Search results for: seismic prediction equations

Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

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At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A³B⁵ and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si_1-xGe_x(x≤0.05) alloys grown by Czochralski technique is studied in initial and ⁶⁰Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: internal friction, shear modulus, gamma-irradiation, SiGe alloys

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Khalda Amr, Noha Eltaweel, Sherif Ismail, Hala Raslan

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Introduction: Osteoarthritis is the most common form of arthritis that involves the wearing away of the cartilage that caps the bones in the joints. While rheumatoid arthritis is an autoimmune disease in which the immune system attacks the joints, beginning with the lining of joints. In this study, we aimed to study the top deregulated miRNAs that might be the cause of pathogenesis in both diseases. Methods: Eight cases were recruited in this study: 4 rheumatoid arthritis (RA), 2 osteoarthritis (OA) patients, as well as 2 healthy controls. Total RNA was isolated from plasma to be subjected to miRNA profiling by NGS. Sequencing libraries were constructed and generated using the NEBNextR UltraTM small RNA Sample Prep Kit for Illumina R (NEB, USA), according to the manufacturer’s instructions. The quality of samples were checked using fastqc and multiQC. Results were compared RA vs Controls and OA vs. Controls. Target gene prediction and functional annotation of the deregulated miRNAs were done using Mienturnet. The top deregulated miRNAs in each disease were selected for further validation using qRT-PCR. Results: The average number of sequencing reads per sample exceeded 2.2 million, of which approximately 57% were mapped to the human reference genome. The top DEMs in RA vs controls were miR-6724-5p, miR-1469, miR-194-3p (up), miR-1468-5p, miR-486-3p (down). In comparison, the top DEMs in OA vs controls were miR-1908-3p, miR-122b-3p, miR-3960 (up), miR-1468-5p, miR-15b-3p (down). The functional enrichment of the selected top deregulated miRNAs revealed the highly enriched KEGG pathways and GO terms. Six of the deregulated miRNAs (miR-15b, -128, -194, -328, -542 and -3180) had multiple target genes in the RA pathway, so they are more likely to affect the RA pathogenesis. Conclusion: Six of our studied deregulated miRNAs (miR-15b, -128, -194, -328, -542 and -3180) might be highly involved in the disease pathogenesis. Further functional studies are crucial to assess their functions and actual target genes.

Keywords: next generation sequencing, mirnas, rheumatoid arthritis, osteoarthritis

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Authors: Anjelika Kremer, Irina Nachimov, Dan Justo

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Background: C-reactive protein (CRP) serum levels are commonly measured in hospitalized patients. Elevated admission CRP serum levels and in-hospital mortality has been seldom studied in the general population of elderly patients admitted to the acute Geriatrics department. Methods: A retrospective cross-sectional study was conducted at a tertiary medical center. Included were all elderly patients (age 65 years or more) admitted to a single acute Geriatrics department from the emergency room between April 2014 and January 2015. CRP serum levels were measured routinely in all patients upon the first 24 hours of admission. A logistic regression analysis was used to study if admission CRP serum levels were associated with in-hospital mortality independent of age, gender, functional status, and co-morbidities. Results: Overall, 498 elderly patients were included in the analysis: 306 (61.4%) female patients and 192 (38.6%) male patients. The mean age was 84.8±7.0 years (median: 85 years; IQR: 80-90 years). The mean admission CRP serum levels was 43.2±67.1 mg/l (median: 13.1 mg/l; IQR: 2.8-51.7 mg/l). Overall, 33 (6.6%) elderly patients died during the hospitalization. A logistic regression analysis showed that in-hospital mortality was independently associated with history of stroke (p < 0.0001), heart failure (p < 0.0001), and admission CRP serum levels (p < 0.0001) – and to a lesser extent with age (p = 0.042), collagen vascular disease (p=0.011), and recent venous thromboembolism (p=0.037). Receiver operating characteristic (ROC) curve showed that admission CRP serum levels predict in-hospital mortality fairly with an area under the curve (AUC) of 0.694 (p < 0.0001). Cut-off value with maximal sensitivity and specificity was 19.7 mg/L. Conclusions: Admission CRP serum levels may be used to predict in-hospital mortality in the general population of elderly patients admitted to the acute Geriatrics department.

