Search results for: equation model

Authors: Wikanda Boonma, Jang Hyunmi

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Smart tourism applications (STAs) play an important role in tourism to enhance the quality tourism experience and add value to tourists with accurate information, better decision support, greater time-saving, and providing more personalized information to meet tourists’ expectations. This paper intends to develop and investigate the effect of smart tourism applications on memorable tourism experiences in enhancing tourist satisfaction and destination loyalty. Questionnaires were distributed to tourists who are traveling in Bangkok, Thailand. A structural equation method was used to find the relationship among smart tourism technology attributes, the perceived value of the STAs, memorable tourism experience, tourist satisfaction, and destination loyalty. The findings of this study provide insight into the critical role of smart tourism applications, which create chances for smart tourism development. Additionally, some theoretical and managerial implications were derived from the findings.

Keywords: smart tourism applications, memorable tourism experience, tourist satisfaction, destination loyalty

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Authors: Ayan Giri, Lukaranjan Phukan, Shantanu Karmakar

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Structure and tectonics play a vital role in ore genesis and deposition. The existence of a swelling structure below the current level of a mine leads to the discovery of ores below some permeant developments of the mine. The discovery and the extraction of the ore body are very critical to sustain the business requirement of the mine. The challenge was to extract the ore without hampering the global stability of the mine. In order to do so, different mining options were considered and analysed by numerical modelling in FLAC3d software. The constitutive model prepared for this simulation is the improved unified constitutive model, which can better and more accurately predict the stress-strain relationships in a continuum model. The IUCM employs the Hoek-Brown criterion to determine the instantaneous Mohr-Coulomb parameters cohesion (c) and friction (ɸ) at each level of confining stress. The extra swelled part can be dimensioned as north-south strike width 50m, east-west strike width 50m. On the north side, already a stope (P1) is excavated of the dimension of 25m NS width. The different options considered were (a) Open stoping of extraction of southern part (P0) of 50m to the full extent, (b) Extraction of the southern part of 25m, then filling of both the primaries and extraction of secondary (S0) 25m in between. (c) Extraction of the southern part (P0) completely, preceded by backfill and modify the design of the secondary (S0) for the overall stability of the permanent excavation above the stoping.

Keywords: extraction, IUCM, FLAC 3D, stoping, tectonics

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

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Authors: Mohamed Elassaly

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The damage status of RC buildings is greatly influenced by the characteristics of the imposed ground motion. Peak Ground Acceleration and frequency contents are considered the main two factors that affect ground motion characteristics; hence, affecting the seismic response of RC structures and consequently their damage state. A detailed investigation on the combined effects of these two factors on damage assessment of RC buildings, is carried out. Twenty one earthquake records are analyzed and arranged into three groups, according to their frequency contents. These records are used in an investigation to define the expected damage state that would be attained by RC buildings, if subjected to varying ground motion characteristics. The damage assessment is conducted through examining drift ratios and damage indices of the overall structure and the significant structural components of RC building. Base and story shear of RC building model, are also investigated, for cases when the model is subjected to the chosen twenty one earthquake records. Nonlinear dynamic analyses are performed on a 2-dimensional model of a 12-story R.C. building.

Keywords: damage, frequency content, ground motion, PGA, RC building, seismic

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Authors: Navarat Sachayansrisakul, Nattawat Ponnara

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Human beings are driving forces for any unit of societies, whether it would be in a family, communities, industries or even organizations. However, as our humanity progresses, the reliance has shifted from human to machineries and technologies. One main challenge when dealing with more than one person is conflict often resulted. If the conflict is properly managed, then economic development also follows. In order to achieve positive outcome of conflict, it is believed that the management comes from within individual entrepreneurs. As such, this is a unique study as it looks into the spiritual side of humans as business people and applies to the business environment with the focus on moral and ethical framework in order for sustainable development. This study aims to provide a model of how to positively manage conflict without compromising the ethical and moral standards of the businesses. Sustainability in this study is achieved through the Buddhists’ aim for liberation in which it works on the balanced approach to solving conflict. Buddhists’ livelihood is established on simplicity and non-violence while contributing not to only one’s self but those around them such as the stake holders of the businesses and the communities. According to Buddhist principles and some findings, a model called ‘The Bestination Conflict Management’ was developed. Bestination model offers an alternative approach for entrepreneurs to achieve sustainability along with intrinsic and extrinsic rewards that benefit the well-beings of the owners, the stakeholders and the communities involved. This research study identifies ‘Conflict Management’ model as having goodwill and wisdom as a base, then moral motivation as the next level up to have a disciplines in order to keep a unit well cooperated.

