Search results for: numerical weather prediction

Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

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Authors: Shakhawan K. Mawlood, Catriona Pickard, Benjamin Pickard

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In summer 2015 the remains of 800 children are among 1,967 bodies were exhumed by archaeologists at St Peter's Burial Ground in Blackburn, Lancashire. One hundred samples from these 19th century ancient bones were selected for DNA analysis. These comprised samples biased for those which prior osteological evidence indicated a potential for microbial infection by Mycobacterium tuberculosis (causing tuberculosis, TB) or Treponema pallidum (causing Syphilis) species, as well a random selection of other bones for which visual inspection suggested good preservation (and, therefore, likely DNA retrieval).They were subject to polymerase chain reaction (PCR) assays aimed at detecting traces of DNA from infecting mycobacteria, with the purpose both of confirming the palaeopathological diagnosis of tuberculosis and determining in individual cases whether disease and death was due to M. tuberculosis or other reasons. Our secondary goal was to determine sex determination and age prediction. The results demonstrated that extraction of vast majority ancient bones DNA samples succeeded.

Keywords: ancient bone, DNA, tuberculosis, age prediction

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Authors: S. Naveen, V. Sivasubramanian

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A modeling theory is proposed to consider the vaporization of LNG during its contact with water following its release from an underwater source. The spillage of LNG underwater can lead to a decrease in the surface temperature of water and subsequent freezing. This can in turn affect the heat flux distribution from the released LNG onto the water surrounding it. The available models predict the rate of vaporization considering the surface of contact as a solid wall, and considering the entire phenomena as a solid-liquid operation. This assumption greatly under-predicted the overall heat transfer on LNG water interface. The vaporization flux would first decrease during the film boiling, followed by an increase during the transition boiling and a steady decrease during the nucleate boiling. A superheat theory is introduced to enhance the accuracy in the prediction of the heat transfer between LNG and water. The work suggests that considering the superheat theory can greatly enhance the prediction of LNG vaporization on underwater releases and also help improve the study of overall thermodynamics.

Keywords: evaporation rate, heat transfer, LNG vaporization, underwater LNG release

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Authors: Suwimon Saneewong Na Ayuttaya

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This paper presents a numerical investigation of electrically driven flow for enhancing convective heat transfer in a channel flow. This study focuses on the electrode arrangements, number of electrode and electrical voltage on Electrohydrodynamics (EHD) and effect of airflow driven on solid sample surface. The inlet airflow and inlet temperature are 0.35 m/s and 60 ^oC, respectively. High electrical voltage is tested in the range of 0-30 kV and number of electrode is tested in the range of 1-5. The numerical results show that electric field intensity is depended on electrical voltage and number of electrode. Increasing number of electrodes is increased shear flow, so swirling flow is increased. The swirling flows from aligned and staggered arrangements are affecting within the solid sample. When electrical voltage is increased, temperature distribution and convective heat transfer on the solid sample are significantly increased due to the electric force much stronger.

Keywords: electrohydrodynamics (EHD), swirling flow, convective heat transfer, solid sample

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Authors: Tayeb Chihi, Messaoud Fatmi

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We present calculations of the structural, elastic and electronic properties of nonferrous Ti, Zr, and Hf pure metals in both parent and martensite phases in bcc and hcp structures respectively. They are based on the generalized gradient approximation (GGA) within the density functional theory (DFT). The shear modulus, Young's modulus and Poisson's ratio for Ti, Zr, and Hf metals have were calculated and compared with the corresponding experimental values. Using elastic constants obtained from calculations GGA, the bulk modulus along the crystallographic axes of single crystals was calculated. This is in good agreement with experiment for Ti and Zr, whereas the hcp structure for Hf is a prediction. At zero temperature and zero pressure, the bcc crystal structure is found to be mechanically unstable for Ti, Zr, and Hf. In our calculations the hcp structures is correctly found to be stable at the equilibrium volume. In the electronic density of states (DOS), the smaller n(EF) is, the more stable the compound is. Therefore, in agreement with the results obtained from the total energy minimum.