Keywords: c-reactive protein, elderly, mortality, prediction

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Authors: Fatih Eren

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This research aims to find an answer to the question of which knowledge and skills do the Turkish urban planners need in their business practice. Understanding change in cities, making a prediction, making an urban decision and putting it into practice, working together with actors from different organizations from various academic disciplines, persuading people to accept something and developing good personal and professional relationships have become very complex and difficult in today’s world. The truth is that urban planners work in many institutions under various positions which are not similar to each other by field of activity and all planners are forced to develop some knowledge and skills for success in their business in Turkey. This study targets to explore what urban planners do in the global information age. The study is the product of a comprehensive nation-wide research. In-depth interviews were conducted with 174 experienced urban planners, who work in different public institutions and private companies under varied positions in the Turkish Planning System, to find out knowledge and skills needed by next-generation urban planners. The main characteristics of next-generation urban planners are defined; skills that planners needed today are explored in this paper. Findings show that the positivist (traditional) planning approach has given place to anti-positivist planning approaches in the Turkish Planning System so next-generation urban planners who seek success and want to carve out a niche for themselves in business life have to equip themselves with innovative skills. The result section also includes useful and instructive findings for planners about what is the meaning of being an urban planner and what is the ideal content and context of planning education at universities in the global age.

Keywords: global information age, Turkish Planning System, the institutional approach, urban planners, roles, skills, values

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Authors: Kizito Ugochukwu Nwajeri

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This paper explores the application of hybrid block methods for solving boundary value problems (BVPs), which are prevalent in various fields such as science, engineering, and applied mathematics. Traditionally, numerical approaches such as finite difference and shooting methods, often encounter challenges related to stability and convergence, particularly in the context of complex and nonlinear BVPs. To address these challenges, we propose a hybrid block method that integrates features from both single-step and multi-step techniques. This method allows for the simultaneous computation of multiple solution points while maintaining high accuracy. Specifically, we employ a combination of polynomial interpolation and collocation strategies to derive a system of equations that captures the behavior of the solution across the entire domain. By directly incorporating boundary conditions into the formulation, we enhance the stability and convergence properties of the numerical solution. Furthermore, we introduce an adaptive step-size mechanism to optimize performance based on the local behavior of the solution. This adjustment allows the method to respond effectively to variations in solution behavior, improving both accuracy and computational efficiency. Numerical tests on a variety of boundary value problems demonstrate the effectiveness of the hybrid block methods. These tests showcase significant improvements in accuracy and computational efficiency compared to conventional methods, indicating that our approach is robust and versatile. The results suggest that this hybrid block method is suitable for a wide range of applications in real-world problems, offering a promising alternative to existing numerical techniques.

Keywords: hybrid block methods, boundary value problem, polynomial interpolation, adaptive step-size control, collocation methods

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Authors: Sameer Jung Karki, Gokhan Saygili

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The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

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Authors: Rukayya Ibrahim Muazu, Aiduan Li Borrion, Julia A. Stegemann

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Biomass briquette gasification is regarded as a promising route for efficient briquette use in energy generation, fuels and other useful chemicals, however, previous research work has focused on briquette gasification in fixed bed gasifiers such as updraft and downdraft gasifiers. Fluidised bed gasifier has the potential to be effectively sized for medium or large scale. This study investigated the use of fuel briquettes produced from blends of rice husks and corn cobs biomass residues, in a bubbling fluidised bed gasifier. The study adopted a combination of numerical equations and Aspen Plus simulation software to predict the product gas (syngas) composition based on briquette's density and biomass composition (blend ratio of rice husks to corn cobs). The Aspen Plus model was based on an experimentally validated model from the literature. The results based on a briquette size of 32 mm diameter and relaxed density range of 500 to 650 kg/m3 indicated that fluidisation air required in the gasifier increased with an increase in briquette density, and the fluidisation air showed to be the controlling factor compared with the actual air required for gasification of the biomass briquettes. The mass flowrate of CO2 in the predicted syngas composition, increased with an increase in the air flow rate, while CO production decreased and H2 was almost constant. The H2/CO ratio for various blends of rice husks and corn cobs did not significantly change at the designed process air, but a significant difference of 1.0 for H2/CO ratio was observed at higher air flow rate, and between 10/90 to 90/10 blend ratio of rice husks to corn cobs. This implies the need for further understanding of biomass variability and hydrodynamic parameters on syngas composition in biomass briquette gasification.

