe₂O₃ components and the temperature-time regime of reduction of iron oxide, it is possible to distinguish the stages of the predominant formation of ferromagnetic compounds, cast iron, and iron carbide. The results indicated the promise of using WAS as a metals oxide reducing agent and obtaining of ceramic-based on metal carbides.

Keywords: carbothermal reduction, Fe₂O₃, FeₓOᵧ-C, waste activated sludge

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Ouahiba Taamallah, Tarek Litim

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The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Tawfiq Chekifi, Brahim Dennai, Rachid Khelfaoui

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Over the last few decades, modeling immiscible fluids such as oil and water have been a classical research topic. Droplet-based microfluidics presents a unique platform for mixing, reaction, separation, dispersion of drops, and numerous other functions. For this purpose, several devices were studied, as well as microfluidic oscillator. The latter was obtained from wall attachment microfluidic amplifiers using a feedback loop from the outputs to the control inputs, nevertheless this device have not well used for microdrops applications. In this paper, we suggest a numerical CFD study of a microfluidic oscillator with two different lengths of feedback loop. In order to produce simultaneous microdrops of gasoil on water, a typical geometry that includes double T-junction is connected to the fluidic oscillator. The generation of microdrops is computed by volume-of-fluid method (VOF). Flow oscillations of microdrops were triggered by the Coanda effect of jet flow. The aim of work is to obtain a high oscillation frequency in output of this passive device, the influence of hydrodynamics and physics parameters on the microdrops frequency in the output of our microsystem is also analyzed, The computational results show that, the length of feedback loop, applied pressure on T-junction and interfacial tension have a significant effect on the dispersion of microdrops and its oscillation frequency. Across the range of low Reynold number, the microdrops generation and its dynamics have been accurately controlled by adjusting applying pressure ratio of two phases.

Keywords: fluidic oscillator, microdrops manipulation, VOF (volume of fluid method), microfluidic oscillator

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Authors: Adel H.El-Afandy, Abd Alrahman Embaby, Mona A. El Harairey

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Abu Marw area is located in the southeastern part of the Eastern Desert, about 150km south east of Aswan. Abu Marw area is mainly covered by late Proterozoic igneous and metamorphic rocks. These basement rocks are nonconformably overlain by late Cretaceous Nubian sandstones in the western and northern parts of the areas. Abu Marw granitoid batholiths comprises a co-magmatic calc alkaline I type peraluminous suite of rocks ranging in composition from tonalite, granodiorite, monzogranite, syenogranite to alkali feldspar granite. The studied tonalite and granodiorite samples have ΣREE lower than the average REE values (250ppm) of granitic rocks, while the monzogranite, syenogranite and alkali feldspar granite samples have ΣREE above the average REE values of granitic rocks. Chondrite-normalized REE patterns of the considered granites display a gull-wing shape, characterized by large to moderately fractionated patterns and high LREE relative to the MREE and HREE contents. Furthermore, the studied rocks have a steadily decreasing Eu/Eu* values from the tonalite to the alkali feldspar granite with simultaneous increase in the ΣREE contents. The average U contents in different granitic rocks.

Keywords: granite, rare earth element, radioactivity, Abu Marw, south eastern desert

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Authors: A. Zarei, M. Porkhalili, B. Gholamhosseini

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In this experiment, sixty Hy-Line (W-36) laying hens were selected in 40weeks of age. Experimental diets were consumed for 12 weeks duration by them. The experimental design was completely randomized block included four treatments and each of them with five replications and three sample in each replicate. Treatments were as follow: Basal diet+probiotic, basal diet + prebiotic and basal diet+probiotic+ prebiotic. Performance traits were measured such as: hen production, egg weight, feed intake, feed conversion ratio ,shell thickness, shell strength, shell weight, hough unit, yolk color, and yolk cholesterol. Blood parameters like; Ca, cholesterol, triglyceride, VLDL and antibody titer and so morphological of intestine were determined. At the end of experimental period, after sampling from end of cecum, bacterial colony count was measured. Results showed; shell weight was significantly greater than other treatments in probiotic treatment.Yolk weight in prebiotic treatment was significantly greater than other treatments. The ratio of height of villi to dept of crypt cells in duodenum, jejunum, ileum and secum in prebiotic treatment were significantly greater. Results from the other traits were not significant between treatments, however there were totally good results in other traits with simultaneous usage of probiotic and prebiotic.

