Search results for: computational%20biomechanics

Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

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Authors: Choonsik Lee, Les Folio

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Pregnant patients may undergo CT in emergencies unrelated with pregnancy, and potential risk to the developing fetus is of concern. It is critical to accurately estimate fetal organ doses in CT scans. We developed a fetal organ dose calculation tool using pregnancy-specific computational phantoms combined with Monte Carlo radiation transport techniques. We adopted a series of pregnancy computational phantoms developed at the University of Florida at the gestational ages of 8, 10, 15, 20, 25, 30, 35, and 38 weeks (Maynard et al. 2011). More than 30 organs and tissues and 20 skeletal sites are defined in each fetus model. We calculated fetal organ dose-normalized by CTDIvol to derive organ dose conversion coefficients (mGy/mGy) for the eight fetuses for consequential slice locations ranging from the top to the bottom of the pregnancy phantoms with 1 cm slice thickness. Organ dose from helical scans was approximated by the summation of doses from multiple axial slices included in the given scan range of interest. We then compared dose conversion coefficients for major fetal organs in the abdominal-pelvis CT scan of pregnancy phantoms with the uterine dose of a non-pregnant adult female computational phantom. A comprehensive library of organ conversion coefficients was established for the eight developing fetuses undergoing CT. They were implemented into an in-house graphical user interface-based computer program for convenient estimation of fetal organ doses by inputting CT technical parameters as well as the age of the fetus. We found that the esophagus received the least dose, whereas the kidneys received the greatest dose in all fetuses in AP scans of the pregnancy phantoms. We also found that when the uterine dose of a non-pregnant adult female phantom is used as a surrogate for fetal organ doses, root-mean-square-error ranged from 0.08 mGy (8 weeks) to 0.38 mGy (38 weeks). The uterine dose was up to 1.7-fold greater than the esophagus dose of the 38-week fetus model. The calculation tool should be useful in cases requiring fetal organ dose in emergency CT scans as well as patient dose monitoring.

Keywords: computed tomography, fetal dose, pregnant women, radiation dose

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), modeling, multi-phase, transport phenomena, lithium-air battery

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: Yousef Almutairi, Yajue Wu

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Various large-scale trends have characterized the current century thus far, including increasing shifts towards urbanization and greater movement. It is predicted that there will be 9.3 billion people on Earth in 2050 and that over two-thirds of this population will be city dwellers. Moreover, in larger cities worldwide, mass transportation systems, including underground systems, have grown to account for the majority of travel in those settings. Underground networks are vulnerable to fires, however, endangering travellers’ safety, with various examples of fire outbreaks in this setting. This study aims to increase knowledge of the impacts of extreme climatic conditions on fires, including the role of the high ambient temperatures experienced in Middle Eastern countries and specifically in Saudi Arabia. This is an element that is not always included when assessments of fire safety are made (considering visibility, temperatures, and flows of smoke). This paper focuses on a tunnel within Riyadh’s underground system as a case study and includes simulations based on computational fluid dynamics using ANSYS Fluent, which investigates the impact of various ventilation systems while identifying smoke density, speed, pressure and temperatures within this tunnel.

Keywords: fire, subway tunnel, CFD, mechanical ventilation, smoke, temperature, harsh weather

