Search results for: H₂-optimal model reduction

Authors: Ali Noorzad, Ehsan Badakhshan, Shima Zameni

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The present paper is focused on a generalized failure criterion for geomaterials with cross-anisotropy. The cyclic behavior of granular material primarily depends on the nature and arrangement of constituent particles, particle size, and shape that affect fabric anisotropy. To account for the influence of loading directions on strength variations, an anisotropic variable in terms of the invariants of the stress tensor and fabric into the failure criterion is proposed. In an extension to original CANAsand constitutive model two concepts namely critical state and compact state play paramount roles as all of the moduli and coefficients are related to these states. The applicability of the present model is evaluated through comparisons between the predicted and the measured results. All simulations have demonstrated that the proposed constitutive model is capable of modeling the cyclic behavior of sand with inherent anisotropy.

Keywords: fabric, cohesionless media, cyclic loading, critical state, compact state, CANAsand constitutive model

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Roberto Pili, Alessandro Romagnoli, Hartmut Spliethoff, Christoph Wieland

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Internal combustion engines (ICE) are today the most common energy system to drive vehicles and transportation systems. Numerous studies state that 50-60% of the fuel energy content is lost to the ambient as sensible heat. ORC offers a valuable alternative to recover such waste heat from ICE, leading to fuel energy savings and reduced emissions. In contrast, the additional weight of the ORC affects the net energy balance of the overall system and the ORC occupies additional volume that competes with vehicle transportation capacity. Consequently, a lower income from delivered freight or passenger tickets can be achieved. The economic feasibility of integrating an ORC into an ICE and the resulting economic impact of weight and volume have not been analyzed in open literature yet. This work intends to define such a benchmark for ORC applications in the transportation sector and investigates the current situation on the market. The applied methodology refers to the freight market, but it can be extended to passenger transportation as well. The economic parameter X is defined as the ratio between the variation of the freight revenues and the variation of fuel costs when an ORC is installed as a bottoming cycle for an ICE with respect to a reference case without ORC. A good economic situation is obtained when the reduction in fuel costs is higher than the reduction of revenues for the delivered freight, i.e. X<1. Through this constraint, a maximum allowable change of transport capacity for a given relative reduction in fuel consumption is determined. The specific fuel consumption is influenced by the ORC in two ways. Firstly because the transportable freight is reduced and secondly because the total weight of the vehicle is increased. Note, that the generated electricity of the ORC influences the size of the ICE and the fuel consumption as well. Taking the above dependencies into account, the limiting condition X = 1 results in a second order equation for the relative change in transported cargo. The described procedure is carried out for a typical city bus, a truck of 24-40 t of payload capacity, a middle-size freight train (1000 t), an inland water vessel (Va RoRo, 2500 t) and handysize-like vessel (25000 t). The maximum allowable mass and volume of the ORC are calculated in dependence of its efficiency in order to satisfy X < 1. Subsequently, these values are compared with weight and volume of commercial ORC products. For ships of any size, the situation appears already highly favorable. A different result is obtained for road and rail vehicles. For trains, the mass and the volume of common ORC products have to be reduced at least by 50%. For trucks and buses, the situation looks even worse. The findings of the present study show a theoretical and practical approach for the economic application of ORC in the transportation sector. In future works, the potential for volume and mass reduction of the ORC will be addressed, together with the integration of an economic assessment for the ORC.

Keywords: ORC, transportation, volume, weight

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: Farrukh Javed, Krzysztof Podgórski

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We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: Saeed Farivar, Mohsen Kahrom

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The purpose of this work is to develop a physical simulation model for the purpose of studying the effect of various design parameters on the performance of packaged-liquid chillers. This paper presents a steady-state model for predicting the performance of package-Liquid chiller over a wide range of operation condition. The model inputs are inlet conditions; geometry and output of model include system performance variable such as power consumption, coefficient of performance (COP) and states of refrigerant through the refrigeration cycle. A computer model that simulates the steady-state cyclic performance of a vapor compression chiller is developed for the purpose of performing detailed physical design analysis of actual industrial chillers. The model can be used for optimizing design and for detailed energy efficiency analysis of packaged liquid chillers. The simulation model takes into account presence of all chiller components such as compressor, shell-and-tube condenser and evaporator heat exchangers, thermostatic expansion valve and connection pipes and tubing’s by thermo-hydraulic modeling of heat transfer, fluids flow and thermodynamics processes in each one of the mentioned components. To verify the validity of the developed model, a 7.5 USRT packaged-liquid chiller is used and a laboratory test stand for bringing the chiller to its standard steady-state performance condition is build. Experimental results obtained from testing the chiller in various load and temperature conditions is shown to be in good agreement with those obtained from simulating the performance of the chiller using the computer prediction model. An entropy-minimization-based optimization analysis is performed based on the developed analytical performance model of the chiller. The variation of design parameters in construction of shell-and-tube condenser and evaporator heat exchangers are studied using the developed performance and optimization analysis and simulation model and a best-match condition between the physical design and construction of chiller heat exchangers and its compressor is found to exist. It is expected that manufacturers of chillers and research organizations interested in developing energy-efficient design and analysis of compression chillers can take advantage of the presented study and its results.