Keywords: sustainable, entrepreneurs, Buddhist, moral, ethics, conflict

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Authors: Kayode Balogun, Femi Ayoola

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Crime is at alarming rate in this part of world and there are many factors that are contributing to this antisocietal behaviour both among the youths and old. In this work, principal component analysis (PCA) was used as a tool to reduce the dimensionality and to really know those variables that were crime prone in the study region. Data were collected on twenty-eight crime variables from National Bureau of Statistics (NBS) databank for a period of fifteen years, while retaining as much of the information as possible. We use PCA in this study to know the number of major variables and contributors to the crime in the Southwest Nigeria. The results of our analysis revealed that there were eight principal variables have been retained using the Scree plot and Loading plot which implies an eight-equation solution will be appropriate for the data. The eight components explained 93.81% of the total variation in the data set. We also found that the highest and commonly committed crimes in the Southwestern Nigeria were: Assault, Grievous Harm and Wounding, theft/stealing, burglary, house breaking, false pretence, unlawful arms possession and breach of public peace.

Keywords: crime rates, data, Southwest Nigeria, principal component analysis, variables

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Authors: Ahmed A. Khamis, Sherif A. Ibrahim, Mahmoud El Khatieb, Mohamed A. Barakat

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Parametric design is an icon of the modern architectural that facilitate taking complex design decisions counting on altering various design parameters. Double skin facades are one of the parametric applications for using parametric designs. This paper opts to enhance different daylight parameters of a selected case study office building in Cairo using parametric double skin facade. First, the design and optimization process executed utilizing Grasshopper parametric design software which is a plugin in rhino. The daylighting performance of the base case building model was compared with the one used the double façade showing an enhancement in daylighting performance indicators like glare and task illuminance in the modified model, execution drawings are made for the optimized design to be executed through Revit, followed by computerized digital fabrication stages of the designed model with various scales to reach the final design decisions using Simplify 3D for mock-up digital fabrication

Keywords: parametric design, double skin facades, digital fabrication, grasshopper, simplify 3D

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Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

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Software architecture plays a key role in software development but absence of formal description of software architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for software architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate software architectural design information.

Keywords: semantic-based software architecture, software architecture, ontology, software engineering

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Authors: Thiyam Tamphasana Devi, Bimlesh Kumar

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A Computational Fluid Dynamics (CFD) technique has been applied to simulate the gas-liquid phase in double stirred tank of Rushton impeller. Eulerian-Eulerian model was adopted to simulate the multiphase with standard correlation of Schiller and Naumann for drag co-efficient. The turbulence was modeled by using standard k-ε turbulence model. The present CFD model predicts flow pattern, local gas hold-up, and local specific area. It also predicts local kLa (mass transfer rate) for single impeller. The predicted results were compared with experimental and CFD results of published literature. The predicted results are slightly over predicted with the experimental results; however, it is in reasonable agreement with other simulated results of published literature.

Keywords: Eulerian-Eulerian, gas-hold up, gas-liquid phase, local mass transfer rate, local specific area, Rushton Impeller

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Authors: A. Giniatoulline

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A nonlinear model of the mathematical fluid dynamics which describes the motion of an incompressible viscous rotating fluid in a homogeneous gravitational field is considered. The model is a generalization of the known Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density. An explicit algorithm for the solution is constructed, and the proof of the existence and uniqueness theorems for the strong solution of the nonlinear problem is given. For the linear case, the localization and the structure of the spectrum of inner waves are also investigated.