Keywords: Ti, Zr, Hf, pure metals, transformation, energy

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Authors: Nadim Zgheib, Sivaramakrishnan Balachandar

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We present results on the initial formation of ripples from an initially flattened erodible bed. We use direct numerical simulations (DNS) of turbulent open channel flow over a fixed sinusoidal bed coupled with hydrodynamic stability analysis. We use the direct forcing immersed boundary method to account for the presence of the sediment bed. The resolved flow provides the bed shear stress and consequently the sediment transport rate, which is needed in the stability analysis of the Exner equation. The approach is different from traditional linear stability analysis in the sense that the phase lag between the bed topology, and the sediment flux is obtained from the DNS. We ran 11 simulations at a fixed shear Reynolds number of 180, but for different sediment bed wavelengths. The analysis allows us to sweep a large range of physical and modelling parameters to predict their effects on linear growth. The Froude number appears to be the critical controlling parameter in the early linear development of ripples, in contrast with the dominant role of particle Reynolds number during the equilibrium stage.

Keywords: direct numerical simulation, immersed boundary method, sediment-bed interactions, turbulent multiphase flow, linear stability analysis

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Authors: Guillaume Craveur

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This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Q. Giraud, J. Gonçalvès, B. Paris

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Remediation of dense non-aqueous phase liquids (DNAPLs) represents a challenging issue because of their persistent behaviour in the environment. This pilot-scale study investigates, by means of in situ experiments and numerical modelling, the feasibility of the pulsed pumping process of a large amount of a DNAPL in an alluvial aquifer. The main compound of the DNAPL is hexachlorobutadiene, an emerging organic pollutant. A low-permeability keyed enclosure was built at the location of the DNAPL source zone in order to isolate a finite undisturbed volume of soil, and a 3-month pulsed pumping process was applied inside the enclosure to exclusively extract the DNAPL. The water/DNAPL interface elevation at both the pumping and observation wells and the cumulated pumped volume of DNAPL were also recorded. A total volume of about 20m³ of purely DNAPL was recovered since no water was extracted during the process. The three-dimensional and multiphase flow simulator TMVOC was used, and a conceptual model was elaborated and generated with the pre/post-processing tool mView. Numerical model consisted of 10 layers of variable thickness and 5060 grid cells. Numerical simulations reproduce the pulsed pumping process and show an excellent match between simulated, and field data of DNAPL cumulated pumped volume and a reasonable agreement between modelled and observed data for the evolution of the water/DNAPL interface elevations at the two wells. This study offers a new perspective in remediation since DNAPL pumping system optimisation may be performed where a large amount of DNAPL is encountered.

Keywords: dense non-aqueous phase liquid (DNAPL), hexachlorobutadiene, in situ pulsed pumping, multiphase flow, numerical modelling, porous media

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Authors: Ebrahim Alamatian, Seyed Mehdi Afzalnia

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One of the most vital hydraulic structures is the dam. Regarding the unrecoverable damages which may occur after a dam break phenomenon, analyzing dams’ break is absolutely essential. GOLESTAN dam is located in the western South of Mashhad city in Iran. GOLESTAN dam break might lead to severe problems due to adjacent tourist and entertainment areas. In this paper, a numerical code based on the finite volume method was applied for assessing the risk of GOLESTAN dam break. As to this issue, first, a canal with a triangular barrier was modeled so as to verify the capability of the concerned code. Comparing analytical, experimental and numerical results showed that water level in the model results is in a good agreement with the similar water level in the analytical solutions and experimental data. The results of dam break modeling are revealed that two of the bridges, that are PARTOIE and NAMAYESHGAH, located downstream in the flow direction, are at risk following the potential GOLESTAN dam break. Therefore, the required times to conduct the precautionary measures at bridges were calculated at about 12 and 21 minutes, respectively. Thus, it is crucial to announce people about the possible risks of the dam break in order to decrease likely losses.

Keywords: numerical model, shallow water equations, GOLESTAN dam break, dry and wet beds modeling

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Authors: I. Ioannou, I. M. Gitman

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This study focused on the contribution of micro-mechanical parameters on the macro-mechanical response of short fiber composites, namely polypropylene matrix reinforced by glass fibers. In the framework of this paper, an attention has been given to the glass fibers length, as micromechanical parameter influences the overall macroscopic material’s behavior. Three dimensional numerical models were developed and analyzed through the concept of a Representative Volume Element (RVE). Results of the RVE-based approach were compared with analytical Halpin-Tsai’s model.