Keywords: optimization, packaged liquid chiller, performance, simulation

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Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

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The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

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Authors: Babak Mohajeri

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In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

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Authors: Asif Jamal, Samia Sakindar, Ramla Rehman

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Biosurfactants are amphiphilic surface active compounds obtained from natural resources such as plants and microorganisms. Because of their diverse physicochemical characteristics biosurfactant are replacing synthetic compounds in various commercial applications. In present study, a strain of P. aeruginosa was isolated from crude oil contaminated soil as efficient biosurfactant producers. The biosurfactant production was analyzed as a function of surface tension reduction, oil spreading capacity, emulsification index and hemolysis assay. This bacterial strain showed excellent emulsion activity of EI24 85%, surface tension reduction up to 28.6 mNm-1 and 7.0 mm oil displacement zone. Physicochemical and biological properties of extracted rhamnolipid were also investigated in current study. The chemical composition of product from strain PSS was analyzed by FTIR spectroscopy. The results revealed that extracted biosurfactant was rhamnolipid type in nature having RL-1 and RL-2 homologues. The surface behavior of rhamnolipid in aqueous phase was investigated varying extreme pH, temperature, salt conditions and with various hydrocarbons. The results indicated that biosurfactant produced by strain PSS Which showed stability during high temperature up to 121 C, salt concentrations up to 20% and pH range between (4—14). The emulsification activity with different hydrocarbons was also remarkable. It was concluded that rhamnolipid biosurfactant produced by strain PSS has excellent potential as emulsifying/remediation agent for broad range of hydrophobic pollutants.

Keywords: P. aeruginosa, bioremediation, rhamnolipid, surfactants

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Authors: Nop Sopipan

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In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.

Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD

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Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

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Authors: Hassan Masoumi, Rashed Alavi, Mahmoud Reza Khorshidian

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In order to measure the water deficit stress effects on seed yield and water productivity of soybean cultivars, a two field experiments wad conducted out via split plot in a randomized complete block design with four replications in 2011 and 2012. Irrigation treatments were three levels (S1; 50, S2; 62.5 and S3; 150 mm) that applied based on evaporation from the ‘class A’ pan. Cultivars were L17, Clean, T.M.S, Williams×Chippewa and M9, too. The results showed that, only extreme water deficit stresses (S3) was reduced number of pods per plants, dry weight, seed yield and also water productivity and water economic productivity, significantly. Among cultivars and at the first and second levels of irrigation (S1, S2) cultivar of L17 and at the third level (S3) cultivar of Wiiliams*Chippwea had the highest seed yield, water productivity and water economic productivity. There were observed a positive and significant correlation between seed yield with number of pods per plants and plants dry weight, too. Also, despite the reduction in water consumption at level of S2 than S1 and due to the lack of a significant reduction in seed yield, water productivity and water economic productivity was also increased, significantly (P < 0.01). All indices of sensitivity and tolerance (SSI, STI and GMP) investigated in this study showed that at the moderate and extreme water deficit stresses (S2, S3), the cultivars of L17 and Wiiliams * Chippwea had the highest tolerance and lowest sensitivity among the cultivars.

Keywords: drought, sensitivity indices, yield components, seed

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Authors: Manas Shah

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

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Authors: H. G. Noh, H. G. Park, B. S. Kang, J. Kim

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Electromagnetic forming process (EMF) is one of high-velocity forming processes using Lorentz force. Advantages of EMF are summarized as improvement of formability, reduction in wrinkling, non-contact forming. In this study, numerical simulations were conducted to determine the practical parameters for EMF process. A 2-D axis-symmetric electromagnetic model was considered based on the spiral type forming coil. In the numerical simulation, RLC circuit coupled with spiral coil was made to consider the design parameters such as system input current and electromagnetic force. In order to deform the sheet in the patter shape die, two types of spiral shape coil were considered to deform the pattern shape sheet. One is a spiral coil that has 6turns with dead zone at centre point. Another is a normal spiral coil without dead zone that has 8 turns. In the electric analysis, input current and magnetic force were compared and then plastic deformation was treated in the mechanical analysis for two coil cases. Deformation behaviour of dead zone coil case has good agreement with pattern shape die. As a result, deformation behaviour could be controlled by giving dead zone at centre of the coil in spiral shape coil case.

