Search results for: hydrodynamic coefficients

Authors: Yi-Chun Kuo, Jo-Chieh Lin

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The objective of a supply chain strategy is to reduce waste and increase efficiency to attain cost benefits, and to guarantee supply chain flexibility when facing the ever-changing market environment in order to meet customer requirements. Strategy implementation aims to fulfill common goals and attain benefits by integrating upstream and downstream enterprises, sharing information, conducting common planning, and taking part in decision making, so as to enhance the overall performance of the supply chain. With the rise of outsourcing and globalization, the increasing dependence on suppliers and customers and the rapid development of information technology, the complexity and uncertainty of the supply chain have intensified, and supply chain vulnerability has surged, resulting in adverse effects on supply chain performance. Thus, this study aims to use supply chain vulnerability as a moderating variable and apply structural equation modeling (SEM) to determine the relationships among supply chain strategy, supply chain integration, and supply chain performance, as well as the moderating effect of supply chain vulnerability on supply chain performance. The data investigation of this study was questionnaires which were collected from the management level of enterprises in Taiwan and China, 149 questionnaires were received. The result of confirmatory factor analysis shows that the path coefficients of supply chain strategy on supply chain integration and supply chain performance are positive (0.497, t= 4.914; 0.748, t= 5.919), having a significantly positive effect. Supply chain integration is also significantly positively correlated to supply chain performance (0.192, t = 2.273). The moderating effects of supply chain vulnerability on supply chain strategy and supply chain integration to supply chain performance are significant (7.407; 4.687). In Taiwan, 97.73% of enterprises are small- and medium-sized enterprises (SMEs) focusing on receiving original equipment manufacturer (OEM) and original design manufacturer (ODM) orders. In order to meet the needs of customers and to respond to market changes, these enterprises especially focus on supply chain flexibility and their integration with the upstream and downstream enterprises. According to the observation of this research, the effect of supply chain vulnerability on supply chain performance is significant, and so enterprises need to attach great importance to the management of supply chain risk and conduct risk analysis on their suppliers in order to formulate response strategies when facing emergency situations. At the same time, risk management is incorporated into the supply chain so as to reduce the effect of supply chain vulnerability on the overall supply chain performance.

Keywords: supply chain integration, supply chain performance, supply chain vulnerability, structural equation modeling

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Authors: Ali Kadivar, Kaveh Niayesh

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This work simulates the voltage drop and resistance of the explosion of copper wires of diameters 25, 40, and 100 µm surrounded by 1 bar nitrogen exposed to a 150 A current and before plasma formation. The absorption of electrical energy in an exploding wire is greatly diminished when the plasma is formed. This study shows the importance of considering radiation and heat conductivity in the accuracy of the circuit simulations. The radiation of the dense plasma formed on the wire surface is modeled with the Net Emission Coefficient (NEC) and is mixed with heat conductivity through PLASIMO® software. A time-transient code for analyzing wire explosions driven by a slow current rise rate is developed. It solves a circuit equation coupled with one-dimensional (1D) equations for the copper electrical conductivity as a function of its physical state and Net Emission Coefficient (NEC) radiation. At first, an initial voltage drop over the copper wire, current, and temperature distribution at the time of expansion is derived. The experiments have demonstrated that wires remain rather uniform lengthwise during the explosion and can be simulated utilizing 1D simulations. Data from the first stage are then used as the initial conditions of the second stage, in which a simplified 1D model for high-Mach-number flows is adopted to describe the expansion of the core. The current was carried by the vaporized wire material before it was dispersed in nitrogen by the shock wave. In the third stage, using a three-dimensional model of the test bench, the streamer threshold is estimated. Electrical breakdown voltage is calculated without solving a full-blown plasma model by integrating Townsend growth coefficients (TdGC) along electric field lines. BOLSIG⁺ and LAPLACE databases are used to calculate the TdGC at different mixture ratios of nitrogen/copper vapor. The simulations show both radiation and heat conductivity should be considered for an adequate description of wire resistance, and gaseous discharges start at lower voltages than expected due to ultraviolet radiation and the exploding shocks, which may have ionized the nitrogen.

Keywords: exploding wire, Townsend breakdown mechanism, streamer, metal vapor, shock waves

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Jagadish Rao Padubidri, Mehak Bhandary, Sowmya J. Rao

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Introduction: The significance of the human foot and its measurements in identifying an individual has been proved a lot of times by different studies in different geographical areas and its association to the stature and gender of the individual has been justified by many researches. In our study we have used different foot measurements including the length, width, malleol height and navicular height for establishing its association to stature and gender and to find out its accuracy. The purpose of this study is to show the relation of foot measurements with stature and gender, and to derive Multiple and Logistic regression equations for stature and gender estimation in South Indian population. Materials and Methods: The subjects for this study were 200 South Indian students out of which 100 were females and 100 were males, aged between 18 to 24 years. The data for the present study included the stature, foot length, foot breath, foot malleol height, foot navicular height of both right and left foot. Descriptive statistics, T-test and Pearson correlation coefficients were derived between stature, gender and foot measurements. The stature was estimated from right and left foot measurements for both male and female South Indian population using multiple regression analysis and logistic regression analysis for gender estimation. Results: The means, standard deviation, stature, right and left foot measurements and T-test in male population were higher than in females. LFL (Left foot length) is more than RFL (Right Foot length) in male groups, but in female groups the length of both foot are almost equal [RFL=226.6, LFL=227.1]. There is not much of difference in means of RFW (Right foot width) and LFW (Left foot width) in both the genders. Significant difference were seen in mean values of malleol and navicular height of right and left feet in male gender. No such difference was seen in female subjects. Conclusions: The study has successfully demonstrated the correlation of foot length in stature estimation in all the three study groups in both right and left foot. Next in parameters are Foot width and malleol height in estimating stature among male and female groups. Navicular height of both right and left foot showed poor relationship with stature estimation in both male and female groups. Multiple regression equations for both right and left foot measurements to estimate stature were derived with standard error ranging from 11-12 cm in males and 10-11 cm in females. The SEE was 5.8 when both male and female groups were pooled together. The logistic regression model which was derived to determine gender showed 85% accuracy and 92.5% accuracy using right and left foot measurements respectively. We believe that stature and gender can be estimated with foot measurements in South Indian population.