Keywords: aspen plus, briquettes, fluidised bed, gasification, syngas

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Authors: Michał Lidner, Zbigniew SzcześNiak

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The ability to estimate blast load overpressure properly plays an important role in safety design of buildings. The issue of studying of blast loading on structural elements has been explored for many years. However, in many literature reports shock wave overpressure is estimated with simplified triangular or exponential distribution in time. This indicates some errors when comparing real and numerical reaction of elements. Nonetheless, it is possible to further improve setting similar to the real blast load overpressure function versus time. The paper presents a method of numerical analysis of the phenomenon of the air shock wave propagation. It uses Finite Volume Method and takes into account energy losses due to a heat transfer with respect to an adiabatic process rule. A system of three equations (conservation of mass, momentum and energy) describes the flow of a volume of gaseous medium in the area remote from building compartments, which can inhibit the movement of gas. For validation three cases of a shock wave flow were analyzed: a free field explosion, an explosion inside a steel insusceptible tube (the 1D case) and an explosion inside insusceptible cube (the 3D case). The results of numerical analysis were compared with the literature reports. Values of impulse, pressure, and its duration were studied. Finally, an overall good convergence of numerical results with experiments was achieved. Also the most important parameters were well reflected. Additionally analyses of dynamic response of one of considered structural element were made.

Keywords: adiabatic process, air shock wave, explosive, finite volume method

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Authors: Paula Pascoal-Faria, Rúben Pereira, Elodie Pinto, Miguel Belbut, Ana Rosa, Inês Sousa, Nuno Alves

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Apple bruise damage from harvesting, handling, transporting and sorting is considered to be the major source of reduced fruit quality, resulting in loss of profits for the entire fruit industry. The three factors which can physically cause fruit bruising are vibration, compression load and impact, the latter being the most common source of bruise damage. Therefore, prediction of the level of damage, stress distribution and deformation of the fruits under external force has become a very important challenge. In this study, experimental and numerical methods were used to better understand the impact caused when an apple is dropped from different heights onto a plastic surface and a conveyor belt. Results showed that the extent of fruit damage is significantly higher for plastic surface, being dependent on the height. In order to support the development of a biomimetic electronic device for the determination of fruit damage, the mechanical properties of the apple fruit were determined using mechanical tests. Preliminary results showed different values for the Young’s modulus according to the zone of the apple tested. Along with the mechanical characterization of the apple fruit, the development of the first two prototypes is discussed and the integration of the results obtained to construct the final element model of the apple is presented. This work will help to reduce significantly the bruise damage of fruits or vegetables during the entire processing which will allow the introduction of exportation destines and consequently an increase in the economic profits in this sector.

Keywords: apple, fruit damage, impact during crop and post-crop, mechanical characterization of the apple, numerical evaluation of fruit damage, electronic device

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Authors: Sally Heyeon Hwang

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Within decision theory, there are normative principles that dictate how one should act in addition to empirical theories of actual behavior. As a normative guide to one’s actual behavior, evidential or causal decision-theoretic equations allow one to identify outcomes with maximal utility values. The choice that each person makes, however, will, of course, differ according to varying assignments of weight and probability values. Regarding these different choices, it remains a subject of considerable philosophical controversy whether individual subjects have the capacity to exercise free will with respect to the assignment of probabilities, or whether instead the assignment is in some way constrained. A version of this question is given a precise form in Richard Jeffrey’s assumption that free will is necessary for Newcomb’s paradox to count as a decision problem. This paper will argue, against Jeffrey, that decision theory does not require the assumption of libertarian freedom. One of the hallmarks of decision-making is its application across a wide variety of contexts; the implications of a background assumption of free will is similarly varied. One constant across the contexts of decision is that there are always at least two levels of choice for a given agent, depending on the degree of prior constraint. Within the context of Newcomb’s problem, when the predictor is attempting to guess the choice the agent will make, he or she is analyzing the determined aspects of the agent such as past characteristics, experiences, and knowledge. On the other hand, as David Lewis’ backtracking argument concerning the relationship between past and present events brings to light, there are similarly varied ways in which the past can actually be dependent on the present. One implication of this argument is that even in deterministic settings, an agent can have more free will than it may seem. This paper will thus argue against the view that a stable background assumption of free will or determinism in decision theory is necessary, arguing instead for a compatibilist decision theory yielding a novel treatment of Newcomb’s problem.