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Authors: Shankaran Sitarama

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Teamwork is an extremely effective pedagogical tool in engineering education. New Product Development (NPD) has been an effective strategy of companies to streamline and bring innovative products and solutions to customers. Thus, Engineering curriculum in many schools, some collaboratively with business schools, have brought NPD into the curriculum at the graduate level. Teamwork is invariably used during instruction, where students work in teams to come up with new products and solutions. There is a significant emphasis of grade on the semester long teamwork for it to be taken seriously by students. As the students work in teams and go through this process to develop the new product prototypes, their effectiveness and learning to a great extent depends on how they function as a team and go through the creative process, come together, and work towards the common goal. A core attribute of a successful NPD team is their creativity and innovation. The team needs to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas resulting in a POC (proof-of-concept) implementation or a prototype of the product. The simultaneous requirement of teams to be creative and at the same time also converge and work together imposes different types of tensions in their team interactions. These ideational tensions / conflicts and sometimes relational tensions / conflicts are inevitable. Effective teams will have to deal with the Team dynamics and manage it to be resilient enough and yet be creative. This research paper provides a computational analysis of the teams’ communication that is reflective of the team dynamics, and through a superimposition of latent semantic analysis with social network analysis, provides a computational methodology of arriving at patterns of visual interaction. These team interaction patterns have clear correlations to the team dynamics and provide insights into the functioning and thus the effectiveness of the teams. 23 student NPD teams over 2 years of a course on Managing NPD that has a blend of engineering and business school students is considered, and the results are presented. It is also correlated with the teams’ detailed and tailored individual and group feedback and self-reflection and evaluation questionnaire.

Keywords: team dynamics, social network analysis, team interaction patterns, new product development teamwork, NPD teams

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Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

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Authors: M. Beusink, E. W. C. Coenen

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The increased application of novel structural materials, such as high grade asphalt, concrete and laminated composites, has sparked the need for a better understanding of the often complex, non-linear mechanical behavior of such materials. The effective macroscopic mechanical response is generally dependent on the applied load path. Moreover, it is also significantly influenced by the microstructure of the material, e.g. embedded fibers, voids and/or grain morphology. At present, multiscale techniques are widely adopted to assess micro-macro interactions in a numerically efficient way. Computational homogenization techniques have been successfully applied over a wide range of engineering cases, e.g. cases involving first order and second order continua, thin shells and cohesive zone models. Most of these homogenization methods rely on Representative Volume Elements (RVE), which model the relevant microstructural details in a confined volume. Imposed through kinematical constraints or boundary conditions, a RVE can be subjected to a microscopic load sequence. This provides the RVE's effective stress-strain response, which can serve as constitutive input for macroscale analyses. Simultaneously, such a study of a RVE gives insight into fine scale phenomena such as microstructural damage and its evolution. It has been reported by several authors that the type of boundary conditions applied to the RVE affect the resulting homogenized stress-strain response. As a consequence, dedicated boundary conditions have been proposed to appropriately deal with this concern. For the specific case of a planar assumption for the analyzed structure, e.g. plane strain, axisymmetric or plane stress, this assumption needs to be addressed consistently in all considered scales. Although in many multiscale studies a planar condition has been employed, the related impact on the multiscale solution has not been explicitly investigated. This work therefore focuses on the influence of the planar assumption for multiscale modeling. In particular the plane stress case is highlighted, by proposing three different implementation strategies which are compatible with a first-order computational homogenization framework. The first method consists of applying classical plane stress theory at the microscale, whereas with the second method a generalized plane stress condition is assumed at the RVE level. For the third method, the plane stress condition is applied at the macroscale by requiring that the resulting macroscopic out-of-plane forces are equal to zero. These strategies are assessed through a numerical study of a thin walled structure and the resulting effective macroscale stress-strain response is compared. It is shown that there is a clear influence of the length scale at which the planar condition is applied.

Keywords: first-order computational homogenization, planar analysis, multiscale, microstrucutures

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Authors: Tytus Tulwin, Rafal Sochaczewski, Ksenia Siadkowska

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Designing a new engine requires a large number of different cases to be considered. Especially different injector parameters and combustion chamber geometries. This is essential when developing an engine with unconventional build – compression ignition, two-stroke operating with direct side injection. Computational Fluid Dynamics modelling allows to test those different conditions and seek for the best conditions with correct combustion. This research presents the combustion results for different injector and combustion chamber cases. The shape of combustion chamber is different than for conventional engines as it requires side injection. This completely changes the optimal shape for the given condition compared to standard automotive heart shaped combustion chamber. Because the injection is not symmetrical there is a strong influence of cylinder swirl and piston motion on the injected fuel stream. The results present the fuel injection phenomena allowing to predict the right injection parameters for a maximum combustion efficiency and minimum piston heat loads. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: CFD, combustion, injection, opposed piston

