Search results for: cloud interface

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

Procedia PDF Downloads 58

Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

Procedia PDF Downloads 408

Authors: Shiva Subhedar, Abhishek Jain, Shivin Mittal

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Icons are not merely decorative elements in enterprise applications but very often used because of their many advantages such as compactness, visual appeal, etc. Despite these potential advantages, icons often cause usability problems when they are designed without consideration for their many potential downsides. The aim of the current study was to examine the effect of articulatory distance – the distance between the physical appearance of an interface element and what it actually means. In other words, will the subject find the association of the function and its appearance on the interface natural or is the icon difficult for them to associate with its function. We have calculated response time and quality of identification by varying icon concreteness, the context of usage and subject experience in the enterprise context. The subjects were asked to associate icons (prepared for study purpose) with given function options in context and out of context mode. Response time and their selection were recorded for analysis.

Keywords: HCI, icons, icon concreteness, icon recognition

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

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Authors: Mojtaba Valinejadshoubi, Azin Shakibabarough, Ashutosh Bagchi

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Facilities such as residential buildings, office buildings, and hospitals house large density of occupants. Therefore, a low-cost facility management program (FMP) should be used to provide a satisfactory built environment for these occupants. Facility management (FM) has been recently used in building projects as a critical task. It has been effective in reducing operation and maintenance cost of these facilities. Issues of information integration and visualization capabilities are critical for reducing the complexity and cost of FM. Building information modeling (BIM) can be used as a strong visual modeling tool and database in FM. The main objective of this study is to examine the applicability of BIM in the FM process during a building’s operational phase. For this purpose, a seven-storey office building is modeled Autodesk Revit software. Authors integrated the cloud-based environment using a visual programming tool, Dynamo, for the purpose of having a real-time cloud-based communication between the facility managers and the participants involved in the project. An appropriate and effective integrated data source and visual model such as BIM can reduce a building’s operational and maintenance costs by managing the building life cycle properly.

Keywords: building information modeling, facility management, operational phase, building life cycle

Procedia PDF Downloads 155

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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Authors: Anita Padmanabhanunni, Labeeqah Jaffer

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Menstruation signifies the transition to biological sexual maturity and culture-bound values influence its meaning and experience for women. In South Africa there is a paucity of research specific to the topic of menstruation. This study addresses this gap in the literature by exploring the experiences of menstruation among a group of women from the ama-Xhosa ethnic group, one of the largest ethnic groups in the country. Focus group and individual interviews were conducted with ama-Xhosa woman (n= 15). Data was analyzed using thematic analysis. The study found that traditional knowledge systems and cultural practices associated with menstruation including virginity testing and intonjane (female right of passage) still exist and impact on women’s subjective experiences. The study highlights the interface of tradition and modernity in the meanings ascribed to menstruation and women’s experiences of it.

Keywords: menstruation, cultural belief systems, South Africa, ama-Xhosa

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique that is capable of regularizing the shocks and sharp interfaces simultaneously in the shock-interface interaction simulations. The direct numerical simulation of flows involving shocks has been investigated for many years and a lot of numerical methods were developed to capture the shocks. However, most of these methods rely on the numerical dissipation to regularize the shocks. Moreover, in high Reynolds number flows, the nonlinear terms in hyperbolic Partial Differential Equations (PDE) dominates, constantly generating small scale features. This makes direct numerical simulation of shocks even harder. The same difficulty happens in two-phase flow with sharp interfaces where the nonlinear terms in the governing equations keep sharpening the interfaces to discontinuities. The main idea of the proposed technique is to average out the small scales that is below the resolution (observable scale) of the computational grid by filtering the convective velocity in the nonlinear terms in the governing PDE. This technique is named “observable method” and it results in a set of hyperbolic equations called observable equations, namely, observable Navier-Stokes or Euler equations. The observable method has been applied to the flow simulations involving shocks, turbulence, and two-phase flows, and the results are promising. In the current paper, the observable method is examined on the performance of regularizing shocks and interfaces at the same time in shock-interface interaction problems. Bubble-shock interactions and Richtmyer-Meshkov instability are particularly chosen to be studied. Observable Euler equations will be numerically solved with pseudo-spectral discretization in space and third order Total Variation Diminishing (TVD) Runge Kutta method in time. Results are presented and compared with existing publications. The interface acceleration and deformation and shock reflection are particularly examined.

