Search results for: modeling and analysis

Authors: Avinoam Rabinovich

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CO₂ geological storage is a proven technology for reducing anthropogenic carbon emissions, which is paramount for achieving the ambitious net zero emissions goal. Core flooding experiments are an important step in any CO₂ storage project, allowing us to gain information on the flow of CO₂ and brine in the porous rock extracted from the reservoir. This information is important for understanding basic mechanisms related to CO₂ geological storage as well as for reservoir modeling, which is an integral part of a field project. In this work, a different method for constructing accurate models of CO₂-brine core flooding will be presented. Results for synthetic cases and real experiments will be shown and compared with numerical models to exhibit their predictive capabilities. Furthermore, the various mechanisms which impact the CO₂ distribution and trapping in the rock samples will be discussed, and examples from models and experiments will be provided. The new method entails solving an inverse problem to obtain a three-dimensional permeability distribution which, along with the relative permeability and capillary pressure functions, constitutes a model of the flow experiments. The model is more accurate when data from a number of experiments are combined to solve the inverse problem. This model can then be used to test various other injection flow rates and fluid fractions which have not been tested in experiments. The models can also be used to bridge the gap between small-scale capillary heterogeneity effects (sub-core and core scale) and large-scale (reservoir scale) effects, known as the upscaling problem.

Keywords: CO₂ geological storage, residual trapping, capillary heterogeneity, core flooding, CO₂-brine flow

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Seyed Abolhasan Naeini, Javad Shamsi Soosahab

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The use of geosynthetic reinforcement within the footing soils is a very effective and useful method to avoid the construction of costly deep foundations. This study investigated the use of geosynthetics for soil improvement based on numerical modeling using FELA software. Pressure settlement behavior and bearing capacity ratio of foundation on geogrid reinforced sand is investigated and the effect of different parameters like as number of geogrid layers and vertical distance between elements in three different relative density soil is studied. The effects of geometrical parameters of reinforcement layers were studied for determining the optimal values to reach to maximum bearing capacity. The results indicated that the optimum range of the distance ratio between the reinforcement layers was achieved at 0.5 to 0.6 and after number of geogrid layers of 4, no significant effect on increasing the bearing capacity of footing on reinforced sandy with geogrid

Keywords: geogrid, reinforced sand, FELA software, distance ratio, number of geogrid layers

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Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler

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Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.

Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids

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Authors: Minh Tu Le, Quang Huy Nguyen, Mai Lan Nguyen

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Bonding characteristics between pavement layers have an important influence on responses of pavement structures. This paper deals with analytical solution for the stresses, strains, and deflections of double-layered asphalt pavement structure. This solution is based on the homogeneous half-space of layered theory developed by Burmister (1943). The partial interaction between the layers is taken into account by considering an interface bonding behavior which is obtained by push-out shear test. Numerical applications considering three cases of bonding (unbonded, partially bonded, and fully bonded overlays) are carried out to the influence of the interface bonding on the structural behavior of asphalt pavement under static loading. Further, it was observed that numerical results indicate that the horizontal shear reaction modulus at the interface (Ks) will significantly affect pavement structure behavior.

Keywords: analytical solution, interface bonding, shear test keyword, double-layered asphalt, shear reaction modulus

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Harche Rima, Laoufi Nadia Aicha

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This work focuses on the study and modeling of the fouling phenomenon in a vertical pipe. In the first step, milk is one of the fluids obeying the phenomenon of fouling because of the denaturation of these proteins, especially lactoglobulin, which is the active element of milk, and to facilitate its use, we chose to study milk as a fouling fluid. In another step, we consider the test section of our installation as a tubular-type heat exchanger that works against the current and in a closed circuit. A simple mathematical model of Kern & Seaton, based on the kinetics of the fouling resistance, was used to evaluate the influence of the operating parameters (fluid flow velocity and exchange wall temperature) on the fouling resistance. The influence of the variation of the fouling resistance with the operating conditions on the efficiency of the heat exchanger and the importance of the dirty state exchange coefficient as an exchange quality control parameter were discussed and examined. On the other hand, an electronic scanning microscope analysis was performed on the milk deposit in order to obtain its actual image and composition, which allowed us to calculate the thickness of this deposit.

