Search results for: parametric model

Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

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The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

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Authors: Fu Jinyu, Lin Jinguan

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This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

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Authors: Ross Calvert, Colin Whittaker, Alison Raby, Alistair G. L. Borthwick, Ton S. van den Bremer

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Large concentrations of plastic have polluted the seas in the last half century, with harmful effects on marine wildlife and potentially to human health. Plastic pollution will have lasting effects because it is expected to take hundreds or thousands of years for plastic to decay in the ocean. The question arises how waves transport plastic in the ocean. The predominant motion induced by waves creates ellipsoid orbits. However, these orbits do not close, resulting in a drift. This is defined as Stokes drift. If a particle is infinitesimally small and the same density as water, it will behave exactly as the water does, i.e., as a purely Lagrangian tracer. However, as the particle grows in size or changes density, it will behave differently. The particle will then have its own inertia, the fluid will exert drag on the particle, because there is relative velocity, and it will rise or sink depending on the density and whether it is on the free surface. Previously, plastic pollution has all been considered to be purely Lagrangian. However, the steepness of waves in the ocean is small, normally about α = k₀a = 0.1 (where k₀ is the wavenumber and a is the wave amplitude), this means that the mean drift flows are of the order of ten times smaller than the oscillatory velocities (Stokes drift is proportional to steepness squared, whilst the oscillatory velocities are proportional to the steepness). Thus, the particle motion must have the forces of the full motion, oscillatory and mean flow, as well as a dynamic buoyancy term to account for the free surface, to determine whether inertia is important. To track the motion of a floating inertial particle under wave action requires the fluid velocities, which form the forcing, and the full equations of motion of a particle to be solved. Starting with the equation of motion of a sphere in unsteady flow with viscous drag. Terms can added then be added to the equation of motion to better model floating plastic: a dynamic buoyancy to model a particle floating on the free surface, quadratic drag for larger particles and a slope sliding term. Using perturbation methods to order the equation of motion into sequentially solvable parts allows a parametric equation for the transport of inertial finite-sized floating particles to be derived. This parametric equation can then be validated using numerical simulations of the equation of motion and flume experiments. This paper presents a parametric equation for the transport of inertial floating finite-size particles by ocean waves. The equation shows an increase in Stokes drift for larger, less dense particles. The equation has been validated using numerical solutions of the equation of motion and laboratory flume experiments. The difference in the particle transport equation and a purely Lagrangian tracer is illustrated using worlds maps of the induced transport. This parametric transport equation would allow ocean-scale numerical models to include inertial effects of floating plastic when predicting or tracing the transport of pollutants.

Keywords: perturbation methods, plastic pollution transport, Stokes drift, wave flume experiments, wave-induced mean flow

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Authors: Hamid Maidat, Khedidja Bouhadef, Djamel Eddine Ameziani, Azzedine Abdedou

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This work consists of a numerical simulation of convective heat transfer in a vertical plane channel filled with a heat generating porous medium, in the absence of local thermal equilibrium. The walls are maintained to a constant temperature and the inlet velocity is uniform. The dynamic range is described by the Darcy-Brinkman model and the thermal field by two energy equations model. A dimensionless formulation is developed for performing a parametric study based on certain dimensionless groups such as, the Biot interstitial number, the thermal conductivity ratio and the volumetric heat generation. The governing equations are solved using the finite volume method, gave rise to a multitude of results concerning in particular the thermal field in the porous channel and the existence or not of the local thermal equilibrium.

Keywords: local thermal non equilibrium model, mixed convection, porous medium, power generation

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Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