Keywords: compressible flow simulation, inviscid regularization, Richtmyer-Meshkov instability, shock-bubble interactions.

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Authors: Pramika J. Muthya

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This paper investigates the impact of web graphics and interface design on building visitor trust in websites. A quantitative survey approach was used to examine how aesthetic and usability elements of website design influence user perceptions of trustworthiness. 133 participants aged 18-25 who live in urban Bangalore and engage in online transactions were recruited via convenience sampling. Data was collected through an online survey measuring trust levels based on website design, using validated constructs like the Visual Aesthetic of Websites Inventory (VisAWI). Statistical analysis, including ordinal regression, was conducted to analyze the results. The findings show a statistically significant relationship between web graphics and interface design and the level of trust visitors place in a website. The goodness-of-fit statistics and highly significant model fitting information provide strong evidence for rejecting the null hypothesis of no relationship. Well-designed visual aesthetics like simplicity, diversity, colorfulness, and craftsmanship are key drivers of perceived credibility. Intuitive navigation and usability also increase trust. The results emphasize the strategic importance for companies to invest in appealing graphic design, consistent with existing theoretical frameworks. There are also implications for taking a user-centric approach to web design and acknowledging the reciprocal link between pre-existing user trust and perception of visuals. While generalizable, limitations include possible sampling and self-report biases. Further research can build on these findings to deepen understanding of nuanced cultural and temporal factors influencing online trust. Overall, this study makes a significant contribution by providing empirical evidence that reinforces the crucial impact of thoughtful graphic design in fostering lasting user trust in websites.

Keywords: web graphics, interface design, visitor trust, website design, aesthetics, user experience, online trust, visual design, graphic design, user perceptions, user expectations

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Authors: Zeeshan Ahmed, Ajinkya Sarode, Pratik Basarkar, Atul Bhargav, Debjyoti Banerjee

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The use of CO₂ in oil recovery and in CO₂ capture and storage is gaining traction in recent years. These applications involve heat transfer between CO₂ and the base fluid, and hence, there arises a need to improve the thermal conductivity of CO₂ to increase the process efficiency and reduce cost. One way to improve the thermal conductivity is through nanoparticle addition in the base fluid. The nanofluid model in this study consisted of copper (Cu) nanoparticles in varying concentrations with CO₂ as a base fluid. No experimental data are available on thermal conductivity of CO₂ based nanofluid. Molecular dynamics (MD) simulations are an increasingly adopted tool to perform preliminary assessments of nanoparticle (NP) fluid interactions. In this study, the effect of the formation of a nanolayer (or molecular layering) at the gas-solid interface on thermal conductivity is investigated using equilibrium MD simulations by varying NP diameter and keeping the volume fraction (1.413%) of nanofluid constant to check the diameter effect of NP on the nanolayer and thermal conductivity. A dense semi-solid fluid layer was seen to be formed at the NP-gas interface, and the thickness increases with increase in particle diameter, which also moves with the NP Brownian motion. Density distribution has been done to see the effect of nanolayer, and its thickness around the NP. These findings are extremely beneficial, especially to industries employed in oil recovery as increased thermal conductivity of CO₂ will lead to enhanced oil recovery and thermal energy storage.

Keywords: copper-CO2 nanofluid, molecular dynamics simulation, molecular interfacial layer, thermal conductivity

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: K. Sowri Babu, P. Srinath, N. Rajeswara Rao, K. Venugopal Reddy

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The effect of gamma ray irradiation on morphology and optical properties of ZnO/Mesoporous silica (MPS) nanocomposite was studied. The ZnO/MPS nanocomposite was irradiated with gamma rays of doses 30, 60, and 90 kGy and dose-rate of irradiation was 0.15 kGy/hour. Irradiated samples are characterized with FE-SEM, FT-IR, UV-vis, and Photoluminescence (PL) spectrometers. SEM pictures showed that morphology changed from spherical to flake like morphology. UV-vis analysis showed that the band gap increased with increase of gamma ray irradiation dose. This enhancement of the band gap is assigned to the depletion of oxygen vacancies with irradiation. The intensity of PL peak decreased gradually with increase of gamma ray irradiation dose. The decrease in PL intensity is attributed to the decrease of oxygen vacancies at the interface due to poor interface and improper passivation between ZnO/MPS.