Keywords: fouling, milk, tubular heat exchanger, fouling resistance

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Authors: Sadeq Al Yaari, Fayza Alhammadi, Ayman Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Saleh Al Yami

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Background: There has been a debate in the literature over the years as to whether or not MossTalk Words program fits Arab Broca’s aphasics (BAs) due to that language differences and also the fact that the technique has not yet been used for aphasics with semantic dementia (SD aphasics). Aims: To oversimplify the above mentioned debate slightly for purposes of exposition, the purpose of the present study is to investigate the “usability” of this program as well as pictures and community as therapeutic techniques for both Arab BAs and SD aphasics. Method: The subjects of this study are two Saudi aphasics (53 and 57 years old, respectively). The former suffers from Broca’s aphasia due to a stroke, while the latter suffers from semantic dementia. Both aphasics can speak English and have used the Moss Talk Words program in addition to intensive picture-naming therapeutic sessions for two years. They were tested by one of the researchers four times (a time per six months). The families of the two subjects, in addition to their relatives and friends, played a major part in all therapeutic sessions. Conclusion: Results show that in averages across the entire therapeutic sessions, MossTalk Words program was clearly found more effective in modeling BAs’ pronunciation than that of SD aphasic. Furthermore, picture-naming intensive exercises in addition to the positive role of the community members played a major role in the progress of the two subjects’ performance.

Keywords: moss talk words, program, technique, Broca’s aphasia, semantic dementia, subjects, picture, community

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Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

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Authors: Kamran Rashid, Tashfeen M. Azhar, Asad-ur-Rahman Wahla

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Current research aims to understand the role of successful buyer-supplier relationship in achieving supply chain competitiveness in a developing country perspective. Five hypotheses are developed to test structural model. Survey data is collected from the manufacturing sector of Pakistan. Analysis is conducted using Partial Least Squares (PLS) Structural Equation Modeling (SEM) through Smart PLS version 2.0 M3. Results demonstrate positive impact of effective supplier selection, buyer-supplier engagement, and information sharing capability on success of buyer supplier relationship. This successful buyer supplier relationship drives the supply chain firm financial and market performance. Additional analyses with large sample sizes are required in other developing countries to cross validate the results. Current study provides empirical evidence of the role of successful buyer supplier relationship in achieving supply chain competitiveness.

Keywords: supply chain management, successful buyer-supplier relationship, supply chain competitiveness, developing country

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Authors: Ibrahim A. Al-Sulaihi, Khalid S. Al-Gahtani, Abdullah M. Al-Sugair, Aref A. Abadel

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Achieving environmental sustainability is one of the important issues considered in many countries’ vision. Green/Sustainable building is widely used terminology for describing a friendly environmental construction. Applying sustainable practices has a significant importance in various fields, including construction field that consumes an enormous amount of resource and causes a considerable amount of waste. The need for sustainability is increased in the regions that suffering from the limitation of natural resource and extreme weather conditions such as Saudi Arabia. Since buildings designs are getting sophisticated, the need for tools, which support decision-making for sustainability issues, is increasing, especially in the design and preconstruction stages. In this context, Building Information Modeling (BIM) can aid in performing complex building performance analyses to ensure an optimized sustainable building design. Accordingly, this paper introduces a roadmap towards developing a systematic approach for presenting the sustainability of buildings using BIM. The approach includes set of main processes including; identifying the sustainability parameters that can be used for sustainability assessment in Saudi Arabia, developing sustainability assessment method that fits the special circumstances in the Kingdom, identifying the sustainability requirements and BIM functions that can be used for satisfying these requirements, and integrating these requirements with identified functions. As a result, the sustainability-BIM approach can be developed which helps designers in assessing the sustainability and exploring different design alternatives at the early stage of the construction project.

Keywords: green buildings, sustainability, BIM, rating systems, environment, Saudi Arabia

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

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Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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Authors: Rym Ghariani, Younes Boujelbene

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In contemporary times, global technological advancements, particularly those in the realm of digital technology, have emerged as pivotal instruments for enterprises in fostering viable partnerships and forging meaningful alliances with other firms. The advent of these digital innovations is poised to revolutionize nearly every facet and operation within corporate entities. The primary objective of this study is to explore the correlation between digitization, integration of supply chains, and the financial efficacy of the agro-industrial sector in Tunisia. To accomplish this, data collection employed a questionnaire as the primary research instrument. Subsequently, the research queries were addressed, and hypotheses were examined by subjecting the gathered data to principal component analysis and linear regression modeling, facilitated by the utilization of SPSS26 software. The findings revealed that digitalization within the supply chain, along with external supply chain integration, exerted discernible impacts on the financial performance of the organization.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: Sandeep, A. Joshi, Kamal, Piu Dhibar, Parveen Kumar

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In the present work strong ground motion has been simulated using a modified semi-empirical technique (MSET), with frequency dependent radiation pattern model. Joshi et al. (2014) have modified the semi-empirical technique to incorporate the modeling of strong motion generation areas (SMGAs). A frequency dependent radiation pattern model is applied to simulate high frequency ground motion more precisely. Identified SMGAs (Kurahashi and Irikura 2012) of the 2011 Tohoku earthquake (Mw 9.0) were modeled using this modified technique. Records are simulated for both frequency dependent and constant radiation pattern function. Simulated records for both cases are compared with observed records in terms of peak ground acceleration and pseudo acceleration response spectra at different stations. Comparison of simulated and observed records in terms of root mean square error suggests that the method is capable of simulating record which matches in a wide frequency range for this earthquake and bears realistic appearance in terms of shape and strong motion parameters. The results confirm the efficacy and suitability of rupture model defined by five SMGAs for the developed modified technique.