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Authors: Ayon Mukherjee

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Covariate-adjusted response-adaptive (CARA) designs use the available responses to skew the treatment allocation in a clinical trial in towards treatment found at an interim stage to be best for a given patient's covariate profile. Extensive research has been done on various aspects of CARA designs with the patient responses assumed to follow a parametric model. However, ranges of application for such designs are limited in real-life clinical trials where the responses infrequently fit a certain parametric form. On the other hand, robust estimates for the covariate-adjusted treatment effects are obtained from the parametric assumption. To balance these two requirements, designs are developed which are free from distributional assumptions about the survival responses, relying only on the assumption of proportional hazards for the two treatment arms. The proposed designs are developed by deriving two types of optimum allocation designs, and also by using a distribution function to link the past allocation, covariate and response histories to the present allocation. The optimal designs are based on biased coin procedures, with a bias towards the better treatment arm. These are the doubly-adaptive biased coin design (DBCD) and the efficient randomized adaptive design (ERADE). The treatment allocation proportions for these designs converge to the expected target values, which are functions of the Cox regression coefficients that are estimated sequentially. These expected target values are derived based on constrained optimization problems and are updated as information accrues with sequential arrival of patients. The design based on the link function is derived using the distribution function of a probit model whose parameters are adjusted based on the covariate profile of the incoming patient. To apply such designs, the treatment allocation probabilities are sequentially modified based on the treatment allocation history, response history, previous patients’ covariates and also the covariates of the incoming patient. Given these information, an expression is obtained for the conditional probability of a patient allocation to a treatment arm. Based on simulation studies, it is found that the ERADE is preferable to the DBCD when the main aim is to minimize the variance of the observed allocation proportion and to maximize the power of the Wald test for a treatment difference. However, the former procedure being discrete tends to be slower in converging towards the expected target allocation proportion. The link function based design achieves the highest skewness of patient allocation to the best treatment arm and thus ethically is the best design. Other comparative merits of the proposed designs have been highlighted and their preferred areas of application are discussed. It is concluded that the proposed CARA designs can be considered as suitable alternatives to the traditional balanced randomization designs in survival trials in terms of the power of the Wald test, provided that response data are available during the recruitment phase of the trial to enable adaptations to the designs. Moreover, the proposed designs enable more patients to get treated with the better treatment during the trial thus making the designs more ethically attractive to the patients. An existing clinical trial has been redesigned using these methods.

Keywords: censored response, Cox regression, efficiency, ethics, optimal allocation, power, variability

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: Olga V. Kharchenko

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Applicability of a KTA crystal-based laser system with optical parametric oscillators (OPO) generation to lidar sounding of the atmosphere in the spectral range 3–4 µm is studied in this work. A technique based on differential absorption lidar (DIAL) method and differential optical absorption spectroscopy (DOAS) is developed for lidar sounding of trace atmospheric gases (TAG). The DIAL-DOAS technique is tested to estimate its efficiency for lidar sounding of atmospheric trace gases.

Keywords: atmosphere, lidar sounding, DIAL, DOAS, trace gases, nonlinear crystal

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Sheetal Kumar Parwar, J. Deb Barma, A. Majumder

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Submerged arc welding is a very complex process. It is a very efficient and high performance welding process. In this present study an attempt have been done to reduce the welding distortion by increased amount of oxide flux through TiO2 in submerged arc welding process. Care has been taken to avoid the excessiveness of the adding agent for attainment of significant results. Data Envelopment Analysis (DEA) based BAT algorithm is used for the parametric optimization purpose in which DEA Data Envelopment Analysis is used to convert multi response parameters into a single response parameter. The present study also helps to know the effectiveness of the addition of TiO2 in active flux during submerged arc welding process.

Keywords: BAT algorithm, design of experiment, optimization, submerged arc welding

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Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Muhammad Ajmair

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This empirical study followed structural vector auto regression (SVAR) approach proposed by the so-called AB-model of Amisano and Giannini (1997) to check the impact of relevant macroeconomic determinants on economic growth in Pakistan. Before that auto regressive distributive lag (ARDL) bound testing technique and time varying parametric approach along with general to specific approach was employed to find out relevant significant determinants of economic growth. To our best knowledge, no author made such a study that employed auto regressive distributive lag (ARDL) bound testing and time varying parametric approach with general to specific approach in empirical literature, but current study will bridge this gap. Annual data was taken from World Development Indicators (2014) during period 1976-2014. The widely-used Schwarz information criterion and Akaike information criterion were considered for the lag length in each estimated equation. Main findings of the study are that remittances received, gross national expenditures and inflation are found to be the best relevant positive and significant determinants of economic growth. Based on these empirical findings, we conclude that government should focus on overall economic growth augmenting factors while formulating any policy relevant to the concerned sector.