Keywords: foot length, gender, stature, South Indian

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Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

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The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

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Authors: Yao Cheng, Weihua Zhang

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Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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Authors: Olubukayo-Opeyemi Oyetayo, Oscar Mendez-Lucio, Andreas Bender, Hans Kiefer

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The thermal melting curve of a protein provides information on its conformational stability and could provide cues on its aggregation behavior. Naturally-occurring osmolytes have been shown to improve the thermal stability of most proteins in a concentration-dependent manner. They are therefore commonly employed as additives in therapeutic protein purification and formulation. A number of intertwined and seemingly conflicting mechanisms have been put forward to explain the observed stabilizing effects, the most prominent being the preferential exclusion mechanism. We attempted to probe and summarize molecular mechanisms for thermal stabilization of a monoclonal antibody (mAb) by developing quantitative structure-activity relationships using a rationally-selected library of 120 osmolyte-like compounds in the polyhydric alcohols, amino acids and methylamines classes. Thermal stabilization potencies were experimentally determined by thermal shift assays based on differential scanning fluorimetry. The cross-validated QSAR model was developed by partial least squares regression using descriptors generated from Molecular Operating Environment software. Careful evaluation of the results with the use of variable importance in projection parameter (VIP) and regression coefficients guided the selection of the most relevant descriptors influencing mAb thermal stability. For the mAb studied and at pH 7, the thermal stabilization effects of tested compounds correlated positively with their fractional polar surface area and inversely with their fractional hydrophobic surface area. We cannot claim that the observed trends are universal for osmolyte-protein interactions because of protein-specific effects, however this approach should guide the quick selection of (de)stabilizing compounds for a protein from a chemical library. Further work with a large variety of proteins and at different pH values would help the derivation of a solid explanation as to the nature of favorable osmolyte-protein interactions for improved thermal stability. This approach may be beneficial in the design of novel protein stabilizers with optimal property values, especially when the influence of solution conditions like the pH and buffer species and the protein properties are factored in.

Keywords: thermal stability, monoclonal antibodies, quantitative structure-activity relationships, osmolytes

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Authors: Aaron Herve Mbwe Mbissik, Lotfi Khiari, Otmane Raji, Abdellatif Elghali, Abdelkarim Lajili, Muhammad Ouabid, Martin Jemo, Jean-Louis Bodinier

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Potassium (K) is an essential macronutrient for plant growth, helping to regulate several physiological and metabolic processes. Evaporite-related potash salts, mainly sylvite minerals (K chloride or KCl), are the principal source of K for the fertilizer industry. However, due to the high potash-supply risk associated with its considerable price fluctuations and uneven geographic distribution for most agriculture-based developing countries, the development of alternative sources of fertilizer K is imperative to maintain adequate crop yield, reduce yield gaps, and food security. Alkaline Igneous rocks containing significant K-rich silicate minerals such as K feldspar are increasingly seen as the best alternative available. However, these rocks may require to be hydrothermally treatment to enhance the release of potassium. In this study, we evaluate the fertilizing capacity of raw and hydrothermally treated K-bearing silicate rocks from different areas in Morocco. The effectiveness of rock powders was tested in a greenhouse experiment using ryegrass (Lolium multiflorum) by comparing them to a control (no K added) and to a conventional fertilizer (muriate of potash: MOP or KCl). The trial was conducted in a randomized complete block design with three replications, and plants were grown on K-depleted soils for three growing cycles. To achieve our objective, in addition to the analysis of the muriate response curve and the different biomasses, we also examined three necessary coefficients, namely: the K uptake, then apparent K recovery (AKR), and the relative K efficiency (RKE). The results showed that based on the optimum economic rate of MOP (230 kg.K.ha⁻¹) and the optimum yield (44 000 kg.K.ha⁻¹), the efficiency of K silicate rocks was as high as that of MOP. Although the plants took up only half of the K supplied by the powdered rock, the hydrothermal material was found to be satisfactory, with a biomass value reaching the optimum economic limit until the second crop cycle. In comparison, the AKR of the MOP (98.6%) and its RKE in the 1st cycle were higher than our materials: 39% and 38%, respectively. Therefore, the raw and hydrothermal materials mixture could be an appropriate solution for long-term agronomic use based on the obtained results.