Keywords: ZnO nanoparticles, nanocomposites, mesoporous silica, photoluminescence

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Authors: Monika Singh

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A carbon nanotube thin film coated on dielectric interface is employed to produce THz surface plasma wave (SPW). The carbon nanotube has its plasmon frequency in the THz range. The SPW field falls off away from the metal film both inside the dielectric as well as in free space. An amplitude modulated laser pulse normally incident, from free space on slow wave structure, exert a modulation frequency ponderomotive force on the free electrons of the CNT film and resonantly excite the THz surface plasma wave at the modulation frequency. Carbon nanotube based plasmonic nano-structure materials provides potentially more versatile approach to tightly confined surface modes in the THz range in comparison to noble metals.

Keywords: surface plasmons, surface waves, thin films, THz radiation

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Fouad Inel, Lakhdar Khochemane

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This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: the first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-IntegratedDerivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: dynamic modeling, geometric modeling, graphical user interface, open loop, parallel cable-based robots, PID/PD controllers

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 564

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 645

Authors: Zeki Oralhan, Mahmut Tokmakçı

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SSVEP based brain computer interface (BCI) systems have been preferred, because of high information transfer rate (ITR) and practical use. ITR is the parameter of BCI overall performance. For high ITR value, one of specification BCI system is that has high accuracy. In this study, we investigated to recognize SSVEP with shorter time and lower error rate. In the experiment, there were 8 flickers on light crystal display (LCD). Participants gazed to flicker which had 12 Hz frequency and 50% duty cycle ratio on the LCD during 10 seconds. During the experiment, EEG signals were acquired via EEG device. The EEG data was filtered in preprocessing session. After that Canonical Correlation Analysis (CCA), Multiset CCA (MsetCCA), phase constrained CCA (PCCA), and Multiway CCA (MwayCCA) methods were applied on data. The highest average accuracy value was reached when MsetCCA was applied.

Keywords: brain computer interface, canonical correlation analysis, human computer interaction, SSVEP

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Authors: Gui Yang Wu, Bo Wang, Xin Wang

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Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Majid Haghshenas, James Wilson, Ranganathan Kumar

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In this study, an Algebraic Coupled Level Set-Volume of Fluid (A-CLSVOF) method with capillary pressure treatment is proposed for the modeling of two-phase capillary flows. The Volume of Fluid (VOF) method is utilized to incorporate one-way coupling with the Level Set (LS) function in order to further improve the accuracy of the interface curvature calculation and resulting surface tension force. The capillary pressure is determined and treated independently of the hydrodynamic pressure in the momentum balance in order to maintain consistency between cell centered and interpolated values, resulting in a reduction in parasitic currents. In this method, both VOF and LS functions are transported where the new volume fraction determines the interface seed position used to reinitialize the LS field. The Hamilton-Godunov function is used with a second order (in space and time) discretization scheme to produce a signed distance function. The performance of the current methodology has been tested against some common test cases in order to assess the reduction in non-physical velocities and improvements in the interfacial pressure jump. The cases of a static drop, non-linear Rayleigh-Taylor instability and finally a droplets impact on a liquid pool were simulated to compare the performance of the present method to other well-known methods in the area of parasitic current reduction, interface location evolution and overall agreement with experimental results.

Keywords: two-phase flow, capillary flow, surface tension force, coupled LS with VOF

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Authors: Masoud Safdari, Jacob Fish

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Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

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Authors: Sandy J. M. Balla, Jerry J. Walker, Isaac K. Kyere