Keywords: economic growth, gross national expenditures, inflation, remittances

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Authors: Mahmoud Roushdy, Mohamed El Naggar, Ahmed Yehia Abdelaziz

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Anchored sheet pile has been used worldwide as front quay walls for decades. With the increase in vessel drafts and weights, those sheet pile walls need to be upgraded by increasing the depth of the dredging line in front of the wall. A system has recently been used to increase the depth in front of the wall by installing a separated platform supported on a deep foundation (so called Relieving Platform) behind the sheet pile wall. The platform is structurally separated from the front wall. This paper presents a numerical investigation utilizing finite element analysis on the behavior of separated relieve platforms installed within existing anchored sheet pile quay walls. The investigation was done in two steps: a verification step followed by a parametric study. In the verification step, the numerical model was verified based on field measurements performed by others. The validated model was extended within the parametric study to a series of models with different backfill soils, separation gap width, and number of pile rows supporting the platform. The results of the numerical investigation show that using stiff clay as backfill soil (neglecting consolidation) gives better performance for the front wall and the first pile row adjacent to sandy backfills. The degree of compaction of the sandy backfill slightly increases lateral deformations but reduces bending moment acting on pile rows, while the effect is minor on the front wall. In addition, the increase in the separation gap width gradually increases bending moments on the front wall regardless of the backfill soil type, while this effect is reversed on pile rows (gradually decrease). Finally, the paper studies the possibility of reducing the number of pile rows along with the separation to take advantage of the positive separation effect on piles.

Keywords: anchored sheet pile, relieving platform, separation gap, upgrade quay wall

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Authors: Chenhao Zhu

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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: Bessaad Taieb, Benbouali Abderrahmen

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Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Keywords: fuzzy adaptive control, behaviour model control, vector control, five-phase asynchronous machine

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete frames

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Authors: A. Hany A. Khater, G. M. Mostafa, M. R. Badawy

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The techno-economic analysis of the nuclear desalination is a very important tool that enables studying of the mutual effects between the nuclear power plant and the coupled desalination plant under different operating conditions, and hence investigating the feasibility of safe and economical production of potable water. For this purpose, a comprehensive model for both technical and economic performance evaluation of the nuclear desalination has been prepared. The developed model has the capability to be used in performing a parametric study for the performance measuring parameters of the nuclear desalination system. Also a sensitivity analysis of varying important factors such as interest/discount rate, power plant availability, fossil fuel prices, purchased electricity price, nuclear fuel cost, and specific base cost for both power and water plant has been conducted.

Keywords: uclear desalination, PWR, MED, MED-TVC, MSF, RO

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Authors: Alireza Mirzaee, Soosan Abdollahi, Mohammad Abdollahi

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Unreinforced Masonry (URM) wall is vulnerable in resisting horizontal load such as wind and seismic loading. It is due to the low tensile strength of masonry, the mortar connection between the brick units. URM structures are still widely used in the world as an infill wall and commonly constructed with door and window openings. This research aimed to investigate the behavior of URM wall with openings when horizontal load acting on it and developed load-drift relationship of the wall. The finite element (FE) method was chosen to numerically simulate the behavior of URM with openings. In this research, ABAQUS, commercially available FE software with explicit solver was employed. In order to ensure the numerical model can accurately represent the behavior of an URM wall, the model was validated for URM wall without openings using available experimental results. Load-displacement relationship of numerical model is well agreed with experimental results. Evidence shows the same load displacement curve shape obtained from the FE model. After validating the model, parametric study conducted on URM wall with openings to investigate the influence of area of openings and pre-compressive load on the horizontal load capacity of the wall. The result showed that the increasing of area of openings decreases the capacity of the wall in resisting horizontal loading. It is also well observed from the result that capacity of the wall increased with the increasing of pre-compressive load applied on the top of the walls.