Keywords: effective properties, homogenization, representative volume element, short fiber reinforced composites

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Authors: Dmitry V. Fomichev, Vladimir I. Solonin

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In this paper, experimental and numerical study of hydrodynamic characteristics of the air coolant flow in the test wire-wrapped assembly is presented. The test assembly has 37 rods, which are similar to the real fuel pins of the BREST-OD-300 fuel assemblies geometrically. Air open loop test facility installed at the “Nuclear Power Plants and Installations” department of BMSTU was used to obtain the experimental data. The obtaining altitudinal distribution of static pressure in the near-wall test assembly as well as velocity and temperature distribution of coolant flow in the test sections can give us some new knowledge about the mechanism of formation of the turbulence flow structure in the wire wrapped fuel assemblies. Numerical simulations of the turbulence flow has been accomplished using ANSYS Fluent 14.5. Different non-local turbulence models have been considered, such as standard and RNG k-e models and k-w SST model. Results of numerical simulations of the flow based on the considered turbulence models give the best agreement with the experimental data and help us to carry out strong analysis of flow characteristics.

Keywords: wire-spaces fuel assembly, turbulent flow structure, computation fluid dynamics

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Authors: Amir Golalipour

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In recent years, resilience emerged as an important topic in transportation infrastructure practice, planning, and design to address the myriad stressors of future climate facing the Nation. Climate change has increased the frequency of extreme weather events and also causes climate and weather patterns to diverge from historic trends, culminating in circumstances where transportation infrastructure and assets are operating outside the scope of their design. To design and maintain transportation infrastructure that can continue meeting objectives over the infrastructure’s design life, these systems must be made adaptable to the changing climate by incorporating resilience wherever practically and financially feasible. This study is focused on the adaptation strategies and incorporation of resilience in infrastructure construction, maintenance, rehabilitation, and preservation processes. This study will include highlights from some of the recent FHWA activities on resilience. This study describes existing resilience planning and decision-making practices related to transportation infrastructure; mechanisms to identify, analyze, and prioritize adaptation options; and the strain that future climate and extreme weather event pressures place on existing transportation assets and the stressors these systems face for both single and combined stressor scenarios. Results of two case studies from Transportation Engineering Approaches to Climate Resiliency (TEACR) projects with focus on temperature and precipitation impacts on transportation infrastructures will be presented. These case studies looked at the impact of infrastructure performance using future temperature and precipitation compared to traditional climate design parameters. The research team used the adaptation decision making assessment and Coupled Model Intercomparison Project (CMIP) processing tool to determine which solution is best to pursue. The CMIP tool provided project climate data for temperature and precipitation which then could be incorporated into the design procedure to estimate the performance. As a result, using the future climate scenarios would impact the design. These changes were noted to have only a slight increase in costs, however it is acknowledged that network wide these costs could be significant. This study will also focus on what we have learned from recent storms, floods, and climate related events that will help us be better prepared to ensure our communities have a resilient transportation network. It should be highlighted that standardized mechanisms to incorporate resilience practices are required to encourage widespread implementation, mitigate the effects of climate stressors, and ensure the continuance of transportation systems and assets in an evolving climate.

Keywords: adaptation strategies, extreme events, resilience, transportation infrastructure

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Authors: Samaila Bawa Muazu

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Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a novel plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.

Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, setting time, simulation

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

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Authors: G. Judakova, M. Bause

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The ability to model and simulate numerically natural gas flow in pipelines has become of high importance for the design of pipeline systems. The understanding of the formation of hydrate particles and their dynamical behavior is of particular interest, since these processes govern the operation properties of the systems and are responsible for system failures by clogging of the pipelines under certain conditions. Mathematically, natural gas flow can be described by multiphase flow models. Using the two-fluid modeling approach, the gas phase is modeled by the compressible Euler equations and the particle phase is modeled by the pressureless Euler equations. The numerical simulation of compressible multiphase flows is an important research topic. It is well known that for nonlinear fluxes, even for smooth initial data, discontinuities in the solution are likely to occur in finite time. They are called shock waves or contact discontinuities. For hyperbolic and singularly perturbed parabolic equations the standard application of the Galerkin finite element method (FEM) leads to spurious oscillations (e.g. Gibb's phenomenon). In our approach, we use stabilized FEM, the streamline upwind Petrov-Galerkin (SUPG) method, where artificial diffusion acting only in the direction of the streamlines and using a special treatment of the boundary conditions in inviscid convective terms, is added. Numerical experiments show that the numerical solution obtained and stabilized by SUPG captures discontinuities or steep gradients of the exact solution in layers. However, within this layer the approximate solution may still exhibit overshoots or undershoots. To suitably reduce these artifacts we add a discontinuity capturing or shock capturing term. The performance properties of our numerical scheme are illustrated for two-phase flow problem.