Keywords: K-uptake, AKR, RKE, K-bearing silicate rock, MOP

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Authors: V. Radulescu, S. Dumitru

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Introduction: Determination of the temperature field inside a fluid in motion has many practical issues, especially in the case of turbulent flow. The phenomenon is greater when the solid walls have a different temperature than the fluid. The turbulent heat and mass transfer have an essential role in case of the thermal pollution, as it was the recorded during the damage of the Thermoelectric Power-plant Oradea (closed even today). Basic Methods: Solving the theoretical turbulent thermal pollution represents a particularly difficult problem. By using the semi-empirical theories or by simplifying the made assumptions, based on the experimental measurements may be assured the elaboration of the mathematical model for further numerical simulations. The three zones of flow are analyzed separately: the vicinity of the solid wall, the turbulent transition zone, and the turbulent core. For each area are determined the distribution law of temperature. It is determined the dependence of between the Stanton and Prandtl numbers with correction factors, based on measurements experimental. Major Findings/Results: The limitation of the laminar thermal substrate was determined based on the theory of Landau and Levice, using the assumption that the longitudinal component of the velocity pulsation and the pulsation’s frequency varies proportionally with the distance to the wall. For the calculation of the average temperature, the formula is used a similar solution as for the velocity, by an analogous mediation. On these assumptions, the numerical modeling was performed with a gradient of temperature for the turbulent flow in pipes (intact or damaged, with cracks) having 4 different diameters, between 200-500 mm, as there were in the Thermoelectric Power-plant Oradea. Conclusions: It was made a superposition between the molecular viscosity and the turbulent one, followed by addition between the molecular and the turbulent transfer coefficients, necessary to elaborate the theoretical and the numerical modeling. The concept of laminar boundary layer has a different thickness when it is compared the flow with heat transfer and that one without a temperature gradient. The obtained results are within the margin of error of 5%, between the semi-empirical classical theories and the developed model, based on the experimental data. Finally, it is obtained a general correlation between the Stanton number and the Prandtl number, for a specific flow (with associated Reynolds number).

Keywords: experimental measurements, numerical correlations, thermal pollution through pipelines, turbulent thermal flow

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Miguel A. Figueroa, José A. Lara-Ramos, Miguel A. Mueses

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Pharmaceutical residues are a section of emerging contaminants of anthropogenic origin that are present in a myriad of waters with which human beings interact daily and are starting to affect the ecosystem directly. Conventional waste-water treatment systems are not capable of degrading these pharmaceutical effluents because their designs cannot handle the intermediate products and biological effects occurring during its treatment. That is why it is necessary to hybridize conventional waste-water systems with non-conventional processes. In the specific case of an ozonation process, its efficiency highly depends on a perfect dispersion of ozone, long times of interaction of the gas-liquid phases and the size of the ozone bubbles formed through-out the reaction system. In order to increase the efficiency of these parameters, the use of a modified flotation cell has been proposed recently as a reactive system, which is used at an industrial level to facilitate the suspension of particles and spreading gas bubbles through the reactor volume at a high rate. The objective of the present work is the development of a mathematical model that can closely predict the kinetic rates of reactions taking place in the flotation cell at an experimental scale by means of identifying proper reaction mechanisms that take into account the modified chemical and hydrodynamic factors in the FeO-catalyzed Ozonation of Diclofenac aqueous solutions in a flotation cell. The methodology is comprised of three steps: an experimental phase where a modified flotation cell reactor is used to analyze the effects of ozone concentration and loading catalyst over the degradation of Diclofenac aqueous solutions. The performance is evaluated through an index of utilized ozone, which relates the amount of ozone supplied to the system per milligram of degraded pollutant. Next, a theoretical phase where the reaction mechanisms taking place during the experiments must be identified and proposed that details the multiple direct and indirect reactions the system goes through. Finally, a kinetic model is obtained that can mathematically represent the reaction mechanisms with adjustable parameters that can be fitted to the experimental results and give the model a proper physical meaning. The expected results are a robust reaction rate law that can simulate the improved results of Diclofenac mineralization on water using the modified flotation cell reactor. By means of this methodology, the following results were obtained: A robust reaction pathways mechanism showcasing the intermediates, free-radicals and products of the reaction, Optimal values of reaction rate constants that simulated Hatta numbers lower than 3 for the system modeled, degradation percentages of 100%, TOC (Total organic carbon) removal percentage of 69.9 only requiring an optimal value of FeO catalyst of 0.3 g/L. These results showed that a flotation cell could be used as a reactor in ozonation, catalytic ozonation and photocatalytic ozonation processes, since it produces high reaction rate constants and reduces mass transfer limitations (Ha > 3) by producing microbubbles and maintaining a good catalyst distribution.

Keywords: advanced oxidation technologies, iron oxide, emergent contaminants, AOTS intensification

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Authors: M. Gomez, A. Molina