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Authors: Lauren B. Birney

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The envisioned long-term outcome of this three-year research, and implementation plan is for 1) teachers and students to design and build their own computational models of real-world environmental-human health phenomena occurring within the context of the “Human Harbor” and 2) project researchers to evaluate the degree to which these integrated Computer Science (CS) education experiences in New York City (NYC) public school classrooms (PreK-12) impact students’ computational-technical skill development, job readiness, career motivations, and measurable abilities to understand, articulate, and solve the underlying phenomena at the center of their models. This effort builds on the partnership’s successes over the past eight years in developing a benchmark Model of restoration-based Science, Technology, Engineering, and Math (STEM) education for urban public schools and achieving relatively broad-based implementation in the nation’s largest public school system. The Billion Oyster Project Curriculum and Community Enterprise for Restoration Science (BOP-CCERS STEM + Computing) curriculum, teacher professional developments, and community engagement programs have reached more than 200 educators and 11,000 students at 124 schools, with 84 waterfront locations and Out of School of Time (OST) programs. The BOP-CCERS Partnership is poised to develop a more refined focus on integrating computer science across the STEM domains; teaching industry-aligned computational methods and tools; and explicitly preparing students from the city’s most under-resourced and underrepresented communities for upwardly mobile careers in NYC’s ever-expanding “digital economy,” in which jobs require computational thinking and an increasing percentage require discreet computer science technical skills. Project Objectives include the following: 1. Computational Thinking (CT) Integration: Integrate computational thinking core practices across existing middle/high school BOP-CCERS STEM curriculum as a means of scaffolding toward long term computer science and computational modeling outcomes. 2. Data Science and Data Analytics: Enabling Researchers to perform interviews with Teachers, students, community members, partners, stakeholders, and Science, Technology, Engineering, and Mathematics (STEM) industry Professionals. Collaborative analysis and data collection were also performed. As a centerpiece, the BOP-CCERS partnership will expand to include a dedicated computer science education partner. New York City Department of Education (NYCDOE), Computer Science for All (CS4ALL) NYC will serve as the dedicated Computer Science (CS) lead, advising the consortium on integration and curriculum development, working in tandem. The BOP-CCERS Model™ also validates that with appropriate application of technical infrastructure, intensive teacher professional developments, and curricular scaffolding, socially connected science learning can be mainstreamed in the nation’s largest urban public school system. This is evidenced and substantiated in the initial phases of BOP-CCERS™. The BOP-CCERS™ student curriculum and teacher professional development have been implemented in approximately 24% of NYC public middle schools, reaching more than 250 educators and 11,000 students directly. BOP-CCERS™ is a fully scalable and transferable educational model, adaptable to all American school districts. In all settings of the proposed Phase IV initiative, the primary beneficiary group will be underrepresented NYC public school students who live in high-poverty neighborhoods and are traditionally underrepresented in the STEM fields, including African Americans, Latinos, English language learners, and children from economically disadvantaged households. In particular, BOP-CCERS Phase IV will explicitly prepare underrepresented students for skilled positions within New York City’s expanding digital economy, computer science, computational information systems, and innovative technology sectors.

Keywords: computer science, data science, equity, diversity and inclusion, STEM education

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Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Diandra Cristache