Keywords: two-phase flow, gas-particle mixture, inviscid two-fluid model, euler equation, finite element method, streamline upwind petrov-galerkin, shock capturing

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Authors: T. J. Hasanova, C. N. Imamalieva

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The problem about the movement of the rigid cylinder keeping the vertical position under the influence of running superficial waves in a liquid is considered. The indignation of a falling wave caused by the presence of the cylinder which moves is thus considered. Special decomposition on a falling harmonious wave is used. The problem dares an operational method. For a finding of the original decision, Considering that the image denominator represents a tabular function, Voltaire's integrated equation of the first sort which dares a numerical method is used. Cylinder movement in the continuous environment under the influence of waves is considered in work. Problems are solved by an operational method, thus originals of required functions are looked for by the numerical definition of poles of combinations of transcendental functions and calculation of not own integrals. Using specificity of a task below, Decisions are under construction the numerical solution of the integrated equation of Volter of the first sort that does not create computing problems of the complex roots of transcendental functions connected with search.

Keywords: rigid cylinder, linear interpolation, fluctuations, Voltaire's integrated equation, harmonious wave

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Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

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Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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Authors: Ajay R, Rammohan B, Sridhar K S S, Gurusharan N

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The objective of the work is to develop a numerical method to solve the inverse mode shape problem by determining the cross-sectional area of a structure for the desired mode shape via the vibration response study of the humerus bone, which is in the form of a cantilever beam with anisotropic material properties. The humerus bone is the long bone in the arm that connects the shoulder to the elbow. The mode shape is assumed to be a higher-order polynomial satisfying a prescribed set of boundary conditions to converge the numerical algorithm. The natural frequency and the mode shapes are calculated for different boundary conditions to find the cross-sectional area of humerus bone from Eigenmode shape with the aid of the inverse mode shape algorithm. The cross-sectional area of humerus bone validates the mode shapes of specific boundary conditions. The numerical method to solve the inverse mode shape problem is validated in the biomedical application by finding the cross-sectional area of a humerus bone in the human arm.

Keywords: Cross-sectional area, Humerus bone, Inverse mode shape problem, Mode shape

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Authors: Hadi Molaei, Yasavoli Davoud, Keshavarz, Mozhde Poordana

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The present study aimed was to prediction the academic performance based on academic motivation, self-efficacy and Resiliency in the students. The present study was descriptive and correlational. Population of the study consisted of all students in Arak schools in year 1393-94. For this purpose, the number of 304 schools students in Arak was selected using multi-stage cluster sampling. They all questionnaires, self-efficacy, Resiliency and academic motivation Questionnaire completed. Data were analyzed using Pearson correlation and multiple regressions. Pearson correlation showed academic motivation, self-efficacy, and Resiliency with academic performance had a positive and significant relationship. In addition, multiple regression analysis showed that the academic motivation, self-efficacy and Resiliency were predicted academic performance. Based on the findings could be conclude that in order to increase the academic performance and further progress of students must provide the ground to strengthen academic motivation, self-efficacy and Resiliency act on them.

Keywords: academic motivation, self-efficacy, resiliency, academic performance

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: numerical simulation, immiscible, finite difference, IADI, IDE, waterflooding

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Authors: Ajay Kumar Rana

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Predicting human behaviour, discerning monozygotic twins or left over remnant tissues/fluids of a single human source remains a big challenge in forensic science. Recent advances in the field of DNA methylations which are broadly chemical hallmarks in response to environmental factors can certainly help to identify and discriminate various single-source DNA samples collected from the crime scenes. In this review, cytosine methylation of DNA has been methodologically discussed with its broad applications in many challenging forensic issues like body fluid identification, race/ethnicity identification, monozygotic twins dilemma, addiction or behavioural prediction, age prediction, or even authenticity of the human DNA. With the advent of next-generation sequencing techniques, blooming of DNA methylation datasets and together with standard molecular protocols, the prospect of investigating and solving the above issues and extracting the exact nature of the truth for reconstructing the crime scene events would be undoubtedly helpful in defending and solving the critical crime cases.