Keywords: electromagnetic forming, spiral coil, Lorentz force, manufacturing

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Authors: Ghada Al-Kafaji, Mohamed Sabry

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Mitochondria are the site of cellular respiration and produce energy in the form of adenosine triphosphate (ATP) via oxidative phosphorylation. They are the major source of intracellular reactive oxygen species (ROS) and are also direct target to ROS attack. Oxidative stress and ROS-mediated disruptions of mitochondrial function are major components involved in the pathogenicity of diabetic complications. In this work, the changes in mitochondrial DNA (mtDNA) copy number, biogenesis, gene expression of mtDNA-encoded subunits of electron transport chain (ETC) complexes, and mitochondrial function in response to hyperglycemia-induced ROS and the effect of direct inhibition of ROS on mitochondria were investigated in an in vitro model of diabetic nephropathy using human renal mesangial cells. The cells were exposed to normoglycemic and hyperglycemic conditions in the presence and absence of Mn(III)tetrakis(4-benzoic acid) porphyrin chloride (MnTBAP) or catalase for 1, 4 and 7 days. ROS production was assessed by the confocal microscope and flow cytometry. mtDNA copy number and PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 transcripts, were all analyzed by real-time PCR. PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 proteins, were analyzed by Western blotting. Mitochondrial function was determined by assessing mitochondrial membrane potential and adenosine triphosphate (ATP) levels. Hyperglycemia-induced a significant increase in the production of mitochondrial superoxide and hydrogen peroxide at day 1 (P < 0.05), and this increase remained significantly elevated at days 4 and 7 (P < 0.05). The copy number of mtDNA and expression of PGC-1a, NRF-1, and TFAM as well as ND2, CYTB, CO1 and ATPase 6 increased after one day of hyperglycemia (P < 0.05), with a significant reduction in all those parameters at 4 and 7 days (P < 0.05). The mitochondrial membrane potential decreased progressively at 1 to 7 days of hyperglycemia with the parallel progressive reduction in ATP levels over time (P < 0.05). MnTBAP and catalase treatment of cells cultured under hyperglycemic conditions attenuated ROS production reversed renal mitochondrial oxidative stress and improved mtDNA, mitochondrial biogenesis, and function. These results show that hyperglycemia-induced ROS caused an early increase in mtDNA copy number, mitochondrial biogenesis and mtDNA-encoded gene expression of the ETC subunits in human mesangial cells as a compensatory response to the decline in mitochondrial function, which precede the mtDNA defect and mitochondrial dysfunction with a progressive oxidative response. Protection from ROS-mediated damage to renal mitochondria induced by hyperglycemia may be a novel therapeutic approach for the prevention/treatment of DN.

Keywords: diabetic nephropathy, hyperglycemia, reactive oxygen species, oxidative stress, mtDNA, mitochondrial dysfunction, manganese superoxide dismutase, catalase

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Authors: Jyothi P. Phatak, L. Venkatesha, C. S. Raviprasad

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The performance improvement of Hybrid Energy Storage System (HESS) in Electric Vehicle (EV) has been in discussion over the last decade. The important issues in terms of performance parameters addressed are, range of vehicle and battery (BA) peak current. Published literature has either addressed battery peak current reduction or range improvement in EV. Both the issues have not been specifically discussed and analyzed. This paper deals with both range improvement in EV and battery peak current reduction by applying a new Karnaugh Map (K-Map) constructed rule based energy management strategy to proposed HESS. The strategy allows Ultracapacitor (UC) to assist battery when the vehicle accelerates there by reducing the burden on battery. Simulation is carried out for various operating modes of EV considering both urban and highway driving conditions. Simulation is done for different values of UC by keeping battery rating constant for each driving cycle and results are presented. Feasible value of UC is selected based on simulation results. The results of proposed HESS show an improvement in performance parameters compared to Battery only Energy Storage System (BESS). Battery life is improved to considerable extent and there is an overall development in the performance of electric vehicle.

Keywords: electric vehicle, PID controller, energy management strategy, range, battery current, ultracapacitor

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Authors: Yousef Abdulaziz Almolhem

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Geographically, the most Arabic countries locate in areas confined to arid or semiarid regions. For this reason, most of our countries have adopted the seawater desalination as a strategy to overcome this problem. For example, the water supply of AUE, Kuwait, and Saudi Arabia is almost 100% from the seawater desalination plants. Many areas in Saudia Arabia and other countries in the world suffer from lack of fresh water which hinders the development of these areas, despite the availability of saline water and high solar radiation intensity. Furthermore, most developing countries do not have sufficient meteorological data to evaluate if the solar radiation is enough to meet the solar desalination. A mathematical model was developed to simulate and predict the thermal behavior of the solar still which used direct solar energy for distillation of seawater. Measurement data were measured in the Environment and Natural Resources Department, Faculty of Agricultural and Food sciences, King Faisal University, Saudi Arabia, in order to evaluate the present model. The simulation results obtained from this model were compared with the measured data. The main results of this research showed that there are slight differences between the measured and predicted values of the elements studied, which is resultant from the change of some factors considered constants in the model such as the sky clearance, wind velocity and the salt concentration in the water in the basin of the solar still. It can be concluded that the present model can be used to estimate the average total solar radiation and the thermal behavior of the solar still in any area with consideration to the geographical location.