Keywords: decision theory, compatibilism, free will, Newcomb’s problem

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Authors: V. Kuzhandai Velu, R. Ramesh

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Background and objectives: Acute myocardial infarction (AMI) is the most common cause of mortality and morbidity. Over the last decade, microRNAs (miRs) have emerged as a potential marker for detecting AMI. The current study evaluates the kinetics and importance of miRs in the differential diagnosis of ST-segment elevated MI (STEMI) and non-STEMI (NSTEMI) and its correlation to conventional biomarkers and to predict the immediate outcome of AMI for arrhythmias and left ventricular (LV) dysfunction. Materials and Method: A total of 100 AMI patients were recruited for the study. Routine cardiac biomarker and miRNA levels were measured during diagnosis and serially at admission, 6, 12, 24, and 72hrs. The baseline biochemical parameters were analyzed. The expression of miRs was compared between STEMI and NSTEMI at different time intervals. Diagnostic utility of miR-1, miR-133, miR-208, and miR-499 levels were analyzed by using RT-PCR and with various diagnostics statistical tools like ROC, odds ratio, and likelihood ratio. Results: The miR-1, miR-133, and miR-499 showed peak concentration at 6 hours, whereas miR-208 showed high significant differences at all time intervals. miR-133 demonstrated the maximum area under the curve at different time intervals in the differential diagnosis of STEMI and NSTEMI which was followed by miR-499 and miR-208. Evaluation of miRs for predicting arrhythmia and LV dysfunction using admission sample demonstrated that miR-1 (OR = 8.64; LR = 1.76) and miR-208 (OR = 26.25; LR = 5.96) showed maximum odds ratio and likelihood respectively. Conclusion: Circulating miRNA showed a highly significant difference between STEMI and NSTEMI in AMI patients. The peak was much earlier than the conventional biomarkers. miR-133, miR-208, and miR-499 can be used in the differential diagnosis of STEMI and NSTEMI, whereas miR-1 and miR-208 could be used in the prediction of arrhythmia and LV dysfunction, respectively.

Keywords: myocardial infarction, cardiac biomarkers, microRNA, arrhythmia, left ventricular dysfunction

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Authors: Sejin Jung, Dongho Kang, Byungsik Kim

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Assessing the impact of climate change requires the use of a multi-model ensemble (MME) to quantify uncertainties between scenarios and produce downscaled outlines for simulation of climate under the influence of different factors, including topography. This study decreases climate change scenarios from the 13 global climate models (GCMs) to assess the impacts of future climate change. Unlike South Korea, North Korea lacks in studies using climate change scenarios of the CoupledModelIntercomparisonProject (CMIP5), and only recently did the country start the projection of extreme precipitation episodes. One of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates high applicability of the Multi-Model Ensemble (MME). Furthermore, the study classifies climatic zones by applying the Köppen-Geiger climate classification system to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate (D) that covers the inland area for the reference climate is expected to shift into the temperate climate (C). The coefficient of variation (CVs) in the temperature ensemble is particularly low for the southern coast of the Korean peninsula, and accordingly, a high possibility of the shifting climatic zone of the coast is predicted. This research was supported by a grant (MOIS-DP-2015-05) of Disaster Prediction and Mitigation Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea).

Keywords: MME, North Korea, Koppen–Geiger, climatic zones, coefficient of variation, CV

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: Vishnu A., Ashesh Saha

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The operation of high-speed rotating machinery in industries is accompanied by rotor vibrations due to many factors. One of the primary instability mechanisms in a rotor system is the centrifugal force induced due to the eccentricity of the center of mass away from the center of rotation. These unwanted vibrations may lead to catastrophic fatigue failure. So, there is a need to control these rotor vibrations. In this work, control of rotor vibrations by using a 4-pole Radial Active Magnetic Bearing (RAMB) as an actuator is analysed. A continuous rotor system model is considered for the analysis. Several important factors, like the gyroscopic effect and rotary inertia of the shaft and disc, are incorporated into this model. The large deflection of the shaft and the restriction to axial motion of the shaft at the bearings result in nonlinearities in the system governing equation. The rotor system is modeled in such a way that the system dynamics can be related to the geometric and material properties of the shaft and disc. The mathematical model of the rotor system is developed by incorporating the control forces generated by the RAMB. A simple PD controller is used for the attenuation of system vibrations. An analytical expression for the amplitude and phase equations is derived using the Method of Multiple Scales (MMS). Analytical results are verified with the numerical results obtained using an ‘ode’ solver in-built into MATLAB Software. The control force is found to be effective in attenuating the system vibrations. The multi-valued solutions leading to the jump phenomenon are also eliminated with a proper choice of control gains. Most interestingly, the shape of the backbone curves can also be altered for certain values of control parameters.