Keywords: probiotic, prebiotic, laying hens, performance, blood parameters, intestine morphology

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Authors: Purnendu Bose, Jyoti Kainthola

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Due to recent advances in illumination technology, artificially illuminated algal-bacterial photo bioreactors are now a potentially feasible option for simultaneous and comprehensive organic carbon and nutrients removal from secondary treated domestic sewage. The experiments described herein were designed to determine the extent of nutrient uptake in photo bioreactors through algal assimilation. Accordingly, quasi steady state data on algal photo bioreactor performance was obtained under 20 different conditions. Results indicated that irrespective of influent N and P levels, algal biomass recycling resulted in superior performance of algal photo bioreactors in terms of both N and P removals. Further, both N and P removals were positively related to the growth of algal biomass in the reactor. Conditions in the reactor favouring greater algal growth also resulted in greater N and P removals. N and P removals were adversely impacted in reactors with low algal concentrations due to the inability of the algae to grow fast enough under the conditions provided. Increasing algal concentrations in reactors over a certain threshold value through higher algal biomass recycling was also not fruitful, since algal growth slowed under such conditions due to reduced light availability due to algal ‘self-shading’. It was concluded that N removals greater than 80% at high influent N concentrations is not possible with the present reactor configuration. Greater than 80% N removals may however be possible in similar reactors if higher light intensity is provided. High P removal is possible only if the influent N: P ratio in the reactor is aligned closely with the algal stoichiometric requirements for P.

Keywords: nutrients, algae, photo, bioreactor

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

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Authors: D. Geringswald, B. Hintze

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The miniaturization of circuits is advancing. During chip manufacturing, structures are filled for example by metal organic chemical vapor deposition (MOCVD). Since this process reaches its limits in case of very high aspect ratios, the use of alternatives such as the atomic layer deposition (ALD) is possible, requiring the extension of existing coating systems. However, it is an unsolved question to what extent MOCVD can achieve results similar as an ALD process. In this context, this work addresses the characterization of a metal organic vapor deposition of titanium nitride. Based on the current state of the art, the film properties coating thickness, sheet resistance, resistivity, stress and chemical composition are considered. The used setting parameters are temperature, plasma gas ratio, plasma power, plasma treatment time, deposition time, deposition pressure, number of cycles and TDMAT flow. The derived process instructions for unstructured wafers and inside a structure with high aspect ratio include lowering the process temperature and increasing the number of cycles, the deposition and the plasma treatment time as well as the plasma gas ratio of hydrogen to nitrogen (H₂:N₂). In contrast to the current process configuration, the deposited titanium nitride (TiN) layer is more uniform inside the entire test structure. Consequently, this paper provides approaches to employ the MOCVD for structures with increasing aspect ratios.

Keywords: ALD, high aspect ratio, PE-MOCVD, TiN

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Authors: Patrick J. Kerpan, Ryan C. Koop, Margaret M. Walker, Chris P. Swan