Keywords: mathematical model, sea water, distillation, solar radiation

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: N. Reppas, Y. L. Gui, B. Wetenhall, C. T. Davie, J. Ma

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A theoretical constitutive model describing the stress-strain behavior of rock subjected to different confining pressures is presented. A bounding surface plastic model with hardening effects is proposed which includes the effect of temperature drop. The bounding surface is based on a mapping rule and the temperature effect on rock is controlled by Poisson’s ratio. Validation of the results against available experimental data is also presented. The relation of deviatoric stress and axial strain is illustrated at different temperatures to analyze the effect of temperature decrease in terms of stiffness of the material.

Keywords: bounding surface, cooling of rock, plasticity model, rock deformation, elasto-plastic behavior

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: Mohamed Ali MiladKrem Salem, Sergio F.Breña, Sanjay R. Arwade, Simi T. Hoque

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The location of the main lateral‐load resisting system in high-rise buildings may have positive impacts on sustainability through a reduction in operational energy consumption, and this paper describes an assessment of the accompanying effects on structural performance. It is found that there is a strong influence of design for environmental performance on the structural performance the building, and that systems selected primarily with an eye towards energy use reduction may require substantial additional structural stiffening to meet safety and serviceability limits under lateral load cases. We present a framework for incorporating the environmental costs of meeting structural design requirements through the embodied energy of the core structural materials and also address the issue of economic cost brought on by incorporation of environmental concerns into the selection of the structural system. We address these issues through four case study high-rise buildings with differing structural morphologies (floor plan and core arrangement) and assess each of these building models for cost and embodied energy when the base structural system, which has been suggested by architect Kenneth Yeang based on environmental concerns, is augmented to meet lateral drift requirements under the wind loads prescribed by ASCE 7-10.

Keywords: sustainable, embodied, Outrigger, skyscraper, morphology, efficiency

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

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Authors: Abdullahi Mohammed Auwal

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Formation and change or decamping from one political party to another have now become a common trend in Nigeria. Many of the parties’ members who could not secure positions and or win elections in their parties or are not very much satisfied with the trends occurring in the party’s internal democratic principles and mechanisms, change their respective parties. This paper developed/presented and analyzed the used of non linear mathematical model for defections between two political parties using epidemiological approach. The whole population was assumed to be a constant and homogeneously mixed. Equilibria have been analytically obtained and their local and global stability discussed. Conditions for the co-existence of both the political parties have been determined, in the study of defections between People Democratic Party (PDP) and All Progressive Congress (APC) in Nigeria using numerical simulations to support the analytical results.

Keywords: model, political parties, deffection, stability, equilibrium, epidemiology

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

Abstract:

Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: M. P. Tripathi, Priti Tiwari

Abstract:

Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.

Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield

Procedia PDF Downloads 366

Authors: Omar Imhemed Alramli

Abstract:

As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

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Authors: Hamed Saremi, Shahla Saremi

Abstract:

In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

Procedia PDF Downloads 466

Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

Abstract:

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

Procedia PDF Downloads 450

Authors: Thanh-Phong Dao, Shyh-Chour Huang

Abstract:

This study presents the optimal design and formulation of a kinematic model of a flexible slider crank mechanism. The objective of the proposed innovative design is to take extra advantage of the compliant mechanism and maximize the fatigue life by applying the Taguchi method. A formulated kinematic model is developed using a Pseudo-Rigid-Body Model (PRBM). By means of mathematic models, the kinematic behaviors of the flexible slider crank mechanism are captured using MATLAB software. Finite Element Analysis (FEA) is used to show the stress distribution. The results show that the optimal shape of the flexible hinge includes a force of 8.5N, a width of 9mm and a thickness of 1.1mm. Analysis of variance shows that the thickness of the proposed hinge is the most significant parameter, with an F test of 15.5. Finally, a prototype is manufactured to prepare for testing the kinematic and dynamic behaviors.

Keywords: kinematic behavior, fatigue life, pseudo-rigid-body model, flexible slider crank mechanism

Procedia PDF Downloads 449