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The concept of brand equity in the wine tourism area is an interesting topic to explore the factors that determine it. The aim of this study is to address this gap by investigating wine tourism destinations brand equity, and understanding the impact that the denomination of origin (DO) brand image and the destination image have on brand equity. Managing and monitoring the branding of wine tourism destinations is crucial to attract tourist arrivals. The multiplicity of stakeholders involved in the branding process calls for research that, unlike previous studies, adopts a broader perspective and incorporates an internal and an external perspective. Therefore, this gap by comparing managers’ and visitors’ approaches to wine tourism destination brand equity has been addressed. A survey questionnaire for data collection purposes was used. The hypotheses were tested using winery managers and winery visitors, each leading a different position relative to the wine tourism destination brand equity. All the interviews were conducted face-to-face. The survey instrument included several scales related to DO brand image, destination image, and wine tourism destination brand equity. All items were measured on seven-point Likert scales. Partial least squares was used to analyze the accuracy of scales, the structural model, and multi-group analysis to identify the differences in the path coefficients and to test the hypotheses. The results show that the positive influence of DO brand image on wine tourism destination brand equity is stronger for wineries than for visitors, but there are no significant differences between the two groups. However, there are significant differences in the positive effect of destination brand image on both wine tourism destination brand equity and DO brand image. The results of this study are important for consultants, practitioners, and policy makers. The gap between managers and visitors calls for the development of a number of campaigns to enhance the image that visitors hold and, thus, increase tourist arrivals. Events such as wine gatherings and gastronomic symposiums held at universities and culinary schools and participation in business meetings can enhance the perceptions and in turn, the added value, brand equity of the wine tourism destinations. The images of destinations and DOs can help strengthen the brand equity of the wine tourism destinations, especially for visitors. Thus, the development and reinforcement of favorable, strong, and unique destination associations and DO associations are important to increase that value. Joint campaigns are advisable to enhance the images of destinations and DOs and, as a consequence, the value of the wine tourism destination brand.

Keywords: brand equity, managers, visitors, wine tourism

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Ali Kadivar, Kaveh Niayesh

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This report summarizes a simulation-based approach to estimate the current interruption behavior of a fuse element utilized in a DC network protecting battery banks under different stresses. Due to internal resistance of the battries, the short circuit current in very close to the nominal current, and it makes the fuse designation tricky. The base configuration considered in this report consists of five fuse units in parallel. The simulations are performed using a multi-physics software package, COMSOL® 5.6, and the necessary material parameters have been calculated using two other software packages.The first phase of the simulation starts with the heating of the fuse elements resulted from the current flow through the fusing element. In this phase, the heat transfer between the metallic strip and the adjacent materials results in melting and evaporation of the filler and housing before the aluminum strip is evaporated and the current flow in the evaporated strip is cut-off, or an arc is eventually initiated. The initiated arc starts to expand, so the entire metallic strip is ablated, and a long arc of around 20 mm is created within the first 3 milliseconds after arc initiation (v_elongation = 6.6 m/s. The final stage of the simulation is related to the arc simulation and its interaction with the external circuitry. Because of the strong ablation of the filler material and venting of the arc caused by the melting and evaporation of the filler and housing before an arc initiates, the arc is assumed to burn in almost pure ablated material. To be able to precisely model this arc, one more step related to the derivation of the transport coefficients of the plasma in ablated urethane was necessary. The results indicate that an arc current interruption, in this case, will not be achieved within the first tens of milliseconds. In a further study, considering two series elements, the arc was interrupted within few milliseconds. A very important aspect in this context is the potential impact of many broken strips parallel to the one where the arc occurs. The generated arcing voltage is also applied to the other broken strips connected in parallel with arcing path. As the gap between the other strips is very small, a large voltage of a few hundred volts generated during the current interruption may eventually lead to a breakdown of another gap. As two arcs in parallel are not stable, one of the arcs will extinguish, and the total current will be carried by one single arc again. This process may be repeated several times if the generated voltage is very large. The ultimate result would be that the current interruption may be delayed.

Keywords: DC network, high current / low SC fuses, FEM simulation, paralle fuses

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Authors: Avdhesh K. Sharma

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Key, in the development of energy-efficient micro-scale heat exchanger devices, is to select large heat transfer surface to volume ratio without much expanse on re-circulated pumps. The increased interest in short heat exchanger (SHE) is due to accessibility of advanced technologies for manufacturing of micro-tubes in range of 1 micron m - 1 mm. Such SHE using micro-tubes are highly effective for high flux heat transfer technologies. Nanofluids, are used to enhance the thermal conductivity of re-circulated coolant and thus enhances heat transfer rate further. Higher viscosity associated with nanofluid expands more pumping power. Thus, there is a trade-off between heat transfer rate and pressure drop with geometry of micro-tubes. Herein, a novel design of short counter flow heat exchanger (SCFHE) using non-circular micro-tubes flooded with CuO-water nanofluid is conceptualized by varying the ratio of surface area to cross-sectional area of micro-tubes. A framework for comparative analysis of SCFHE using micro-tubes non-circular shape flooded by CuO-water nanofluid is presented. In SCFHE concept, micro-tubes having various geometrical shapes (viz., triangular, rectangular and trapezoidal) has been arranged row-wise to facilitate two aspects: (1) allowing easy flow distribution for cold and hot stream, and (2) maximizing the thermal interactions with neighboring channels. Adequate distribution of rows for cold and hot flow streams enables above two aspects. For comparative analysis, a specific volume or cross-section area is assigned to each elemental cell (which includes flow area and area corresponds to half wall thickness). A specific volume or cross-section area is assumed to be constant for each elemental cell (which includes flow area and half wall thickness area) and variation in surface area is allowed by selecting different geometry of micro-tubes in SCFHE. Effective thermal conductivity model for CuO-water nanofluid has been adopted, while the viscosity values for water based nanofluids are obtained empirically. Correlations for Nusselt number (Nu) and Poiseuille number (Po) for micro-tubes have been derived or adopted. Entrance effect is accounted for. Thermal and hydrodynamic performances of SCFHE are defined in terms of effectiveness and pressure drop or pumping power, respectively. For defining the overall performance index of SCFHE, two links are employed. First one relates heat transfer between the fluid streams q and pumping power PP as (=qj/PPj); while another link relates effectiveness eff and pressure drop dP as (=effj/dPj). For analysis, the inlet temperatures of hot and cold streams are varied in usual range of 20dC-65dC. Fully turbulent regime is seldom encountered in micro-tubes and transition of flow regime occurs much early (i.e., ~Re=1000). Thus, Re is fixed at 900, however, the uncertainty in Re due to addition of nanoparticles in base fluid is quantified by averaging of Re. Moreover, for minimizing error, volumetric concentration is limited to range 0% to ≤4% only. Such framework may be helpful in utilizing maximum peripheral surface area of SCFHE without any serious severity on pumping power and towards developing advanced short heat exchangers.