Keywords: Galerkin method, Navier-Stokes equations, nonlinear partial differential equations, Sobolev spaces, stratified fluid

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Authors: Awad Khireldin, Colin Law

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Runways are the major infrastructure of airports around the world. Efficient operations of runways are key to ensure that airports are running smoothly with minimal delays. There are many factors that affect the efficiency of runway operations, such as the aircraft wake separation, runways system configuration, the fleet mix, and the runways separation distance. This paper aims to address how to maximize runway operations using a Discrete Event Simulation model. A case study of Cairo International Airport (CIA) is developed to maximize the utilizing of three parallel runways using a simulation model. Different scenarios have been designed where every runway could be assigned for arrival, departure, or mixed operations. A benchmarking study was also included to compare the actual to the proposed results to spot the potential improvements. The simulation model shows that there is a significant difference in utilization and delays between the actual and the proposed ones, there are several recommendations that can be provided to airport management, in the short and long term, to increase the efficiency and to reduce the delays. By including the recommendation with different operations scenarios, such as upgrading the airport slot Coordination from Level 1 to Level 2 in the short term. In the long run, discuss the possibilities to increase the International Air Transport association (IATA) slot coordination to Level 3 as more flights are expected to be handled by the airport. Technological advancements such as radar in the approach full airside simulation model could improve the airport performance where the airport is recommended to review the standard operations procedures with the appropriate authorities. Also, the airport can adopt a future operational plan to accommodate the forecasted additional traffic density in case of adding a fourth terminal building to increase the airport capacity.

Keywords: airport performance, runway, discrete event simulation, capacity, airside

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Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

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The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Morteza Esfandiari, Shabnam Jabari, Heather MacGrath, David Coleman

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Flood is a severe issue in different places in the world as well as the city of Fredericton, New Brunswick, Canada. The downtown area of Fredericton is close to the Saint John River, which is susceptible to flood around May every year. Recently, the frequency of flooding seems to be increased, especially after the fact that the downtown area and surrounding urban/agricultural lands got flooded in two consecutive years in 2018 and 2019. In order to have an explicit vision of flood span and damage to affected areas, it is necessary to use either flood inundation modelling or satellite data. Due to contingent availability and weather dependency of optical satellites, and limited existing data for the high cost of hydrodynamic models, it is not always feasible to rely on these sources of data to generate quality flood maps after or during the catastrophe. Height Above the Nearest Drainage (HAND), a state-of-the-art topo-hydrological index, normalizes the height of a basin based on the relative elevation along with the stream network and specifies the gravitational or the relative drainage potential of an area. HAND is a relative height difference between the stream network and each cell on a Digital Terrain Model (DTM). The stream layer is provided through a multi-step, time-consuming process which does not always result in an optimal representation of the river centerline depending on the topographic complexity of that region. HAND is used in numerous case studies with quite acceptable and sometimes unexpected results because of natural and human-made features on the surface of the earth. Some of these features might cause a disturbance in the generated model, and consequently, the model might not be able to predict the flow simulation accurately. We propose to include a previously existing stream layer generated by the province of New Brunswick and benefit from culvert maps to improve the water flow simulation and accordingly the accuracy of HAND model. By considering these parameters in our processing, we were able to increase the accuracy of the model from nearly 74% to almost 92%. The improved model can be used for generating highly accurate flood maps, which is necessary for future urban planning and flood damage estimation without any need for satellite imagery or hydrodynamic computations.

Keywords: HAND, DTM, rapid floodplain, simplified conceptual models

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Authors: Ali Akyar, Osman Serdar Gedik

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Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction.

Keywords: monocular depth estimation, thermal dataset, benchmarking, vision transformers

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Authors: J. H. Park, R. H. Hwang, K. B. Yi

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Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

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Authors: Melvin Mothoa

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Small Micro and Medium Enterprises are very significant for the development of their market economies. They are the main creators of the new working places, and they present a vital core of the market economy in countries across the globe. Access to finance is identified as crucial for small, micro, and medium-sized enterprises for their growth and innovation. This paper is conceived to propose a perception-based SMME framework to aid in access to financial support. Furthermore, the study will address issues that impede SMMEs in South Africa from obtaining finance from financial institutions. The framework will be tested against data collected from 200 Small Micro & Medium Enterprises in the Gauteng province of South Africa. The study adopts a quantitative method, and the delivery of self-administered questionnaires to SMMEs will be the primary data collection tool. Structural equation modeling will be used to further analyse the data collected.