Keywords: strong ground motion, semi-empirical, strong motion generation area, frequency dependent radiation pattern, 2011 Tohoku Earthquake

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Authors: Omar Imine, Mohammed Aounallah, Mustapha Belkadi

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Steady three-dimensional and two free surface waves generated by moving bodies are presented, the flow problem to be simulated is rich in complexity and poses many modeling challenges because of the existence of breaking waves around the ship hull, and because of the interaction of the two-phase flow with the turbulent boundary layer. The results of several simulations are reported. The first study was performed for NACA0012 of hydrofoil with different meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second simulation, a mathematically defined Wigley hull form is used to investigate the application of a commercial CFD code in prediction of the total resistance and its components from tangential and normal forces on the hull wetted surface. The computed resistance and wave profiles are used to estimate the coefficient of the total resistance for Wigley hull advancing in calm water under steady conditions. The commercial CFD software FLUENT version 12 is used for the computations in the present study. The calculated grid is established using the code computer GAMBIT 2.3.26. The shear stress k-ωSST model is used for turbulence modeling and the volume of the fluid technique is employed to simulate the free-surface motion. The second order upwind scheme is used for discretizing the convection terms in the momentum transport equations, the Modified HRICscheme for VOF discretization. The results obtained compare well with the experimental data.

Keywords: free surface flows, breaking waves, boundary layer, Wigley hull, volume of fluid

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Authors: Omid Giahi, Ebrahim Darvishi, Mahdi Akbarzadeh

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Introduction: Occupational low back pain (LBP) is one of the most prevalent work-related musculoskeletal disorders in which a lot of risk factors are involved that. The present study focuses on the relation between personal, psycho-social and occupational risk factors and LBP severity in industrial workers. Materials and Methods: This research was a case-control study which was conducted in Kurdistan province. 100 workers (Mean Age ± SD of 39.9 ± 10.45) with LBP were selected as the case group, and 100 workers (Mean Age ± SD of 37.2 ± 8.5) without LBP were assigned into the control group. All participants were selected from various industrial units, and they had similar occupational conditions. The required data including demographic information (BMI, smoking, alcohol, and family history), occupational (posture, mental workload (MWL), force, vibration and repetition), and psychosocial factors (stress, occupational satisfaction and security) of the participants were collected via consultation with occupational medicine specialists, interview, and the related questionnaires and also the NASA-TLX software and REBA worksheet. Chi-square test, logistic regression and structural equation modeling (SEM) were used to analyze the data. For analysis of data, IBM Statistics SPSS 24 and Mplus6 software have been used. Results: 114 (77%) of the individuals were male and 86 were (23%) female. Mean Career length of the Case Group and Control Group were 10.90 ± 5.92, 9.22 ± 4.24, respectively. The statistical analysis of the data revealed that there was a significant correlation between the Posture, Smoking, Stress, Satisfaction, and MWL with occupational LBP. The odds ratios (95% confidence intervals) derived from a logistic regression model were 2.7 (1.27-2.24) and 2.5 (2.26-5.17) and 3.22 (2.47-3.24) for Stress, MWL, and Posture, respectively. Also, the SEM analysis of the personal, psycho-social and occupational factors with LBP revealed that there was a significant correlation. Conclusion: All three broad categories of risk factors simultaneously increase the risk of occupational LBP in the workplace. But, the risks of Posture, Stress, and MWL have a major role in LBP severity. Therefore, prevention strategies for persons in jobs with high risks for LBP are required to decrease the risk of occupational LBP.

Keywords: industrial workers occupational, low back pain, occupational risk factors, psychosocial factors

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Authors: Sanghoon Shim, Jaehwan Jung, Sung-Ah Kim

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As the digital technology develops, studies on the TUI (Tangible User Interface) that links the physical environment utilizing the human senses with the virtual environment through the computer are actively being conducted. In addition, there has been a tremendous advance in computer design making through the use of computer-aided design techniques, which enable optimized decision-making through comparison with machine learning and parallel comparison of alternatives. However, a complex design that can respond to user requirements or performance can emerge through the intuition of the designer, but it is difficult to actualize the emerged design by the designer's ability alone. Ancillary tools such as Gaudí's Sandbag can be an instrument to reinforce and evolve emerged ideas from designers. With the advent of many commercial tools that support 3D objects, designers' intentions are easily reflected in their designs, but the degree of their reflection reflects their intentions according to the proficiency of design tools. This study embodies the environment in which the form can be implemented by the fingers of the most basic designer in the initial design phase of the complex type building design. Leapmotion is used as a sensor to recognize the hand motions of the designer, and it is converted into digital information to realize an environment that can be linked in real time in virtual reality (VR). In addition, the implemented design can be linked with Rhino™, a 3D authoring tool, and its plug-in Grasshopper™ in real time. As a result, it is possible to design sensibly using TUI, and it can serve as a tool for assisting designer intuition.

