Search results for: quantile function model
19784 A Mathematical Description of a Growing Cell Colony Based on the Mechanical Bidomain Model
Authors: Debabrata Auddya, Bradley J. Roth
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The mechanical bidomain model is used to describe a colony of cells growing on a substrate. Analytical expressions are derived for the intracellular and extracellular displacements. Mechanotransduction events are driven by the difference between the displacements in the two spaces, corresponding to the force acting on integrins. The equation for the displacement consists of two terms: one proportional to the radius that is the same in the intracellular and extracellular spaces (the monodomain term) and one that is proportional to a modified Bessel function that is responsible for mechanotransduction (the bidomain term). The model predicts that mechanotransduction occurs within a few length constants of the colony’s edge, and an expression for the length constant contains the intracellular and extracellular shear moduli and the spring constant of the integrins coupling the two spaces. The model predictions are qualitatively consistent with experiments on human embryonic stem cell colonies, in which differentiation is localized near the edge.Keywords: cell colony, integrin, mechanical bidomain model, stem cell, stress-strain, traction force
Procedia PDF Downloads 23519783 Welfare Estimation in a General Equilibrium Model with Cities
Authors: Oded Hochman
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We first show that current measures of welfare changes in the whole economy do not apply to an economy with cities. In addition, since such measures are defined over a partial equilibrium, they capture only partially the effect of a welfare change. We then define a unique and additive measure that we term the modified economic surplus (mES) which fully captures the welfare effects caused by a change in the price of a nationally traded good. We show that the price change causes, on the one hand a change of land rents in the economy and, on the other hand, an equal change of mES that can be estimated by measuring areas in the price-quantity national demand and supply plane. We construct for each city a cost function from which we derive a city’s and, after aggregation, an economy-wide demand and supply functions of nationwide prices and of either the unearned incomes (Marshalian functions) or the utility levels (compensated functions).Keywords: city cost function, welfare measures, modified compensated variation, modified economic surplus, unearned income function, differential land rents, city size
Procedia PDF Downloads 30719782 Model Updating Based on Modal Parameters Using Hybrid Pattern Search Technique
Authors: N. Guo, C. Xu, Z. C. Yang
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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search
Procedia PDF Downloads 15419781 Numerical Performance Evaluation of a Savonius Wind Turbines Using Resistive Torque Modeling
Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines
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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances
Procedia PDF Downloads 15019780 A Flexible Pareto Distribution Using α-Power Transformation
Authors: Shumaila Ehtisham
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In Statistical Distribution Theory, considering an additional parameter to classical distributions is a usual practice. In this study, a new distribution referred to as α-Power Pareto distribution is introduced by including an extra parameter. Several properties of the proposed distribution including explicit expressions for the moment generating function, mode, quantiles, entropies and order statistics are obtained. Unknown parameters have been estimated by using maximum likelihood estimation technique. Two real datasets have been considered to examine the usefulness of the proposed distribution. It has been observed that α-Power Pareto distribution outperforms while compared to different variants of Pareto distribution on the basis of model selection criteria.Keywords: α-power transformation, maximum likelihood estimation, moment generating function, Pareto distribution
Procedia PDF Downloads 21119779 Modified Plastic-Damage Model for FRP-Confined Repaired Concrete Columns
Authors: I. A Tijani, Y. F Wu, C.W. Lim
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Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.Keywords: Concrete, FRP, Damage, Repairing, Plasticity, and Finite element method
Procedia PDF Downloads 13319778 Kinematic Hardening Parameters Identification with Respect to Objective Function
Authors: Marina Franulovic, Robert Basan, Bozidar Krizan
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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.Keywords: genetic algorithm, kinematic hardening, material model, objective function
Procedia PDF Downloads 32519777 Effect of the Applied Bias on Miniband Structures in Dimer Fibonacci Inas/Ga1-Xinxas Superlattices
Authors: Z. Aziz, S. Terkhi, Y. Sefir, R. Djelti, S. Bentata
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The effect of a uniform electric field across multibarrier systems (InAs/InxGa1-xAs) is exhaustively explored by a computational model using exact airy function formalism and the transfer-matrix technique. In the case of biased DFHBSL structure a strong reduction in transmission properties was observed and the width of the miniband structure linearly decreases with the increase of the applied bias. This is due to the confinement of the states in the miniband structure, which becomes increasingly important (Wannier-Stark Effect).Keywords: dimer fibonacci height barrier superlattices, singular extended state, exact airy function, transfer matrix formalism
Procedia PDF Downloads 29919776 Analysis of Path Nonparametric Truncated Spline Maximum Cubic Order in Farmers Loyalty Modeling
Authors: Adji Achmad Rinaldo Fernandes