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The User Datagram Protocol (UDP) multicast is a vital part of data center networking that is being left out of major cloud computing providers' network infrastructure. Enterprise users rely on multicast, and particularly UDP multicast to create and connect vital business operations. For example, UPD makes a variety of business functions possible from simultaneous content media updates, High-Performance Computing (HPC) grids, and video call routing for massive open online courses (MOOCs). Essentially, UDP multicast's technological slight is causing a huge effect on whether companies choose to use (or not to use) public cloud infrastructure as a service (IaaS). Allowing the ‘chatty’ UDP multicast protocol inside a cloud network could have a serious impact on the performance of the cloud as a whole. Cloud IaaS providers solve the issue by disallowing all UDP multicast. But what about enterprise use cases for multicast applications in organizations that want to move to the cloud? To re-allow multicast traffic, enterprises can build a layer 3 - 7 network over the top of a data center, private cloud, or public cloud. An overlay network simply creates a private, sealed network on top of the existing network. Overlays give complete control of the network back to enterprise cloud users the freedom to manage their network beyond the control of the cloud provider’s firewall conditions. The same logic applies if for users who wish to use IPsec or BGP network protocols inside or connected into an overlay network in cloud IaaS.

Keywords: cloud computing, protocols, UDP multicast, virtualization

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Authors: Dharamashi Rabari, Anand Patel

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n-Butanol can be regarded as a potential biofuel. Being resistive to corrosion and having high calorific value, butanol is a very attractive energy source as opposed to ethanol. By fermentation process called ABE (acetone, butanol, ethanol), bio-butanol can be produced. ABE carried out mostly by bacteria Clostridium acetobutylicum. The major drawback of the process is the butanol concentration higher than 10 g/L, delays the growth of microbes resulting in a low yield. It indicates the simultaneous separation of butanol from the fermentation broth. Two hydrophobic Ionic Liquids (ILs) 1-butyl-1-methylpiperidinium bis (trifluoromethylsulfonyl)imide [bmPIP][Tf₂N] and 1-hexyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [hmim][Tf₂N] were chosen. The binary interaction parameters for both ternary systems i.e. [bmPIP][Tf₂N] + water + n-butanol and [hmim][Tf₂N] + water +n-butanol were taken from the literature that was generated by NRTL model. Particle swarm optimization (PSO) with the isothermal sum rate (ISR) method was used to optimize the cost of liquid-liquid extractor. For [hmim][Tf₂N] + water +n-butanol system, PSO shows 84% success rate with the number of stages equal to eight and solvent flow rate equal to 461 kmol/hr. The number of stages was three with 269.95 kmol/hr solvent flow rate for [bmPIP][Tf₂N] + water + n-butanol system. Moreover, both ILs were very efficient as the loss of ILs in raffinate phase was negligible.

Keywords: particle swarm optimization, isothermal sum rate method, success rate, extraction

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Authors: L. Al Ahmad, C. Latrille, D. Hainos, D. Blanc, M. Clausse

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A two-dimensional finite volume axisymmetric model is developed to predict the simultaneous heat and mass transfers during the drying of industrial sludge. The simulations were run using COMSOL-Multiphysics 3.5a. The input parameters of the numerical model were acquired from a preliminary experimental work. Results permit to establish correlations describing the evolution of the various parameters as a function of the drying temperature and the sludge water content. The selection and coupling of the equation are validated based on the drying kinetics acquired experimentally at a temperature range of 45-65 °C and absolute pressure range of 200-1000 mbar. The model, incorporating the heat and mass transfer mechanisms at different operating conditions, shows simulated values of temperature and water content. Simulated results are found concordant with the experimental values, only at the first and last drying stages where sludge shrinkage is insignificant. Simulated and experimental results show that sludge drying is favored at high temperatures and low pressure. As experimentally observed, the drying time is reduced by 68% for drying at 65 °C compared to 45 °C under 1 atm. At 65 °C, a 200-mbar absolute pressure vacuum leads to an additional reduction in drying time estimated by 61%. However, the drying rate is underestimated in the intermediate stage. This rate underestimation could be improved in the model by considering the shrinkage phenomena that occurs during sludge drying.