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The heat transfer coefficient at the soil–air interface is important in calculating underground cable ampacity when convection occurs. Calculating the heat transfer coefficient accurately is complex because of the temperature variations at the earth's surface. This paper presents the effect of convection heat flow across the ground surface on the rating of three single-core, 132kV, XLPE cables buried underground. The Finite element method (FEM) is a numerical analysis technique used to determine the cable rating of buried cables under installation conditions that are difficult to support when using the analytical method. This study demonstrates the use of FEM to investigate the effect of convection on the rating ofburied cables in flat formation using QuickField finite element simulation software. As a result, developing a model to simulate this type of situation necessitates important considerations such as the following boundary conditions: burial depth, soil thermal resistivity, and soil temperature, which play an important role in the simulation's accuracy and reliability. The results show that when the ground surface is taken as a convection interface, the conductor temperature rises and may exceed the maximum permissible temperature when rated current flows. This is because the ground surface acts as a convection interface between the soil and the air (fluid). This result correlates and is compared with the rating obtained using the IEC60287 analytical method, which is based on the condition that the ground surface is an isotherm.

Keywords: finite element method, convection, buried cables, steady-state rating

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Authors: Jake Tempo, Taylor Smithurst, Jen Leah, Skye Waddingham, Amanda Catlin, Richard Cetti

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Introduction: Percutaneous nephrolithotomy (PCNL) is the gold-standard procedure for removing large or complex renal stones. Many operating positions can be used, and the debate over the ideal position continues. PCNL can be a long procedure during which patients can sustain pressure injuries. These injuries are often underreported in the literature. Interface pressure mapping records the pressure loading between a surface and the patient. High pressures with prolonged loading result in ischaemia, muscle deformation, and reperfusion which can cause skin breakdown and muscular injury. We compared the peak pressure indexes of common PCNL positions to identify positions which may be at high risk of pressure injuries. We hope the data can be used to adapt high-risk positions so that the PPI can be lessened by either adapting the positions or by using adjuncts to lower PPI. Materials and Methods: We placed a 23-year-old male subject in fourteen different PCNL positions while performing interface pressure mapping. The subject was 179 cm with a weight of 63.3 kg, BMI 19.8kg/m². Results: Supine positions had a higher mean PPI (119mmHg (41-137)) compared to prone positions (64mmHg (32-89)) (p=0.046 two tailed t-test). The supine flexed position with a bolster under the flank produced the highest PPI (194mmHg), and this was at the sacrum. Peak pressure indexes >100mmHg were recorded in eight PCNL positions. Conclusion: Supine PCNL positions produce higher PPI than prone PCNL positions. Our study shows where ‘at risk’ bony prominences are for each PCNL position. Surgeons must ensure these areas are protected during prolonged operations.

Keywords: PCNL, pressure ulcer, interface pressure mapping, surgery

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Authors: Razieh Teimouri

Abstract:

Electrical modelling of Cu (In,Ga)Se₂ thin film solar cells is carried out with compositionally graded absorber and CdS buffer layer. Simulation results are compared with experimental data. Surface defect layers (SDL) are located in CdS/CIGS interface for improving open circuit voltage simulated structure through the analysis of the interface is investigated with or without this layer. When SDL removed, by optimizing the conduction band offset (CBO) position of the buffer/absorber layers with its recombination mechanisms and also shallow donor density in the CdS, the open circuit voltage increased significantly. As a result of simulation, excellent performance can be obtained when the conduction band of window layer positions higher by 0.2 eV than that of CIGS and shallow donor density in the CdS was found about 1×10¹⁸ (cm⁻³).

Keywords: CIGS solar cells, thin film, SCAPS, buffer layer, conduction band offset

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Authors: Dung Nguyen, Yu Wei, Eric Henderson

Abstract:

Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

Procedia PDF Downloads 112

Authors: Shenghong Huang, Weirong Wang, Xisheng Luo, Xinzhu Li, Xinwen Zhao

Abstract:

Understanding of material mixing induced by Richtmyer-Meshkov instability (RMI) at extreme shock compressing conditions (high energy density environment: P >> 100GPa, T >> 10000k) is of great significance in engineering and science, such as inertial confinement fusion(ICF), supersonic combustion, etc. Turbulent mixing induced by RMI is a kind of complex fluid dynamics, which is closely related with hydrodynamic conditions, thermodynamic states, material physical properties such as compressibility, strength, surface tension and viscosity, etc. as well as initial perturbation on interface. For phenomena in ordinary thermodynamic conditions (low energy density environment), many investigations have been conducted and many progresses have been reported, while for mixing in extreme thermodynamic conditions, the evolution may be very different due to ionization as well as large difference of material physical properties, which is full of scientific problems and academic interests. In this investigation, the first principle based molecular dynamic method is applied to study metal Lithium and gas Hydrogen (Li-H2) interface mixing in micro/meso scale regime at different shock compressing loading speed ranging from 3 km/s to 30 km/s. It's found that, 1) Different from low-speed shock compressing cases, in high-speed shock compresing (>9km/s) cases, a strong acceleration of metal/gas interface after strong shock compression is observed numerically, leading to a strong phase inverse and spike growing with a relative larger linear rate. And more specially, the spike growing rate is observed to be increased with shock loading speed, presenting large discrepancy with available empirical RMI models; 2) Ionization is happened in shock font zone at high-speed loading cases(>9km/s). An additional local electric field induced by the inhomogeneous diffusion of electrons and nuclei after shock font is observed to occur near the metal/gas interface, leading to a large acceleration of nuclei in this zone; 3) In conclusion, the work of additional electric field contributes to a mechanism of RMI in micro/meso scale regime at extreme shock compressing conditions, i.e., a Rayleigh-Taylor instability(RTI) is induced by additional electric field during RMI mixing process and thus a larger linear growing rate of interface spike.

Keywords: ionization, micro/meso scale, material mixing, shock

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Authors: Martin Alexander Eder, Sergei Semenov

Abstract:

Many glass-epoxy composite structures, such as large utility wind turbine rotor blades (WTBs), comprise of adhesive joints with typically thick bond lines used to connect the different components during assembly. Performance optimization of rotor blades to increase power output by simultaneously maintaining high stiffness-to-low-mass ratios entails intricate geometries in conjunction with complex anisotropic material behavior. Consequently, adhesive joints in WTBs are subject to multiaxial stress states with significant stress gradients depending on the local joint geometry. Moreover, the dynamic aero-elastic interaction of the WTB with the airflow generates non-proportional, variable amplitude stress histories in the material. Empiricism shows that a prominent failure type in WTBs is high cycle fatigue failure of adhesive bond line interfaces, which in fact over time developed into a design driver as WTB sizes increase rapidly. Structural optimization employed at an early design stage, therefore, sets high demands on computationally efficient interface fatigue models capable of predicting the critical locations prone for interface failure. The numerical stress-based interface fatigue model presented in this work uses the Drucker-Prager criterion to compute three different damage indices corresponding to the two interface shear tractions and the outward normal traction. The two-parameter Drucker-Prager model was chosen because of its ability to consider shear strength enhancement under compression and shear strength reduction under tension. The governing interface damage index is taken as the maximum of the triple. The damage indices are computed through the well-known linear Palmgren-Miner rule after separate rain flow-counting of the equivalent shear stress history and the equivalent pure normal stress history. The equivalent stress signals are obtained by self-similar scaling of the Drucker-Prager surface whose shape is defined by the uniaxial tensile strength and the shear strength such that it intersects with the stress point at every time step. This approach implicitly assumes that the damage caused by the prevailing multiaxial stress state is the same as the damage caused by an amplified equivalent uniaxial stress state in the three interface directions. The model was implemented as Python plug-in for the commercially available finite element code Abaqus for its use with solid elements. The model was used to predict the interface damage of an adhesively bonded, tapered glass-epoxy composite cantilever I-beam tested by LM Wind Power under constant amplitude compression-compression tip load in the high cycle fatigue regime. Results show that the model was able to predict the location of debonding in the adhesive interface between the webfoot and the cap. Moreover, with a set of two different constant life diagrams namely in shear and tension, it was possible to predict both the fatigue lifetime and the failure mode of the sub-component with reasonable accuracy. It can be concluded that the fidelity, robustness and computational efficiency of the proposed model make it especially suitable for rapid fatigue damage screening of large 3D finite element models subject to complex dynamic load histories.

Keywords: adhesive, fatigue, interface, multiaxial stress

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Authors: Fouad. Inel, Lakhdar. Khochemane

Abstract:

This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: The first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-Integrated Derivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: parallel cable-based robots, geometric modeling, dynamic modeling, graphical user interface, open loop, PID/PD controllers

Procedia PDF Downloads 451