Keywords: masonry constructions, performance at earthquake, MSJC-08 (ASD), bearing wall, tie-column

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Authors: Juan Francisco Reinoso Gordo, Francisco Javier Ariza-López, José Rodríguez Avi, Domingo Barrera Rosillo

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The evaluation of the quality of a data product is based on the comparison of the product with a reference of greater accuracy. In the case of MDE data products, quality assessment usually focuses on positional accuracy and few studies consider other terrain characteristics, such as slope and orientation. The proposal that is made consists of evaluating the similarity of two DEMs (a product and a reference), through the joint analysis of the distribution functions of the variables of interest, for example, elevations, slopes and orientations. This is a multivariable approach that focuses on distribution functions, not on single parameters such as mean values or dispersions (e.g. root mean squared error or variance). This is considered to be a more holistic approach. The use of the Kolmogorov-Smirnov test is proposed due to its non-parametric nature, since the distributions of the variables of interest cannot always be adequately modeled by parametric models (e.g. the Normal distribution model). In addition, its application to the multivariate case is carried out jointly by means of a single test on the convolution of the distribution functions of the variables considered, which avoids the use of corrections such as Bonferroni when several statistics hypothesis tests are carried out together. In this work, two DEM products have been considered, DEM02 with a resolution of 2x2 meters and DEM05 with a resolution of 5x5 meters, both generated by the National Geographic Institute of Spain. DEM02 is considered as the reference and DEM05 as the product to be evaluated. In addition, the slope and aspect derived models have been calculated by GIS operations on the two DEM datasets. Through sample simulation processes, the adequate behavior of the Kolmogorov-Smirnov statistical test has been verified when the null hypothesis is true, which allows calibrating the value of the statistic for the desired significance value (e.g. 5%). Once the process has been calibrated, the same process can be applied to compare the similarity of different DEM data sets (e.g. the DEM05 versus the DEM02). In summary, an innovative alternative for the comparison of DEM data sets based on a multinomial non-parametric perspective has been proposed by means of a single Kolmogorov-Smirnov test. This new approach could be extended to other DEM features of interest (e.g. curvature, etc.) and to more than three variables

Keywords: data quality, DEM, kolmogorov-smirnov test, multivariate DEM comparison

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Authors: Paulo Mendonca, Nzar Faiq Naqeshbandi

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The objective of this study is to propose an interactive design environment that outlines the underlying computational framework to reach self-supporting overhangs. The research demonstrates the digital printability of overhangs taking into consideration factors related to the geometry design, the material used, the applied support, and the printing set-up of slicing and the extruder inclination. Parametric design tools can contribute to the design phase, form-finding, and stability optimization of self-supporting structures while printing in order to hold the components in place until they are sufficiently advanced to support themselves. The challenge is to ensure the stability of the printed parts in the critical inclinations during the whole fabrication process. Facilitating the identification of parameterization will allow to predict and optimize the process. Later, in the light of the previous findings, some guidelines of simulations and physical tests are given to be conducted for estimating the structural and functional performance.

Keywords: additive manufacturing, overhangs, self-support overhangs, printability, parametric tools

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Authors: Bassim Shaheen Bachy, Jörg Franke

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In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multi-functional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: laser structuring, simulation, finite element analysis, thermal modeling

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Authors: Elzbieta Babula, Juhyun Park

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Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Yaxian Chen, Yeonhee Park

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Driven by evolving FDA recommendations, modern clinical trials demand innovative designs that strike a balance between statistical rigor and ethical considerations. Covariate-adjusted response-adaptive (CARA) designs bridge this gap by utilizing patient attributes and responses to skew treatment allocation in favor of the treatment that is best for an individual patient’s profile. However, existing CARA designs for survival outcomes often hinge on specific parametric models, constraining their applicability in clinical practice. In this article, we address this limitation by introducing a CARA design for survival outcomes (CARAS) based on the Cox model and a variance estimator. This method addresses issues of model misspecification and enhances the flexibility of the design. We also propose a group sequential overlapweighted log-rank test to preserve type I error rate in the context of group sequential trials using extensive simulation studies to demonstrate the clinical benefit, statistical efficiency, and robustness to model misspecification of the proposed method compared to traditional randomized controlled trial designs and response-adaptive randomization designs.