Keywords: DNA methylation, differentially methylated regions, human identification, forensics

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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Authors: Raghad Alhusari, Farag Omar, Moustafa Fadel

Abstract:

A traditional greenhouse is a metal frame agricultural building used for cultivation plants in a controlled environment isolated from external climatic changes. Using greenhouses in agriculture is an efficient way to reduce the water consumption, where agriculture field is considered the biggest water consumer world widely. Controlling greenhouse environment yields better productivity of plants but demands an increase of electric power. Although various control approaches have been used towards greenhouse automation, most of them are applied to traditional greenhouses with ventilation fans and/or evaporation cooling system. Such approaches are still demanding high energy and water consumption. The aim of this research is to develop a fuzzy control system that minimizes water and energy consumption by utilizing outside weather conditions and underground heat exchanger to maintain the optimum climate of the greenhouse. The proposed control system is implemented on an experimental model of thermally isolated greenhouse structure with dimensions of 6x5x2.8 meters. It uses fans for extracting heat from the ground heat exchanger system, motors for automatic open/close of the greenhouse windows and LED as lighting system. The controller is integrated also with environmental condition sensors. It was found that using the air-to-air horizontal ground heat exchanger with 90 mm diameter and 2 mm thickness placed 2.5 m below the ground surface results in decreasing the greenhouse temperature of 3.28 ˚C which saves around 3 kW of consumed energy. It also eliminated the water consumption needed in evaporation cooling systems which are traditionally used for cooling the greenhouse environment.

Keywords: automation, earth-to-air heat exchangers, fuzzy control, greenhouse, sustainable buildings

Procedia PDF Downloads 133

Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

Abstract:

In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

Procedia PDF Downloads 110

Authors: Asal Pournaghshband

Abstract:

This paper presents the development of a finite element model to study the large deflection behavior of restrained stainless steel cellular beams at elevated temperature. Cellular beams are widely used for efficient utilization of raw materials to facilitate long spans with faster construction resulting sustainable design solution that can enhance the performance and merit of any construction project. However, their load carrying capacity is less than the equivalent beams without opening due to developing shear-moment interaction at the openings. In structural frames due to elements continuity, such beams are restrained by their adjoining members which has a substantial effect on beams behavior in fire. Stainless steel has also become integral part of the build environment due to its excellent corrosion resistance, whole life-cycle costs, and sustainability. This paper reports the numerical investigations into the effect of structural continuity on the thermo-mechanical performance of restrained steel beams with circle and elongated circle shapes of web opening in fire. The numerical model is firstly validated using existing numerical results from the literature, and then employed to perform a parametric study. The structural continuity is evaluated through the application of different levels of axial restraints on the response of carbon steel and stainless steel cellular beam in fire. The transit temperature for stainless steel cellular beam is shown to be less affected by the level of axial stiffness than the equivalent carbon steel cellular beam. Overall, it was established that whereas stainless steel cellular beams show similar stages of behavior of carbon steel cellular beams in fire, they are capable of withstanding higher temperatures prior to the onset of catenary action in large deflection, despite the higher thermal expansion of stainless steel material.

Keywords: axial restraint, catenary action, cellular beam, fire, numerical modeling, stainless steel, transit temperature

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Authors: Qijiao He, Lin Ye

Abstract:

To evaluate the effect of the ribs on internal structure in film hole and the film cooling performance on outer surface, the numerical study investigates on the effects of rib configuration on the film cooling performance with ribbed cross-flow coolant channel. The base smooth case and three ribbed cases, including the continuous rib case and two cross-truncated rib cases with different arrangement, are studied. The distributions of adiabatic film cooling effectiveness and heat transfer coefficient are obtained under the blowing ratios with the value of 0.5 and 1.0, respectively. A commercial steady RANS (Reynolds-averaged Navier-Stokes) code with realizable k-ε turbulence model and enhanced wall treatment were performed for numerical simulations. The numerical model is validated against available experimental data. The two cross-truncated rib cases produce approximately identical cooling effectiveness compared with the smooth case under lower blowing ratio. The continuous rib case significantly outperforms the other cases. With the increase of blowing ratio, the cases with ribs are inferior to the smooth case, especially in the upstream region. The cross-truncated rib I case produces the highest cooling effectiveness among the studied the ribbed channel case. It is found that film cooling effectiveness deteriorates with the increase of spiral intensity of the cross-flow inside the film hole. Lower spiral intensity leads to a better film coverage and thus results in better cooling effectiveness. The distinct relative merits among the cases at different blowing ratios are explored based on the aforementioned dominant mechanism. With regard to the heat transfer coefficient, the smooth case has higher heat transfer intensity than the ribbed cases under the studied blowing ratios. The laterally-averaged heat transfer coefficient of the cross-truncated rib I case is higher than the cross-truncated rib II case.

Keywords: cross-flow, cross-truncated rib, film cooling, numerical simulation

Procedia PDF Downloads 136