Keywords: CuO-water nanofluid, non-circular micro-tubes, performance index, short counter flow heat exchanger

Procedia PDF Downloads 209

Authors: Hamza Javar Magnier, Robin Curtis

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There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

Procedia PDF Downloads 359

Authors: Ali Pourkazemi

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The transient radar method (TRM) is one of the non-destructive methods that was introduced by authors a few years ago. The transient radar method can be classified as a wave-based non destructive testing (NDT) method that can be used in a wide frequency range. Nevertheless, it requires a narrow band, ranging from a few GHz to a few THz, depending on the application. As a time-of-flight and real-time method, TRM can measure the electromagnetic properties of the sample under test not only quickly and accurately, but also blindly. This means that it requires no prior knowledge of the sample under test. For multi-layer structures, TRM is not only able to detect changes related to any parameter within the multi-layer structure but can also measure the electromagnetic properties of each layer and its thickness individually. Although the temperature, humidity, and general environmental conditions may affect the sample under test, they do not affect the accuracy of the Blind TRM algorithm. In this paper, the electromagnetic properties as well as the thickness of the individual building insulation materials - as a single-layer structure - are measured experimentally. Finally, the correlation between the reflection coefficients and some other technical parameters such as sound insulation, thermal resistance, thermal conductivity, compressive strength, and density is investigated. The sample to be studied is 30 cm x 50 cm and the thickness of the samples varies from a few millimeters to 6 centimeters. This experiment is performed with both biostatic and differential hardware at 10 GHz. Since it is a narrow-band system, high-speed computation for analysis, free-space application, and real-time sensor, it has a wide range of potential applications, e.g., in the construction industry, rubber industry, piping industry, wind energy industry, automotive industry, biotechnology, food industry, pharmaceuticals, etc. Detection of metallic, plastic pipes wires, etc. through or behind the walls are specific applications for the construction industry.

Keywords: transient radar method, blind electromagnetic geometrical parameter extraction technique, ultrafast nondestructive multilayer dielectric structure characterization, electronic measurement systems, illumination, data acquisition performance, submillimeter depth resolution, time-dependent reflected electromagnetic signal blind analysis method, EM signal blind analysis method, time domain reflectometer, microwave, milimeter wave frequencies

Procedia PDF Downloads 68

Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

Procedia PDF Downloads 177

Authors: Meiyan Gao, Zongmin Wang, Haibo Yang, Qiuhua Liang

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Under the background of global climate change and rapid development of modern urbanization, the frequency of climate disasters such as extreme precipitation in cities around the world is gradually increasing. In this paper, Hi-PIMS model is used to simulate the "720" flood in Zhengzhou, and the continuous stages of flood resilience are determined with the urban flood stages are divided. The flood resilience curve under the influence of multiple factors were determined and the urban flood toughness was evaluated by combining the results of resilience curves. The flood resilience of urban unit grid was evaluated based on economy, population, road network, hospital distribution and land use type. Firstly, the rainfall data of meteorological stations near Zhengzhou and the remote sensing rainfall data from July 17 to 22, 2021 were collected. The Kriging interpolation method was used to expand the rainfall data of Zhengzhou. According to the rainfall data, the flood process generated by four rainfall events in Zhengzhou was reproduced. Based on the results of the inundation range and inundation depth in different areas, the flood process was divided into four stages: absorption, resistance, overload and recovery based on the once in 50 years rainfall standard. At the same time, based on the levels of slope, GDP, population, hospital affected area, land use type, road network density and other aspects, the resilience curve was applied to evaluate the urban flood resilience of different regional units, and the difference of flood process of different precipitation in "720" rainstorm in Zhengzhou was analyzed. Faced with more than 1,000 years of rainstorm, most areas are quickly entering the stage of overload. The influence levels of factors in different areas are different, some areas with ramps or higher terrain have better resilience, and restore normal social order faster, that is, the recovery stage needs shorter time. Some low-lying areas or special terrain, such as tunnels, will enter the overload stage faster in the case of heavy rainfall. As a result, high levels of flood protection, water level warning systems and faster emergency response are needed in areas with low resilience and high risk. The building density of built-up area, population of densely populated area and road network density all have a certain negative impact on urban flood resistance, and the positive impact of slope on flood resilience is also very obvious. While hospitals can have positive effects on medical treatment, they also have negative effects such as population density and asset density when they encounter floods. The result of a separate comparison of the unit grid of hospitals shows that the resilience of hospitals in the distribution range is low when they encounter floods. Therefore, in addition to improving the flood resistance capacity of cities, through reasonable planning can also increase the flood response capacity of cities. Changes in these influencing factors can further improve urban flood resilience, such as raise design standards and the temporary water storage area when floods occur, train the response speed of emergency personnel and adjust emergency support equipment.