Keywords: industrial sludge drying, heat transfer, mass transfer, mathematical modelling

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Authors: Javier Delgado-Gonzaga, Wilfrido Rivera, David Juárez-Romero

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Cooling and water purification are processes that have contributed to the economic and social development of the modern world. However, these processes require a significant amount of energy globally. Nowadays, absorption heat pumps have been studied with great interest since they are capable of producing cooling and/or purifying water from low-temperature energy sources such as industrial waste heat or renewable energy. In addition, absorption heat pumps require negligible amounts of electricity for their operation and generally use working fluids that do not represent a risk to the environment. The objective of this work is to evaluate a system that integrates an absorption heat transformer and an absorption cooling system to produce fresh water and cooling from a low-temperature heat source. Both cycles operate with the working pair LiBr-H2O. The integration is possible through the interaction of the LiBr-H2O solution streams between both cycles and also by recycling heat from the absorption heat transformer to the absorption cooling system. Mathematical models were developed to compare the performance of four different configurations. The results showed that the configuration in which the hottest streams of LiBr-H2O solution preheated the coldest streams in the economizers of both cycles was one that achieved the best performance. The interaction of the solution currents and the heat recycling analyzed in this work serves as a record of the possibilities of integration between absorption cycles for cogeneration.

Keywords: absorption heat transformer, absorption cooling system, water desalination, integrated system

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Authors: Dawei Cai, Yuya Tokuda

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The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

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Authors: A. Mohammed, A. Babatunde

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This study investigated the integrated removal of heavy metals, organic matter and nitrogen from landfill leachate using a novel laboratory scale constructed wetland system. The main objectives of this study were: (i) to assess the overall effectiveness of the constructed wetland system for treating landfill leachate; (ii) to examine the interactions and impact of key leachate constituents (heavy metals, organic matter and nitrogen) on the overall removal dynamics and efficiency. The constructed wetland system consisted of four stages operated in tidal flow and anoxic conditions. Results obtained from 215 days of operation have demonstrated extraordinary heavy metals removal up to 100%. Analysis of the physico- chemical data reveal that the controlling factors for metals removal were the anoxic condition and the use of the novel media (dewatered ferric sludge which is a by-product of drinking water treatment process) as the main substrate in the constructed wetland system. Results show that the use of the ferric sludge enhanced heavy metals removal and brought more flexibility to simultaneous nitrification and denitrification which occurs within the microbial flocs. Furthermore, COD and NH₄-N were effectively removed in the system and this coincided with enhanced aeration in the 2nd and 3rd stages of the constructed wetland system. Overall, the results demonstrated that the ferric dewatered sludge constructed wetland system would be an effective solution for integrated removal of pollutants from landfill leachates.

Keywords: constructed wetland, ferric dewatered sludge, heavy metals, landfill leachate

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: Yuri Kitahara

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Background: Cognitive reappraisal refers to an emotion regulation strategy in which one changes the interpretation of emotion-eliciting events. Numerous studies show that cognitive reappraisal is associated with mental health and better social functioning. However the examination of the predictive factors of adaptive emotion regulation remains as an issue. The present study examined the factors contributing to the habitual use of cognitive reappraisal, with a focus on emotional awareness and working memory. Methods: Data was collected from 30 junior high school students, using a Japanese version of the Emotion Regulation Questionnaire (ERQ), the Levels of Emotional Awareness Scale for Children (LEAS-C), and N-back task. Results: A positive correlation between emotional awareness and cognitive reappraisal was observed in the high-working-memory group (r = .54, p < .05), whereas no significant relationship was found in the low-working-memory group. In addition, the results of the analysis of variance (ANOVA) showed a significant interaction between emotional awareness and working memory capacity (F(1, 26) = 7.74, p < .05). Subsequent analysis of simple main effects confirmed that high working memory capacity significantly increases the use of cognitive reappraisal for high-emotional-awareness subjects, and significantly decreases the use of cognitive reappraisal for low-emotional-awareness subjects. Discussion: These results indicate that under the condition when one has an adequate ability for simultaneous processing of information, explicit understanding of emotion would contribute to adaptive cognitive emotion regulation. The findings are discussed along with neuroscientific claims.