Keywords: finance, small business, growth, development

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Authors: Olushola S. Ayanda, Olalekan S. Fatoki, Folahan A. Adekola, Bhekumusa J. Ximba, Cecilia O. Akintayo

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In the present study, the kinetics, equilibrium and thermodynamics of the adsorption of triphenyltin (TPT) from TPT-contaminated water onto nanoSiO2/fly ash/activated carbon composite was investigated in batch adsorption system. Equilibrium adsorption data were analyzed using Langmuir, Freundlich, Temkin and Dubinin–Radushkevich (D-R) isotherm models. Pseudo first- and second-order, Elovich and fractional power models were applied to test the kinetic data and in order to understand the mechanism of adsorption, thermodynamic parameters such as ΔG°, ΔSo and ΔH° were also calculated. The results showed a very good compliance with pseudo second-order equation while the Freundlich and D-R models fit the experiment data. Approximately 99.999 % TPT was removed from the initial concentration of 100 mg/L TPT at 80oC, contact time of 60 min, pH 8 and a stirring speed of 200 rpm. Thus, nanoSiO2/fly ash/activated carbon composite could be used as effective adsorbent for the removal of TPT from contaminated water and wastewater.

Keywords: isotherm, kinetics, nanoSiO₂/fly ash/activated carbon composite, tributyltin

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Authors: Moon-Soo Kim

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In order to cope with the increasing demand for multidisciplinary learning between academy and industry, a collaborative teaching and learning model and related operational tools enabling applications to engineering education are essential. This study proposes a web-based collaborative framework for interactive teaching and learning between academy and industry as an initial step for the development of a web- and mobile-based integrated system for both engineering students and industrial practitioners. The proposed web-based collaborative teaching and learning framework defines several entities such as learner, solver and supporter or sponsor for industrial problems, and also has a systematic architecture to build information system including diverse functions enabling effective interaction among the defined entities regardless of time and places. Furthermore, the framework, which includes knowledge and information self-reinforcing mechanism, focuses on the previous problem-solving records as well as subsequent learners’ creative reusing in solving process of new problems.

Keywords: collaborative teaching and learning model, academy and industry, web-based collaborative framework, self-reinforcing mechanism

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Authors: F. A. Hassona, M. D. Hashem, R. I. Melek, B. M. Hakeem

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A differential settlement at the end of a bridge near the interface between the abutment and the embankment is a persistent problem for highway agencies. The differential settlement produces the common ‘bump at the end of the bridge’. Reduction in steering response, distraction to the driver, added risk and expense to maintenance operation, and reduction in a transportation agency’s public image are all undesirable effects of these uneven and irregular transitions. This paper attempts to simulate the bump at the end of the bridge using PLAXIS finite element 2D program. PLAXIS was used to simulate a laboratory model called Bridge to Embankment Simulator of Transition (B.E.S.T.) device which was built by others to investigate this problem. A total of six numerical simulations were conducted using hardening- soil model with rational assumptions of missing soil parameters to estimate the bump at the end of the bridge. The results show good agreements between the numerical and the laboratory models. Important factors influencing bumps at bridge ends were also addressed in light of the model results.

Keywords: bridge approach slabs, bridge bump, hardening-soil, PLAXIS 2D, settlement

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Defne Uz

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Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

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Authors: Barenten Suciu, Yoshiki Tsuji

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In this paper, a theoretical investigation on the dynamic characteristics of one degree of freedom vibration system equipped with inerter of variable inertance, is presented. Differential equation of movement was solved under proper initial conditions in the case of free undamped/damped vibration, considered in the absence/presence of the inerter in the mechanical system. Influence of inertance on the amplitude of vibration, phase angle, natural frequency, damping ratio, and logarithmic decrement was clarified. It was mainly found that the inerter decreases the natural frequency of the undamped system and also of the damped system if the damping ratio is below 0.707. On the other hand, the inerter increases the natural frequency of the damped system if the damping ratio exceeds 0.707. Results obtained in this work are useful for the adequate design of inerters.