Keywords: urban flood resilience, resilience assessment, hydrodynamic model, resilience curve

Procedia PDF Downloads 38

Authors: Marouen Dghim, Mohsen Ferchichi

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The effect of synthetic jet actuation on the roll-up and the development of a wing tip vortex downstream a square-tipped rectangular wing was investigated experimentally using hotwire anemometry. The wing is equipped with a hallow cavity designed to generate a high aspect ratio synthetic jets blowing at an angles with respect to the spanwise direction. The structure of the wing tip vortex under the effect of fluidic actuation was examined at a chord Reynolds number Re_c=8×10^4. An extensive qualitative study on the effect of actuation on the spanwise pressure distribution at c⁄4 was achieved using pressure scanner measurements in order to determine the optimal actuation parameters namely, the blowing momentum coefficient, Cμ, and the non-dimensionalized actuation frequency, F^+. A qualitative study on the effect of actuation parameters on the spanwise pressure distribution showed that optimal actuation frequencies of the synthetic jet were found within the range amplified by both long and short wave instabilities where spanwise pressure coefficients exhibited a considerable decrease by up to 60%. The vortex appeared larger and more diffuse than that of the natural vortex case. Operating the synthetic jet seemed to introduce unsteadiness and turbulence into the vortex core. Based on the ‘a priori’ optimal selected parameters, results of the hotwire wake survey indicated that the actuation achieved a reduction and broadening of the axial velocity deficit. A decrease in the peak tangential velocity associated with an increase in the vortex core radius was reported as a result of the accelerated radial transport of angular momentum. Peak vorticity level near the core was also found to be largely diffused as a direct result of the increased turbulent mixing within the vortex. The wing tip vortex a exhibited a reduced strength and a diffused core as a direct result of increased turbulent mixing due to the presence of turbulent small scale vortices within its core. It is believed that the increased turbulence within the vortex due to the synthetic jet control was the main mechanism associated with the decreased strength and increased size of the wing tip vortex as it evolves downstream. A comparison with a ‘non-optimal’ case was included to demonstrate the effectiveness of selecting the appropriate control parameters. The Synthetic Jet will be operated at various actuation configurations and an extensive parametric study is projected to determine the optimal actuation parameters.

Keywords: flow control, hotwire anemometry, synthetic jet, wing tip vortex

Procedia PDF Downloads 435

Authors: M. Reza Hashemi, Chris Small, Scott Hayward

Abstract:

The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

Procedia PDF Downloads 115

Authors: José M. Liñeira Del Río, Ramón Rial, Khodor Nasser, María J.G. Guimarey

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The need to develop new lubricants that offer better anti-friction and anti-wear performance in internal combustion vehicles is one of the great challenges of lubrication in the automotive field. The addition of nanoparticles has emerged as a possible solution and, combined with the lubricating power of ionic liquids, may become one of the alternatives to reduce friction losses and wear of the contact surfaces in the conditions to which tribo-pairs are subjected, especially in the contact of the piston rings and the cylinder liner surface. In this study, the improvement in SAE 10W-40 engine oil tribological performance after the addition of magnesium oxide (MgO) nanoadditives and two different phosphonium-based ionic liquids (ILs) was investigated. The nanoparticle characterization was performed by means of transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The tribological properties, friction coefficients and wear parameters of the formulated oil modified with 0.01 wt.% MgO and 1 wt.% ILs compared with the neat 10W-40 oil were performed and analyzed using a ball-on-three-pins tribometer and a 3D optical profilometer, respectively. Further analysis on the worn surface was carried out by Raman spectroscopy and SEM microscopy, illustrating the formation of the protective IL and MgO tribo-films as hybrid additives. In friction tests with sliding steel-steel tribo-pairs, IL3-based hybrid nanolubricant decreased the friction coefficient and wear volume by 7% and 59%, respectively, in comparison with the neat SAE 10W-40, while the one based on IL1 only achieved a reduction of these parameters by 6% and 39%, respectively. Thus, the tribological characterization also revealed that the MgO and IL3 addition has a positive synergy over the commercial lubricant, adequately meeting the requirements for their use in internal combustion engines. In summary, this study has shown that the addition of ionic liquids to MgO nanoparticles can improve the stability and lubrication behavior of MgO nanolubricant and encourages more investigations on using nanoparticle additives with green solvents such as ionic liquids to protect the environment as well as prolong the lifetime of machinery. The improvement in the lubricant properties was attributed to the following wear mechanisms: the formation of a protective tribo-film and the ability of nanoparticles to fill out valleys between asperities, thereby effectively smoothing out the shearing surfaces.