Keywords: cognitive reappraisal, emotional awareness, emotion regulation, working memory

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Authors: Reza Sabbagh, Linda Hasanovich, Aleksey Baldygin, David S. Nobes, Prashant R. Waghmare

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The capillary filling process is significantly important to study for numerous applications such as the under filling of the material in electronic packaging or liquid hydrocarbons seepage through porous structure. The approximation of the fluid being Newtonian, i.e., linear relationship between the shear stress and deformation rate cannot be justified in cases where the extent of non-Newtonian behavior of liquid governs the surface driven transport, i.e., capillarity action. In this study, the capillary action of a non-Newtonian fluid is not only analyzed, but also the modified generalized theoretical analysis for the capillary transport is proposed. The commonly observed three regimes: surface forces dominant (travelling air-liquid interface), developing flow (viscous force dominant), and developed regimes (interfacial, inertial and viscous forces are comparable) are identified. The velocity field along each regime is quantified with Newtonian and non-Newtonian fluid in square shaped vertically oriented channel. Theoretical understanding of capillary imbibition process, particularly in the case of Newtonian fluids, is relied on the simplified assumption of a fully developed velocity profile which has been revisited for developing a modified theory for the capillary transport of non-Newtonian fluids. Furthermore, the development of the velocity profile from the entrance regime to the developed regime, for different power law fluids, is also investigated theoretically and experimentally.

Keywords: capillary, non-Newtonian flow, shadowgraphy, rising velocity

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov

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The development of active and stable catalysts without noble metals for low temperature oxidation of exhaust gases remains a significant challenge. The purpose of this study is to determine the influence of the preparation method on the catalytic activity of the supported copper-manganese mixed oxides in terms of VOCs oxidation. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and acetates and the possibilities for CO, CH3OH and dimethyl ether (DME) oxidation were evaluated using continuous flow equipment with a four-channel isothermal stainless steel reactor. Effect of the support, Cu/Mn mole ratio, heat treatment of the precursor and active component loading were investigated. Highly active alumina supported Cu-Mn catalysts for CO and VOCs oxidation were synthesized. The effect of preparation conditions on the activity behavior of the catalysts was discussed. The synergetic interaction between copper and manganese species increases the activity for complete oxidation over mixed catalysts. Type of support, calcination temperature and active component loading along with catalyst composition are important factors, determining catalytic activity. Cu/Mn molar ratio of 1:5, heat treatment at 450oC and 20 % active component loading are the best compromise for production of active catalyst for simultaneous combustion of CO, CH3OH and DME.

Keywords: copper-manganese catalysts, CO, VOCs oxidation, exhaust gases

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Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

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In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

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Authors: Naouel Zoghlami

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Spoken-word recognition involves the simultaneous activation of potential word candidates which compete with each other for final correct recognition. In continuous speech, the activation-competition process gets more complicated due to speech reductions existing at word boundaries. Lexical processing is more difficult in L2 than in L1 because L2 listeners often lack phonetic, lexico-semantic, syntactic, and prosodic knowledge in the target language. In this study, we investigate the on-line lexical segmentation hypotheses that French listeners of L2 English form and then revise as subsequent perceptual evidence is revealed. Our purpose is to shed further light on the processes of L2 spoken-word recognition in context and better understand L2 listening difficulties through a comparison of skilled and unskilled reactions at the point where their working hypothesis is rejected. We use a variant of the gating experiment in which subjects transcribe an English sentence presented in increments of progressively greater duration. The spoken sentence was “And this amazing athlete has just broken another world record”, chosen mainly because it included common reductions and phonetic features in English, such as elision and assimilation. Our preliminary results show that there is an important difference in the manner in which proficient and less-proficient L2 listeners handle connected speech. Less-proficient listeners delay recognition of words as they wait for lexical and syntactic evidence to appear in the gates. Further statistical results are currently being undertaken.