Keywords: damping, frequency control, inerter, one degree of freedom vibration system, parallel connection, variable inertance

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Authors: Paramita Sekar Ayu, Sunjaya Deni Kurniadi, Yamazaki Chiho, Hilfi Lukman, Koyama Hiroshi

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Social cohesion, or closeness among members of society, is an important determinant of population health. A cohesive society is a crucial societal condition for a positive life evaluation and subjective wellbeing, and people living in a cohesive society are happier and more satisfied with life and achieve better health status. The objective of this study was to compose and validate a questionnaire for measuring social cohesion with Rasch analysis. We develop a set of 13 questions to measure 4 dimensions of social cohesion. Random samples of 166 Bandung citizens’ were selected to answer the questionnaire. To evaluate the questionnaire’s validity and reliability, Rasch analysis (a psychometric model for analyzing categorical data on questionnaire responses) was carried out using Winsteps version 3.75.0. Rasch analysis was performed on the response given to 13 items included in the questionnaire. The reliability coefficient, Cronbach’s alpha was 0.70, model RMSE 0.08, SD 0.54, separation 7.14, and reliability of 0.98. ‘Kohesif-Ques’ is a useful instrument to assess social cohesion.

Keywords: rasch analysis, rasch model, social cohesion, quesionnaire

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Authors: Taisiia Gorshkova

Abstract:

Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

Procedia PDF Downloads 141

Authors: Y. J. Wang, C. Q. Ru

Abstract:

A key issue of cohesive zone models is how to determine the cohesive zone model (CZM) parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model: the maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is simulated by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.

Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral

Procedia PDF Downloads 513

Authors: Inje Cho

Abstract:

The leading health risks threatening the world today are associated with a modern lifestyle characterized by sedentary behavior, stress, anxiety, and an obesogenic food environment. To counter this alarming trend, the Centers for Disease Control and Prevention have proffered Physical Activity guidelines to bolster physical engagement. Concurrently, the burgeon of smartphones and mobile applications has witnessed a proliferation of fitness applications aimed at invigorating exercise adherence and real-time activity monitoring. Grounded in the Uses and gratification theory, this study delves into the technological affordances of mobile fitness applications, discerning the mediating influences of escapism and social outcome expectations on attitudes and exercise intention. The theory explains how individuals employ distinct communication mediums to satiate their exigencies and desires. Technological affordances manifest as attributes of emerging technologies that galvanize personal engagement in physical activities. Several features of mobile fitness applications include affordances for goal setting, virtual rewards, peer support, and exercise information. Escapism, denoting the inclination to disengage from normal routines, has emerged as a salient motivator for the consumption of new media. This study postulates that individual’s perceptions technological affordances within mobile fitness applications, can affect escapism and social outcome expectations, potentially influencing attitude, and behavior formation. Thus, the integrated model has been developed to empirically examine the interrelationships between technological affordances, escapism, social outcome expectations, and exercise intention. Structural Equation Modelling serves as the methodological tool, and a cohort of 400 Fitbit users shall be enlisted from the Prolific, data collection platform. A sequence of multivariate data analyses will scrutinize both the measurement and hypothesized structural models. By delving into the effects of mobile fitness applications, this study contributes to the growing of new media studies in sport management. Moreover, the novel integration of the uses and gratification theory, technological affordances, via the prism of escapism, illustrates the dynamics that underlies mobile fitness user’s attitudes and behavioral intentions. Therefore, the findings from this study contribute to theoretical understanding and provide pragmatic insights to developers and practitioners in optimizing the impact of mobile fitness applications.

Keywords: technological affordances, uses and gratification, mobile fitness apps, escapism, physical activity

Procedia PDF Downloads 80

Authors: Mohammad Azam

Abstract:

The purpose of this study is to investigate risk and real excess portfolio returns using inflation adjusted risk-free rates, a measuring technique that focuses on the momentum augmented Fama-French six-factor model and use monthly data from 1994 to 2022. With the exception of profitability, the data show that market, size, value, momentum, and investment factors are all strongly associated to excess portfolio stock returns using ordinary lease square regression technique. According to the Gibbons, Ross, and Shanken test, the momentum augmented Fama-French six-factor model outperforms the market. This technique discovery may be utilised by academics and professionals to acquire an in-depth knowledge of the Pakistan Stock Exchange across a broad stock pattern for investing decisions and portfolio construction.

Keywords: real excess portfolio returns, momentum augmented fama & french five-factor model, GRS-test, pakistan stock exchange

Procedia PDF Downloads 102

Authors: Aisulu Tileukulova, Zhexebay Dauren

Abstract:

Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 353