Keywords: rotor dynamics, continuous rotor system model, active magnetic bearing, PD controller, method of multiple scales, backbone curve

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Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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Authors: Nasim Abuali Galehdari, Thomas J. Ryan, Ajit D. Kelkar

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In recent years, nanotechnology has played an important role in the design of an efficient radiation shielding polymeric composites. It is well known that, high loading of nanomaterials with radiation absorption properties can enhance the radiation attenuation efficiency of shielding structures. However, due to difficulties in dispersion of nanomaterials into polymer matrices, there has been a limitation in higher loading percentages of nanoparticles in the polymer matrix. Therefore, the objective of the present work is to provide a methodology to fabricate and then to characterize the functionally graded radiation shielding structures, which can provide an efficient radiation absorption property along with good structural integrity. Sandwich structures composed of Ultra High Molecular Weight Polyethylene (UHMWPE) fabric as face sheets and functionally graded epoxy nanocomposite as core material were fabricated. A method to fabricate a functionally graded core panel with controllable gradient dispersion of nanoparticles is discussed. In order to optimize the design of functionally graded sandwich composites and to analyze the stress distribution throughout the sandwich composite thickness, a finite element method was used. The sandwich panels were discretized using 3-Dimensional 8 nodded brick elements. Classical laminate analysis in conjunction with simplified micromechanics equations were used to obtain the properties of the face sheets. The presented finite element model would provide insight into deformation and damage mechanics of the functionally graded sandwich composites from the structural point of view.

Keywords: nanotechnology, functionally graded material, radiation shielding, sandwich composites, finite element method

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Authors: Sabine Pau, Sophia Volz, Emanuel Bauer, Amelie De Gregorio, Frank Reister, Wolfgang Janni, Florian Ebner

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Purpose: The umbilical cord pH is a well evaluated contributor for prediction of neonatal outcome. This study correlates nenonatal umbilical cord pH with the weekday of delivery, the time of birth as well as the staff hand over times (midwifes and doctors). Material and Methods: This retrospective study included all deliveries of a 20 year period (1994-2014) at our primary obstetric center. All deliveries with a newborn cord pH under 7,20 were included in this analysis (6929 of 48974 deliveries (14,4%)). Further subgroups were formed according to the pH (< 7,05; 7,05 – 7,09; 7,10 – 7,14; 7,15 – 7,19). The data were then separated in day- and night time (8am-8pm/8pm-8am) for a first analysis. Finally, handover times were defined at 6 am – 6.30 am, 2 pm -2.30 pm, 10 pm- 10.30 pm (midwives) and for the doctors 8-8.30 am, 4 – 4.30 pm (Monday- Thursday); 2 pm -2.30 pm (Friday) and 9 am – 9.30 am (weekend). Routinely a shift consists of at least three doctors as well as three midwives. Results: During the last 20 years, 6929 neonates were born with an umbilical cord ph < 7,20 ( < 7,05 : 7,1%; 7,05 – 7,09 : 10,9%; 7,10 – 7,14 : 30,2%; 7,15 – 7,19:51,8%). There was no significant difference between either night/day delivery (p = 0.408), delivery on different weekdays (p = 0.253), delivery between Monday to Thursday, Friday and the weekend (p = 0.496 ) or delivery during the handover times of the doctors as well as the midwives (p = 0.221). Even the standard deviation showed no differences between the groups. Conclusion: Despite an increased workload over the last 20 years, the standard of care remains high even during the handover times and night shifts. This applies for midwives and doctors. As the neonatal outcome depends on various factors, further studies are necessary to take more factors influencing the fetal outcome into consideration. In order to maintain this high standard of care, an adaption of work-load and changing conditions is necessary.