Keywords: lubricant, nanoparticles, phosphonium-based ionic liquids, tribology

Procedia PDF Downloads 81

Authors: I. Wiedemann, A. R. Sharifi, A. Mählmeyer, C. Knorr

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A requirement for sperm motility is a morphologically intact flagellum with a central axoneme. The flagellar beating is caused by the varying activation and inactivation of dynein molecules which are located in the axoneme. DNAL4 (dynein, axonemal, light chain 4) is regarded as a possible functional candidate gene encoding a small subunit of the dyneins. In the present study, 5814bp of the porcine DNAL4 (GenBank Acc. No. AM284696.1, 6097 bp, 4 exons) were comparatively sequenced using three boars with a high motility (>68%) and three with a low motility (<60%). Primers were self-designed except for those covering exons 1, 2 and 3. Prior to sequencing, the PCR products were purified. Sequencing was performed with an ABI PRISM 3100 Genetic Analyzer using the BigDyeTM Terminator v3.1 Cycle Sequencing Reaction Kit. Finally, 23 SNPs were described and genotyped for 82 AI boars representing the breeds Piétrain, German Large White and German Landrace. The genotypes were used to assess possible associations with standard spermatological parameters (ejaculate volume, density, and sperm motility (undiluted (Motud), 24h (Mot1) and 48h (Mot2) after semen collection) that were regularly recorded on the AI station. The analysis included a total of 8,833 spermatological data sets which ranged from 2 to 295 sets per boar in five years. Only SNP g.1007A>G had a significant effect. Finally, the gene substitution effect using the following statistical model was calculated: Yijk= µ+αi+βj+αβij+b1Sijk+b2Aijk+b3T ijk + b4Vijk+b5(α*A)ijk +b6(β*A)ijk+b7(A*T)ijk+Uijk+eijk where Yijk is the semen characteristics, µ is the general mean, α is the main effect of breed, β is the main effect of season, S is the effect of SNP (g.1007A > G), A is the effect of age at semen collection, V is the effect of diluter, αβ, α*A, β*A, A*T are interactions between the fixed effects, b1-b7 are regression coefficients between y and the respective covariate, U is the random effect of repeated observation on animal and e is the random error. The results from the single marker regression analysis revealed highly significant effects (p < 0.0001) of SNP g.1007A > G on Mot1 resp. on Mot2, resulting in a marked reduction by 11.4% resp. 15.4%. Furthermore a loss of Motud by 4.6% was detected (p < 0.0178). Considering the SNP g.1007A > G as a main factor (dominant-recessive model), significant differences between genotypes AA and AG as well as AA and GG for Mot1 and Mot2 exist. For Motud there was a significant difference between AA and GG.

Keywords: association, DNAL4, porcine, sperm traits

Procedia PDF Downloads 458

Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

Procedia PDF Downloads 474

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 408

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

Procedia PDF Downloads 77

Authors: F. Mutelet, L. Cesari

Abstract:

Development of safer and environmentally friendly processes and products is needed to achieve sustainable production and consumption patterns. Ionic liquids, which are of great interest to the chemical and related industries because of their attractive properties as solvents, should be considered. Ionic liquids are comprised of an asymmetric, bulky organic cation and a weakly coordinating organic or inorganic anion. A large number of possible combinations allows for the ability to ‘fine tune’ the solvent properties for a specific purpose. Physical and chemical properties of ionic liquids are not only influenced by the nature of the cation and the nature of cation substituents but also by the polarity and the size of the anion. These features infer to ionic liquids numerous applications, in organic synthesis, separation processes, and electrochemistry. Separation processes required a good knowledge of the behavior of organic compounds with ionic liquids. Gas chromatography is a useful tool to estimate the interactions between organic compounds and ionic liquids. Indeed, retention data may be used to determine infinite dilution thermodynamic properties of volatile organic compounds in ionic liquids. Among others, the activity coefficient at infinite dilution is a direct measure of solute-ionic liquid interaction. In this work, infinite dilution thermodynamic properties of volatile organic compounds in specific bis(trifluoromethylsulfonyl)imide based ionic liquids measured by gas chromatography is presented. It was found that apolar compounds are not miscible in this family of ionic liquids. As expected, the solubility of organic compounds is related to their polarity and hydrogen-bond. Through activity coefficients data, the performance of these ionic liquids was evaluated for different separation processes (benzene/heptane, thiophene/heptane and pyridine/heptane). Results indicate that ionic liquids may be used for the extraction of polar compounds (aromatics, alcohols, pyridine, thiophene, tetrahydrofuran) from aliphatic media. For example, 1-benzylpyridinium bis(trifluoromethylsulfonyl) imide and 1-cyclohexylmethyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide are more efficient for the extraction of aromatics or pyridine from aliphatics than classical solvents. Ionic liquids with long alkyl chain length present important capacity values but their selectivity values are low. In conclusion, we have demonstrated that specific bis(trifluoromethylsulfonyl)imide based ILs containing polar chain grafted on the cation (for example benzyl or cyclohexyl) increases considerably their performance in separation processes.

Keywords: interaction organic solvent-ionic liquid, gas chromatography, solvation model, COSMO-RS

Procedia PDF Downloads 107

Authors: M. Azharul Islam, M. Russel Sarker, M. Shahadat Hossen

Abstract:

Air pollution is one of the major environmental problems that have gained importance in all over the world. Air pollution is a problem for all of us. The present study was conducted to explore the people’s perception level and awareness of air pollution in selected areas of Mymensingh in Bangladesh. Health impacts of air pollution also studied through personal interview and structured questionnaire. The relationship of independent variables (age, educational qualification, family size, residence and communication exposure) with the respondent’s perception level and awareness of air pollution (dependent variable) was studied to achieve the objectives of the study. About 600 respondents were selected randomly from six sites for collecting data during the period of July 2016 to June 2017. Pearson’s product-moment correlation coefficients were computed to examine the relationship between the concerned variables. The results revealed that about half (46.67%) of the respondents had a medium level of perception and awareness about air pollution in their areas where 31.67 percent had low, and 21.67 percent had a high level. In rural areas of the study sites, 43.33 percent respondents had low, 50 percent had medium, and only 6.67 percent had high perception and awareness on air pollution. In case of urban areas, 20 percent respondents had low, 43.33 percent had medium, and 36.67 percent had a high level of awareness and perception on air pollution. The majority of the respondents (93.33 percent) were lacking of proper awareness about air pollution in rural areas while 63.33 percent in urban areas. Out of five independent variables, three variables such as- educational qualification, residence status and communication exposure had positive and significant relationship. Age of respondents had negative and significant relationship with their awareness of air pollution where family size of the respondents had no significant relationship with their perception and awareness of air pollution. Thousands of people live in urban areas where urban smog, particle pollution, and toxic pollutants pose serious health concerns. But most of the respondents of the urban sites are not familiarize about the real causes of air pollution. Respondents exposed higher level of experience for air pollutants, such as- irritation of the eyes, coughing, tightness of chest and many health difficulties. But respondents of both rural and urban area hugely suffered such health problems and the tendency of certain difficulties increased day by day. In this study, most of the respondents had lack of knowledge on the causes of such health difficulties due to their lower perception level. Proper attempts should be taken to raise literacy level, communication exposure to increase the perception and awareness of air pollution among the respondents of the study areas. Extra care with above concerned fields should be taken to increase perception and awareness of air pollution in rural areas.

Keywords: air pollution, awareness, health impacts, perception of people

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Authors: Cagri Mollamahmutoglu, Aykut Levent, Ali Mercan

Abstract:

Micro-beams are one of the most common components of Nano-Electromechanical Systems (NEMS) and Micro Electromechanical Systems (MEMS). For this reason, static bending, buckling, and free vibration analysis of micro-beams have been the subject of many studies. In addition, micro-beams restrained with elastic type foundations have been of particular interest. In the analysis of microstructures, closed-form solutions are proposed when available, but most of the time solutions are based on numerical methods due to the complex nature of the resulting differential equations. Thus, a robust and efficient solution method has great importance. In this study, a mixed finite element formulation is obtained for a functionally graded Timoshenko micro-beam resting on two-parameter elastic foundation. In the formulation modified couple stress theory is utilized for the micro-scale effects. The equation of motion and boundary conditions are derived according to Hamilton’s principle. A functional, derived through a scientific procedure based on Gateaux Differential, is proposed for the bending and buckling analysis which is equivalent to the governing equations and boundary conditions. Most important advantage of the formulation is that the mixed finite element formulation allows usage of C₀ type continuous shape functions. Thus shear-locking is avoided in a built-in manner. Also, element matrices are sparsely populated and can be easily calculated with closed-form integration. In this framework results concerning the effects of micro-scale length parameter, power-law parameter, aspect ratio and coefficients of partially or fully continuous elastic foundation over the static bending, buckling, and free vibration response of FG-micro-beam under various boundary conditions are presented and compared with existing literature. Performance characteristics of the presented formulation were evaluated concerning other numerical methods such as generalized differential quadrature method (GDQM). It is found that with less computational burden similar convergence characteristics were obtained. Moreover, formulation also includes a direct calculation of the micro-scale related contributions to the structural response as well.

Keywords: micro-beam, functionally graded materials, two-paramater elastic foundation, mixed finite element method

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Authors: Dalia Antiniene, Rosita Lekaviciene

Abstract:

The qualitative methodology based study is designed to reveal a connection between emotional intelligence (EI) and locus of control (LC) within the population of Lithuanian youth. In the context of emotional problems, the locus of control reflects how one estimates the causes of his/her emotions: internals (internal locus of control) associate their emotions with their manner of thinking, whereas externals (external locus of control) consider emotions to be evoked by external circumstances. On the other hand, there is little empirical data about this connection, and the results in disposition are often contradictory. In the conducted study 1430 young people, aged 17 to 27, from various regions of Lithuania were surveyed. The subjects were selected by quota sampling, maintaining natural proportions of the general Lithuanian youth population. To assess emotional intelligence the EI-DARL test (i.e. self-report questionnaire consisting of 75 items) was implemented. The emotional intelligence test, created applying exploratory factor analysis, reveals four main dimensions of EI: understanding of one’s own emotions, regulation of one’s own emotions, understanding other’s emotions, and regulation of other’s emotions (subscale reliability coefficients fluctuate between 0,84 and 0,91). An original 16-item internality/externality scale was used to examine the locus of control (internal consistency of the Externality subscale - 0,75; Internality subscale - 0,65). The study has determined that the youth understands and regulates other people’s emotions better than their own. Using the K-mean cluster analysis method, it was established that there are three groups of subjects according to their EI level – people with low, medium and high EI. After comparing means of subjects’ favorability of statements on the Internality/Externality scale, a predominance of internal locus of control in the young population was established. The multiple regression models has shown that a rather strong statistically significant correlation exists between total EI, EI subscales and LC. People who tend to attribute responsibility for the outcome of their actions to their own abilities and efforts have higher EI and, conversely, the tendency to attribute responsibility to external forces is related more with lower EI. While pursuing their goals, young people with high internality have a predisposition to analyze perceived emotions and, therefore, gain emotional experience: they learn to control their natural reactions and to act adequately in a situation at hand. Thus the study unfolds, that a person’s locus of control and emotional intelligence are related phenomena and allows us to draw a conclusion, that a person’s internality/externality is a reliable predictor of total EI and its components.

Keywords: emotional intelligence, externality, internality, locus of control

Procedia PDF Downloads 221