Keywords: design environment, digital modeling, hand gesture, TUI, virtual reality

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Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity

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Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

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Authors: Pui-Lai To, Chechen Liao, Ming-Chi Sung

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Work and family life are the most important areas for men and women today. Every professional is required to meet and fulfill the responsibilities of work and family roles. Although the development and popularity of communication technology bring a lot of benefits, including effective and efficient communication, may also generate conflicts between work and family life. Since mobile devices and the applications of mobile devices, such as instant messages, are ubiquitous, the boundaries of work and family roles are increasingly blurred. Professionals may be in the risk of work over-loading and work-family conflict. This study examines the impact of work stress on professionals’ life and health in the context of instant messaging application of smart phone. This study uses a web-based questionnaire to collect samples. The questionnaires are sent via virtual community sites, instant messaging applications, and e-mail. The study develops and empirically validates a work-family conflict model by integrating the pressure theory and technostress factors. The causal relationship between variables in the research model is tested. In terms of data analysis, Partial Least Square (PLS) in Structural Equation Modeling (SEM) is used for sample analysis and research model testing. The results of this study are as follows. First, both the variables of work-related stress and technological violations positively affect the work-family conflict. Second, both the variables of work-loading and technology-overloading have no effect on work-family conflict. Third, work-family conflict has negative effect on job satisfaction, family satisfaction, physical health, and mental health.

Keywords: mental health, physical health, technostress, work-family conflict, work-related stress

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Authors: Hojjat Mohammadi, Randall Divito, Gary J. E. Kramer

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Tunnelling and pipe jacking in very soft soils (fat clays), even with an Earth Pressure Balance tunnel boring machine (EPBM), can cause large ground displacements. In this study, the short-term and long-term ground and tunnel response is predicted for twin, pipe-jacked EPBM 3 meter diameter tunnels with a narrow pillar width. Initial modelling indicated complete closure of the annulus gap at the tail shield onto the centrifugally cast, glass-fiber-reinforced, polymer mortar jacking pipe (FRP). Numerical modelling was employed to simulate the excavation and support installation sequence, examine the ground response during excavation, confirm the adequacy of the pillar width and check the structural adequacy of the installed pipe. In the numerical models, Mohr-Coulomb constitutive model with the effect of unloading was adopted for the fat clays, while for the bedrock layer, the generalized Hoek-Brown was employed. The numerical models considered explicit excavation sequences and different levels of ground convergence prior to support installation. The well-studied excavation sequences made the analysis possible for this study on a very soft clay, otherwise, obtaining the convergency in the numerical analysis would be impossible. The predicted results indicate that the ground displacements around the tunnel and its effect on the pipe would be acceptable despite predictions of large zones of plastic behaviour around the tunnels and within the entire pillar between them due to excavation-induced ground movements.

Keywords: finite element modeling (FEM), pipe-jacked tunneling, very soft clay, EPBM

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

Procedia PDF Downloads 219

Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

Procedia PDF Downloads 453

Authors: Hassan Parandvar, Mehrdad Farid

Abstract:

In this paper, a finite element modeling is presented for large amplitude vibration of functionally graded material (FGM) plates subjected to combined random pressure and thermal load. The material properties of the plates are assumed to vary continuously in the thickness direction by a simple power law distribution in terms of the volume fractions of the constituents. The material properties depend on the temperature whose distribution along the thickness can be expressed explicitly. The von Karman large deflection strain displacement and extended Hamilton's principle are used to obtain the governing system of equations of motion in structural node degrees of freedom (DOF) using finite element method. Three-node triangular Mindlin plate element with shear correction factor is used. The nonlinear equations of motion in structural degrees of freedom are reduced by using modal reduction method. The reduced equations of motion are solved numerically by 4th order Runge-Kutta scheme. In this study, the random pressure is generated using Monte Carlo method. The modeling is verified and the nonlinear dynamic response of FGM plates is studied for various values of volume fraction and sound pressure level under different thermal loads. Snap-through type behavior of FGM plates is studied too.

Keywords: nonlinear vibration, finite element method, functionally graded material (FGM) plates, snap-through, random vibration, thermal effect

Procedia PDF Downloads 262