Keywords: cox model, log-rank test, optimal allocation ratio, overlap weight, survival outcome

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Authors: Xin-Yu Li, Dung-Ying Lin

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Fleet availability is a crucial indicator for an aircraft fleet. However, in practice, fleet planning involves many resource and safety constraints, such as annual and monthly flight training targets and maximum engine usage limits. Due to safety considerations, engines must be removed for mandatory maintenance and replacement of key components. This situation is known as the "threshold." The annual number of thresholds is a key factor in maintaining fleet availability. However, the traditional method heavily relies on experience and manual planning, which may result in ineffective engine usage and affect the flight missions. This study aims to address the challenges of fleet planning and availability maintenance in aircraft fleets with resource and safety constraints. The goal is to effectively optimize engine usage and maintenance tasks. This study has four objectives: minimizing the number of engine thresholds, minimizing the monthly lack of flight hours, minimizing the monthly excess of flight hours, and minimizing engine disassembly frequency. To solve the resulting formulation, this study uses parametric programming techniques and ϵ-constraint method to reformulate multi-objective problems into single-objective problems, efficiently generating Pareto fronts. This method is advantageous when handling multiple conflicting objectives. It allows for an effective trade-off between these competing objectives. Empirical results and managerial insights will be provided.

Keywords: aircraft fleet, engine utilization planning, multi-objective optimization, parametric method, Pareto optimality

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Authors: John Knight, Fuchun Li, Yan Xu

Abstract:

Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

Procedia PDF Downloads 368

Authors: Jongho Park, Jinwoong Choi, Sungnam Hong, Seung-Kyung Kye, Sun-Kyu Park

Abstract:

Recently, to cope with the rapidly changing construction trend because of aging infrastructures, modular bridge technology has been studied actively. Modular bridge is easily constructed by assembling standardized precast structure members in the field. It will be possible to construct rapidly and reduce construction cost efficiently. However, the shape examination of the transverse connection of T-type girder newly developed between the segmented modules is not performed. Therefore, the investigation of the connection shape is needed. In this study, shape of the modular T-girder bridge transverse connection was analyzed by finite element model that was verified in study which was verification of model for transverse connection using Abaqus. Connection angle was chosen as the parameter. The result of analyses showed that optimal value of angle is 130 degree.

Keywords: modular bridge, optimal transverse shape, parameter, FEM

Procedia PDF Downloads 650

Authors: A. Flammini, R. Morbidelli, C. Saltalippi

Abstract:

The increase of air surface temperature at global scale is a fact, with values around 0.85 ºC since the late nineteen century, as well as a significant change in main features of rainfall regime. Nevertheless, the detected climatic changes are not equally distributed all over the world, but exhibit specific characteristics in different regions. Therefore, studying the evolution of climatic indices in different geographical areas with a prefixed standard approach becomes very useful in order to analyze the existence of climatic trend and compare results. In this work, a methodology to investigate the climatic change and its effects on a wide set of climatic indices is proposed and applied at regional scale in the case study of a Mediterranean area, Umbria region in Italy. From data of the available temperature stations, nine temperature indices have been obtained and the existence of trends has been checked by applying the non-parametric Mann-Kendall test, while the non-parametric Pettitt test and the parametric Standard Normal Homogeneity Test (SNHT) have been applied to detect the presence of break points. In addition, aimed to characterize the rainfall regime, data from 11 rainfall stations have been used and a trend analysis has been performed on cumulative annual rainfall depth, daily rainfall, rainy days, and dry periods length. The results show a general increase in any temperature indices, even if with a trend pattern dependent of indices and stations, and a general decrease of cumulative annual rainfall and average daily rainfall, with a time rainfall distribution over the year different from the past.

Keywords: climatic change, temperature, rainfall regime, trend analysis

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Authors: Shamraiz Ahmad, Riaz Ahmad, Adnan Maqsood

Abstract:

This paper describes the application of 2k-design of experiment in order to screen the geometric parameters and experimental refinement of ceiling fan blades. The ratio of the air delivery to the power consumed is commonly known as service value (SV) in ceiling fan designer’s community. Service value was considered as the response for 56 inch ceiling fan and four geometric parameters (bend position at root, bend position at tip, bent angle at root and bent angle at tip) of blade were analyzed. With two levels, the 4-design parameters along with their eleven interactions were studied and design of experiment was employed for experimental arrangement. Blade manufacturing and testing were done in a medium scale enterprise. The objective was achieved and service value of ceiling fan was increased by 10.4 % without increasing the cost of production and manufacturing system. Experiments were designed and results were analyzed using Minitab® 16 software package.

Keywords: parametric screening, 2k-design of experiment, ceiling fan, service value, performance improvement

Procedia PDF Downloads 564