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Path analysis tests the relationship between variables through cause and effect. Before conducting further tests on path analysis, the assumption of linearity must be met. If the shape of the relationship is not linear and the shape of the curve is unknown, then use a nonparametric approach, one of which is a truncated spline. The purpose of this study is to estimate the function and get the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in modeling farmer loyalty through the jackknife resampling method. This study uses secondary data through questionnaires to farmers in Sumbawa Regency who use SP-36 subsidized fertilizer products as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.Keywords: nonparametric path analysis, farmer loyalty, jackknife resampling, truncated spline
Procedia PDF Downloads 3619775 Sampled-Data Model Predictive Tracking Control for Mobile Robot
Authors: Wookyong Kwon, Sangmoon Lee
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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.Keywords: model predictive control, sampled-data control, linear parameter varying systems, LPV
Procedia PDF Downloads 30519774 Control-Oriented Enhanced Zero-Dimensional Two-Zone Combustion Modelling of Internal Combustion Engines
Authors: Razieh Arian, Hadi Adibi-Asl
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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine
Procedia PDF Downloads 33419773 A Fourier Method for Risk Quantification and Allocation of Credit Portfolios
Authors: Xiaoyu Shen, Fang Fang, Chujun Qiu
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Herewith we present a Fourier method for credit risk quantification and allocation in the factor-copula model framework. The key insight is that, compared to directly computing the cumulative distribution function of the portfolio loss via Monte Carlo simulation, it is, in fact, more efficient to calculate the transformation of the distribution function in the Fourier domain instead and inverting back to the real domain can be done in just one step and semi-analytically, thanks to the popular COS method (with some adjustments). We also show that the Euler risk allocation problem can be solved in the same way since it can be transformed into the problem of evaluating a conditional cumulative distribution function. Once the conditional or unconditional cumulative distribution function is known, one can easily calculate various risk metrics. The proposed method not only fills the niche in literature, to the best of our knowledge, of accurate numerical methods for risk allocation but may also serve as a much faster alternative to the Monte Carlo simulation method for risk quantification in general. It can cope with various factor-copula model choices, which we demonstrate via examples of a two-factor Gaussian copula and a two-factor Gaussian-t hybrid copula. The fast error convergence is proved mathematically and then verified by numerical experiments, in which Value-at-Risk, Expected Shortfall, and conditional Expected Shortfall are taken as examples of commonly used risk metrics. The calculation speed and accuracy are tested to be significantly superior to the MC simulation for real-sized portfolios. The computational complexity is, by design, primarily driven by the number of factors instead of the number of obligors, as in the case of Monte Carlo simulation. The limitation of this method lies in the "curse of dimension" that is intrinsic to multi-dimensional numerical integration, which, however, can be relaxed with the help of dimension reduction techniques and/or parallel computing, as we will demonstrate in a separate paper. The potential application of this method has a wide range: from credit derivatives pricing to economic capital calculation of the banking book, default risk charge and incremental risk charge computation of the trading book, and even to other risk types than credit risk.Keywords: credit portfolio, risk allocation, factor copula model, the COS method, Fourier method
Procedia PDF Downloads 15919772 Slip Suppression Sliding Mode Control with Various Chattering Functions
Authors: Shun Horikoshi, Tohru Kawabe
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This study presents performance analysis results of SMC (Sliding mode control) with changing the chattering functions applied to slip suppression problem of electric vehicles (EVs). In SMC, chattering phenomenon always occurs through high frequency switching of the control inputs. It is undesirable phenomenon and degrade the control performance, since it causes the oscillations of the control inputs. Several studies have been conducted on this problem by introducing some general saturation function. However, study about whether saturation function was really best and the performance analysis when using the other functions, weren’t being done so much. Therefore, in this paper, several candidate functions for SMC are selected and control performance of candidate functions is analyzed. In the analysis, evaluation function based on the trade-off between slip suppression performance and chattering reduction performance is proposed. The analyses are conducted in several numerical simulations of slip suppression problem of EVs. Then, we can see that there is no difference of employed candidate functions in chattering reduction performance. On the other hand, in slip suppression performance, the saturation function is excellent overall. So, we conclude the saturation function is most suitable for slip suppression sliding mode control.Keywords: sliding mode control, chattering function, electric vehicle, slip suppression, performance analysis
Procedia PDF Downloads 31819771 Application of Genetic Algorithm with Multiobjective Function to Improve the Efficiency of Photovoltaic Thermal System
Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar
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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.Keywords: genetic algorithm, energy, exergy, PVT module, optimization
Procedia PDF Downloads 60119770 Clustering-Based Threshold Model for Condition Rating of Concrete Bridge Decks
Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous
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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique
Procedia PDF Downloads 21819769 Closest Possible Neighbor of a Different Class: Explaining a Model Using a Neighbor Migrating Generator
Authors: Hassan Eshkiki, Benjamin Mora
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The Neighbor Migrating Generator is a simple and efficient approach to finding the closest potential neighbor(s) with a different label for a given instance and so without the need to calibrate any kernel settings at all. This allows determining and explaining the most important features that will influence an AI model. It can be used to either migrate a specific sample to the class decision boundary of the original model within a close neighborhood of that sample or identify global features that can help localising neighbor classes. The proposed technique works by minimizing a loss function that is divided into two components which are independently weighted according to three parameters α, β, and ω, α being self-adjusting. Results show that this approach is superior to past techniques when detecting the smallest changes in the feature space and may also point out issues in models like over-fitting.Keywords: explainable AI, EX AI, feature importance, counterfactual explanations
Procedia PDF Downloads 16619768 Multiphase Equilibrium Characterization Model For Hydrate-Containing Systems Based On Trust-Region Method Non-Iterative Solving Approach
Authors: Zhuoran Li, Guan Qin
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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method
Procedia PDF Downloads 16519767 Facial Emotion Recognition Using Deep Learning
Authors: Ashutosh Mishra, Nikhil Goyal
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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.Keywords: facial recognition, computational intelligence, convolutional neural network, depth map
Procedia PDF Downloads 21919766 Competing Risk Analyses in Survival Trials During COVID-19 Pandemic
Authors: Ping Xu, Gregory T. Golm, Guanghan (Frank) Liu
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In the presence of competing events, traditional survival analysis may not be appropriate and can result in biased estimates, as it assumes independence between competing events and the event of interest. Instead, competing risk analysis should be considered to correctly estimate the survival probability of the event of interest and the hazard ratio between treatment groups. The COVID-19 pandemic has provided a potential source of competing risks in clinical trials, as participants in trials may experienceCOVID-related competing events before the occurrence of the event of interest, for instance, death due to COVID-19, which can affect the incidence rate of the event of interest. We have performed simulation studies to compare multiple competing risk analysis models, including the cumulative incidence function, the sub-distribution hazard function, and the cause-specific hazard function, to the traditional survival analysis model under various scenarios. We also provide a general recommendation on conducting competing risk analysis in randomized clinical trials during the era of the COVID-19 pandemic based on the extensive simulation results.Keywords: competing risk, survival analysis, simulations, randomized clinical trial, COVID-19 pandemic
Procedia PDF Downloads 17919765 Assessment of Association Between Microalbuminuria and Lung Function Test Among the Community of Jimma Town
Authors: Diriba Dereje
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Background: Cardiac and renal disease are the most prevalent chronic non-communicable diseases (CNCD) affecting the community in a significant manner. The best and recommended method in halting CNCD is by working on prevention as early as possible. This is only possible if early surrogate markers are identified. As part of the stated solution, this study will identify an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Objective: The main aim of this study was to assess an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Methodology: Community based cross sectional study was conducted among 384 adult in Jimma town. A systematic sampling technique was used in selecting participants to the study. In searching for the possible association, binary and multivariate logistic regression and t-test was conducted. Finally, the association between microalbuminuria and lung function test was well stated in the form of figures and written description. Result and Conclusion: A significant association was found between microalbuminuria and different lung function test parameters.Keywords: microalbuminuria, lung function, association, test
Procedia PDF Downloads 18619764 Optical and Double Folding Analysis for 6Li+16O Elastic Scattering
Authors: Abd Elrahman Elgamala, N. Darwish, I. Bondouk, Sh. Hamada
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Available experimental angular distributions for 6Li elastically scattered from 16O nucleus in the energy range 13.0–50.0 MeV are investigated and reanalyzed using optical model of the conventional phenomenological potential and also using double folding optical model of different interaction models: DDM3Y1, CDM3Y1, CDM3Y2, and CDM3Y3. All the involved models of interaction are of M3Y Paris except DDM3Y1 which is of M3Y Reid and the main difference between them lies in the different values for the parameters of the incorporated density distribution function F(ρ). We have extracted the renormalization factor NR for 6Li+16O nuclear system in the energy range 13.0–50.0 MeV using the aforementioned interaction models.Keywords: elastic scattering, optical model, folding potential, density distribution
Procedia PDF Downloads 13919763 Artificial Neural Network to Predict the Optimum Performance of Air Conditioners under Environmental Conditions in Saudi Arabia
Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany
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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities
Procedia PDF Downloads 6719762 Generalization of Tsallis Entropy from a Q-Deformed Arithmetic
Authors: J. Juan Peña, J. Morales, J. García-Ravelo, J. García-Martínez
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It is known that by introducing alternative forms of exponential and logarithmic functions, the Tsallis entropy Sᵩ is itself a generalization of Shannon entropy S. In this work, from a deformation through a scaling function applied to the differential operator, it is possible to generate a q-deformed calculus as well as a q-deformed arithmetic, which not only allows generalizing the exponential and logarithmic functions but also any other standard function. The updated q-deformed differential operator leads to an updated integral operator under which the functions are integrated together with a weight function. For each differentiable function, it is possible to identify its q-deformed partner, which is useful to generalize other algebraic relations proper of the original functions. As an application of this proposal, in this work, a generalization of exponential and logarithmic functions is studied in such a way that their relationship with the thermodynamic functions, particularly the entropy, allows us to have a q-deformed expression of these. As a result, from a particular scaling function applied to the differential operator, a q-deformed arithmetic is obtained, leading to the generalization of the Tsallis entropy.Keywords: q-calculus, q-deformed arithmetic, entropy, exponential functions, thermodynamic functions
Procedia PDF Downloads 7019761 Data Driven Infrastructure Planning for Offshore Wind farms
Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree
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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data
Procedia PDF Downloads 7719760 3D Modelling and Numerical Analysis of Human Inner Ear by Means of Finite Elements Method
Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González
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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea
Procedia PDF Downloads 35819759 Computational Model of Human Cardiopulmonary System
Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek
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The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine
Procedia PDF Downloads 17019758 Logistic Regression Model versus Additive Model for Recurrent Event Data
Authors: Entisar A. Elgmati
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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event
Procedia PDF Downloads 62819757 Integration GIS–SCADA Power Systems to Enclosure Air Dispersion Model
Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey
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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system
Procedia PDF Downloads 35919756 Cerebrovascular Modeling: A Vessel Network Approach for Fluid Distribution
Authors: Karla E. Sanchez-Cazares, Kim H. Parker, Jennifer H. Tweedy
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The purpose of this work is to develop a simple compartmental model of cerebral fluid balance including blood and cerebrospinal-fluid (CSF). At the first level the cerebral arteries and veins are modelled as bifurcating trees with constant scaling factors between generations which are connected through a homogeneous microcirculation. The arteries and veins are assumed to be non-rigid and the cross-sectional area, resistance and mean pressure in each generation are determined as a function of blood volume flow rate. From the mean pressure and further assumptions about the variation of wall permeability, the transmural fluid flux can be calculated. The results suggest the next level of modelling where the cerebral vasculature is divided into three compartments; the large arteries, the small arteries, the capillaries and the veins with effective compliances and permeabilities derived from the detailed vascular model. These vascular compartments are then linked to other compartments describing the different CSF spaces, the cerebral ventricles and the subarachnoid space. This compartmental model is used to calculate the distribution of fluid in the cranium. Known volumes and flows for normal conditions are used to determine reasonable parameters for the model, which can then be used to help understand pathological behaviour and suggest clinical interventions.Keywords: cerebrovascular, compartmental model, CSF model, vascular network
Procedia PDF Downloads 26919755 Strategic Role of Fintechs in Evolving Financial Functions and Enhancing Corporate Resilience Amid Economic Crises
Authors: Ghizlane Barzi, Zineb Bamousse
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In an increasingly volatile global economic context characterized by recurring crises, the financial function of companies is called upon to play a strategic role not only in resource management but also in organizational resilience. The emergence of financial technologies (fintech) offers innovative tools capable of transforming this function by enhancing the efficiency of financial processes and increasing companies' ability to adapt and overcome economic shocks. However, despite the rapid rise of fintechs and their growing adoption by companies, there remain uncertainties regarding the real impact of these innovations on the financial resilience of organizations. Indeed, how do fintech-driven innovations transform the financial function, and to what extent does this transformation contribute to strengthening the financial resilience of companies in the face of contemporary crises? This research aims to explore these questions by examining the interrelationships between the financial function, fintech innovations, and corporate resilience, in order to identify optimization levers that could be adopted for better financial risk management.Keywords: finance, financial function, fintech, resilience, innovation
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