Keywords: delivery, fetal umbilical cord pH, day time, hand over times

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Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

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A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 146

Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

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Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

Procedia PDF Downloads 236

Authors: Sayantika Biswas, Dipanshu Sur, Amitoj Athwal, Ratnabali Chakravorty

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Title: Impact of serum estrogen and progesterone levels in the outcome pregnancy rate in frozen embryo transfer cycles. A prospective cohort study Objective: The aim of the current study was to evaluate the effect of serum estradiol (E2) and progesterone (P4) levels at different time points on pregnancy outcomes in frozen embryo transfer (FET) cycles. Materials & Method: A prospective cohort study was performed in patients undergoing frozen embryo transfer. Patients under age 37 years of age with at least one good blastocyst or three good day 3 embryos were included in the study. For endometrial preparation, 14 days of oral estradiol use (2X2 mg for 5 days. 3X2 mg for 4 days, and 4X2 mg for 5 days) was followed by vaginal progesterone twice a day and 50 mg intramuscular progesterone twice a day. Embryo transfer was scheduled 72-76 hrs or 116-120hrs after the initiation of progesterone. Serum E2 and P4 levels were examined at 4 times a) at the start of the menstrual cycle prior to the hormone supplementation. b) on the day of P4 start. c) on the day of ET. d) on the third day after ET. Result: A total 41 women were included in this study (mean age 31.8; SD 2.8). Clinical pregnancy rate was 65.55%. Serum E2 levels on at the start of the menstrual cycle prior to the hormone supplementation and on the day of P4 start were high in patients who achieved pregnancy compared to who did not (P=0.005 and P=0.019 respectively). P4 levels on on the day of ET were also high in patients with clinical pregnancy. On the day of P4 start, a serum E2 threshold of 186.4 pg/ml had a sensitivity of 82%, and P4 had a sensitivity of 71% for the prediction of clinical pregnancy at the threshold value 16.00 ng/ml. Conclusion: In women undergoing FET with hormone replacement, serum E2 level >186.4 pg/ml on the day of the start of progesterone and serum P4 levels >16.00 ng/ml on embryo transfer day are associated with clinical pregnancy.

Keywords: serum estradiol, serum progesterone, clinical pregnancy, frozen embryo transfer

Procedia PDF Downloads 75

Authors: Jerzy Merkisz, Pawel Fuc, Piotr Lijewski, Andrzej Ziolkowski, Pawel Czarkowski

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The paper presents preliminary results of the development of an automotive exhaust gas energy recovery module. The aim of the performed analyses was to select the geometry of the heat exchanger that would ensure the highest possible transfer of heat at minimum heat flow losses. The starting point for the analyses was a straight portion of a pipe, from which the exhaust system of the tested vehicle was made. The design of the heat exchanger had a cylindrical cross-section, was 300 mm long and was fitted with a diffuser and a confusor. The model works were performed for the mentioned geometry utilizing the finite volume method based on the Ansys CFX v12.1 and v14 software. This method consisted in dividing of the system into small control volumes for which the exhaust gas velocity and pressure calculations were performed using the Navier-Stockes equations. The heat exchange in the system was modeled based on the enthalpy balance. The temperature growth resulting from the acting viscosity was not taken into account. The heat transfer on the fluid/solid boundary in the wall layer with the turbulent flow was done based on an arbitrarily adopted dimensionless temperature. The boundary conditions adopted in the analyses included the convective condition of heat transfer on the outer surface of the heat exchanger and the mass flow and temperature of the exhaust gas at the inlet. The mass flow and temperature of the exhaust gas were assumed based on the measurements performed in actual traffic using portable PEMS analyzers. The research object was a passenger vehicle fitted with a 1.9 dm3 85 kW diesel engine. The tests were performed in city traffic conditions.