Keywords: gating paradigm, spoken word recognition, online lexical segmentation, L2 listening

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Authors: Wassima El Mofid, Svetlozar Ivanov, Andreas Bund

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The increasing requirements for high power and energy lithium ion batteries have led to the development of several classes of positive electrode materials. Among those one promising material is LiNixMnyCo1−x−yO2 due to its high reversible capacity and remarkable cycling performance. Further structural stabilization and improved electrochemical performance of this class of cathode materials can be achieved by cationic substitution to a transition metal such as Al, Mg, Cr, etc. The current study discusses a novel NMC type material obtained by simultaneous cationic substitution of the cobalt which is a toxic element, with aluminum and iron. A compound with the composition LiNi0.6Mn0.2Co0.15Al0.025Fe0.025O2 (NMCAF) was synthesized by the self-combustion method using sucrose as fuel. The material has a layered α-NaFeO2 type structure with a good hexagonal ordering. Rietveld refinement analysis of the XRD patterns revealed a very low cationic mixing compared to the non-substituted material LiNi0.6Mn0,2Co0.2O2 suggesting a structural stabilization. Galvanostatic cycling measurements indicate improved electrochemical performance after the metal substitution. An initial discharge capacity of about 190 mAh.g−1 at slow rate (C/20), and a good cycling stability even at moderately faster rates (C/5 and C) have been observed. The long term cycling displayed a capacity retention of about 90% after 10 cycles.

Keywords: cationic substitution, lithium ion batteries, positive electrode material, self-combustion synthesis method

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Authors: Dweepabiswa Bagchi, D. V. Senthilkumar

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Numerous studies have typically demonstrated the devastation of invasions on an isolated ecosystem or, at most, a network of dispersively coupled similar ecosystem patches. Using such a simplistic 2-D network model, one can only consider dispersal coupling and inter-species trophic interactions. However, in a realistic ecosystem, numerous species co-exist and interact trophically and non-trophically in groups of 2 or more. Even different types of dispersal can introduce complexity in an ecological network. Therefore, a more accurate representation of actual ecosystems (or ecological networks) is a complex network consisting of motifs formed by two or more interacting species. Here, the apropos structure of the network should be multiplex or multi-layered. Motifs between different patches or species should be identical within the same layer and vary from one layer to another. This study investigates three distinct ecological multiplex networks facing invasion from one or more external species. This work determines and quantifies the criteria for the increased extinction risk of these networks. The dynamical states of the network with high extinction risk, i.e., the danger states, and those with low extinction risk, i.e., the resistive network states, are both subsequently identified. The analysis done in this study further quantifies the persistence of the entire network corresponding to simultaneous changes in the strength of invasive dispersal and higher-order trophic and non-trophic interactions. This study also demonstrates that the ecosystems enjoy an inherent advantage against invasions due to their multiplex network structure.

Keywords: increased ecosystem persistence, invasion on ecosystems, multiplex networks, non-trophic interactions

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Authors: Abhishek Agarwal, Manoj Sarda, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

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Propagation of fire through a non-air conditioned railway compartment is studied by virtue of numerical simulations. Simultaneous computational fire dynamics equations, such as Navier-Stokes, lumped species continuity, overall mass and energy conservation, and heat transfer are solved using finite volume based (for radiation) and finite difference based (for all other equations) solver, Fire Dynamics Simulator (FDS). A single coupe with an eight berth occupancy is used to establish the numerical model, followed by the selection of a three coupe system as the fundamental unit of the locomotive compartment. Heat Release Rate Per Unit Area (HRRPUA) of the initial fire is varied to consider a wide range of compartmental fires. Parameters, such as air inlet velocity relative to the locomotive at the windows, the level of interaction with the ambiance and closure of middle berth are studied through a wide range of numerical simulations. Almost all the loss of lives and properties due to fire breakout can be attributed to the direct or indirect exposure to flames or to the inhalation of toxic gases and resultant suffocation due to smoke and soot. Therefore, the temporal stature of fire and smoke are reported for each of the considered cases which can be used in the present or extended form to develop guidelines to be followed in case of a fire breakout.

Keywords: fire dynamics, flame propagation, locomotive fire, soot flow pattern, non-air-conditioned coaches

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