Keywords: waste heat recovery, heat exchanger, CFD simulation, pems

Procedia PDF Downloads 571

Authors: Canan Türeli̇, İrem Nur Yeşi̇lyurt

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A total of nine stomatopod crustaceans have been reported from the eastern Mediterranean, with the eight from the Turkey coasts and three from the Levantine coast of Turkey (Squilla massavensis (Linnaeus,1758), Erugosquilla massavensis (Kossmann, 1880), Clorida albolitura (Ahyong&Naiyanetr, 2000). E. massavensis is the most successful Red Sea immigrant, and it is now the dominant eastern Levantine stomatopod. At this research, carapace length/total length- weight relationship of 2 erythrean mantis shrimp, E. massavensis and C. albolitura was studied in Yumurtalık Cove, in the Northeastern Mediterranean of Turkey. Samples were collected monthly from July 2014 to June 2015 (except February), using bottom trawl net into three different depth strata; 0- 10 m, 10-20 m, 20-50m. E. massavensis samples were caught all studied time, except winter, in the three depth range but C. albolitura samples were caught only in July, October and May's months. A total of 572 specimens of the E. massavensis and 12 specimens of the C. albolitura were collected and analyzed. Morphometric equations for the conversions of total length and weight, carapace lengths were constructed for males, females, combined sexes for E. massavensis and C. albolitura. The b-values for total length (TL)-weight (W) in males and females for E. massavensis were 2.738 and 2.725 respectively and for carapace length (CL)-total length (TL) they were 1.041 and 0.978, relatively. The b-values (total length-weight) were determined for combined sexes of E. massavensis and C. albolitura as: 2.771, 1.852 relatively. In both species, the relative growth of weight and total length was found highly positively allometric. However, carapace length showed negative allometry in females of E. Massavensis.

Keywords: Clorida albolitura, Erugosquilla massavensis, Erythrean stomatopod, length/length-weight relationships

Procedia PDF Downloads 290

Authors: Somya R. Patro, Arnab Banerjee, G. V. Ramana

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A flexural beam carrying elastically mounted concentrated masses, such as engines, motors, oscillators, or vibration absorbers, is often encountered in mechanical, civil, and aeronautical engineering domains. To prevent resonance conditions, the designers must predict the natural frequencies of such a constrained beam system. This paper investigates experimental and analytical studies on vibration suppression in a cantilever beam with a tip mass with the help of spring-mass to achieve local resonance conditions. The system consists of a 3D printed polylactic acid (PLA) beam screwed at the base plate of the shaker system. The top of the free end is connected by an accelerometer which also acts as a tip mass. A spring and a mass are attached at the bottom to replicate the mechanism of the spring-mass resonator. The Fast Fourier Transform (FFT) algorithm converts time acceleration plots into frequency amplitude plots from which transmittance is calculated as a function of the excitation frequency. The mathematical formulation is based on the transfer matrix method, and the governing differential equations are based on Euler Bernoulli's beam theory. The experimental results are successfully validated with the analytical results, providing us essential confidence in our proposed methodology. The beam spring-mass system is then converted to an equivalent two-degree of freedom system, from which frequency response function is obtained. The H2 optimization technique is also used to obtain the closed-form expression of optimum spring stiffness, which shows the influence of spring stiffness on the system's natural frequency and vibration response.

Keywords: euler bernoulli beam theory, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

Procedia PDF Downloads 100

Authors: Kizito Ugochukwu Nwajeri

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This paper presents a distinct approach to solving fractional dynamical systems using hybrid block methods (HBMs). Fractional calculus extends the concept of derivatives and integrals to non-integer orders and finds increasing application in fields such as physics, engineering, and finance. However, traditional numerical techniques often struggle to accurately capture the complex behaviors exhibited by these systems. To address this challenge, we develop HBMs that integrate single-step and multi-step methods, enabling the simultaneous computation of multiple solution points while maintaining high accuracy. Our approach employs polynomial interpolation and collocation techniques to derive a system of equations that effectively models the dynamics of fractional systems. We also directly incorporate boundary and initial conditions into the formulation, enhancing the stability and convergence properties of the numerical solution. An adaptive step-size mechanism is introduced to optimize performance based on the local behavior of the solution. Extensive numerical simulations are conducted to evaluate the proposed methods, demonstrating significant improvements in accuracy and efficiency compared to traditional numerical approaches. The results indicate that our hybrid block methods are robust and versatile, making them suitable for a wide range of applications involving fractional dynamical systems. This work contributes to the existing literature by providing an effective numerical framework for analyzing complex behaviors in fractional systems, thereby opening new avenues for research and practical implementation across various disciplines.

Keywords: fractional calculus, numerical simulation, stability and convergence, Adaptive step-size mechanism, collocation methods

Procedia PDF Downloads 32

Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 148

Authors: Foad Hassaninejadafarahani, Scott Ormiston

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Reflux condensation occurs in a vertical channels and tubes when there is an upward core flow of vapor (or gas-vapor mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapor-gas mixture (or pure vapor) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapor core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on a finite volume method and a co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and pressure profiles, as well as axial variations of film thickness, Nusselt number and interface gas mass fraction.

Keywords: Reflux, Condensation, CFD-Two Phase, Nusselt number

Procedia PDF Downloads 358

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

Procedia PDF Downloads 92