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The transition of traditional manuscript studies into the digital framework closely affects the methodological premises upon which manuscript descriptions are modeled, created, and questioned for the purpose of research. This paper intends to explore the issue by presenting a methodological investigation into the process of modeling, creating, and questioning manuscript metadata. The investigation is founded on a close observation of the Polonsky Greek Manuscripts Project, a collaboration between the Universities of Cambridge and Heidelberg. More than just providing a realistic ground for methodological exploration, along with a complete metadata set for computational demonstration, the case study also contributes to a broader purpose: outlining general methodological principles for making the most out of manuscript metadata by means of research-oriented digital outputs. The analysis mainly focuses on the scholarly approach to manuscript descriptions, in the specific instance where the act of metadata recording does not have a programmatic research purpose. Close attention is paid to the encounter of 'traditional' practices in manuscript studies with the formal constraints of the digital framework: does the shift in practices (especially from the straight narrative of free writing towards the hierarchical constraints of the TEI encoding model) impact the structure of metadata and its capability to respond specific research questions? It is argued that flexible structure of TEI and traditional approaches to manuscript description lead to a proliferation of markup: does an 'encyclopedic' descriptive approach ensure the epistemological relevance of the digital outputs to metadata? To provide further insight on the computational approach to manuscript metadata, the metadata of the Polonsky project are processed with techniques of distant reading and data networking, thus resulting in a new group of digital outputs (relational graphs, geographic maps). The computational process and the digital outputs are thoroughly illustrated and discussed. Eventually, a retrospective analysis evaluates how the digital outputs respond to the scientific expectations of research, and the other way round, how the requirements of research questions feed back into the creation and enrichment of metadata in an iterative loop.

Keywords: digital manuscript studies, digital outputs to manuscripts metadata, metadata interoperability, methodological issues

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Authors: Khizir Mohd Ismail, Yu Jun Lim, Tshun Howe Yong

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The study of flow behavior in an enclosed volume using Computational Fluid Dynamics (CFD) has been around for decades. However, due to the knowledge limitation of adaptive grid methods, the flow in an enclosed volume near the moving wall using CFD is less explored. A CFD simulation of flow in an enclosed volume near a moving wall was demonstrated and studied by introducing a moving mesh method and was modeled with Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach. A static enclosed volume with controlled opening size in the bottom was positioned against a moving, translational wall with sliding mesh features. Controlled variables such as smoothed, crevices and corrugated wall characteristics, the distance between the enclosed volume to the wall and the moving wall speed against the enclosed chamber were varied to understand how the flow behaves and reacts in between these two geometries. These model simulations were validated against experimental results and provided result confidence when the simulation had shown good agreement with the experimental data. This study had provided better insight into the flow behaving in an enclosed volume when various wall types in motion were introduced within the various distance between each other and create a potential opportunity of application which involves adaptive grid methods in CFD.

Keywords: moving wall, adaptive grid methods, CFD, moving mesh method

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Authors: Muhanad Al-Jubouri

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A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

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Authors: Cesar Augusto Hoil Rosas, José Luis Vázquez Burgos, José Juan Carbajal Hernandez

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White fish (Chirostoma estor estor) is an endemic species that habits in the Patzcuaro Lake, located in Michoacan, Mexico; being an important source of gastronomic and cultural wealth of the area. Actually, it have undergone an immense depopulation of individuals, due to the high fishing, contamination and eutrophication of the lake water, resulting in the possible extinction of this important species. This work proposes a new computational model for monitoring and assessment of critical environmental parameters of the white fish ecosystem. According to an Analytical Hierarchy Process, a mathematical model is built assigning weights to each environmental parameter depending on their water quality importance on the ecosystem. Then, a development of an advanced system for the monitoring, analysis and control of water quality is built using the virtual environment of LabVIEW. As results, we have obtained a global score that indicates the condition level of the water quality in the Chirostoma estor ecosystem (excellent, good, regular and poor), allowing to provide an effective decision making about the environmental parameters that affect the proper culture of the white fish such as temperature, pH and dissolved oxygen. In situ evaluations show regular conditions for a success reproduction and growth rates of this species where the water quality tends to have regular levels. This system emerges as a suitable tool for the water management, where future laws for white fish fishery regulations will result in the reduction of the mortality rate in the early stages of development of the species, which represent the most critical phase. This can guarantees better population sizes than those currently obtained in the aquiculture crop. The main benefit will be seen as a contribution to maintain the cultural and gastronomic wealth of the area and for its inhabitants, since white fish is an important food and economical income of the region, but the species is endangered.

Keywords: Chirostoma estor estor, computational system, lab view, white fish

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Authors: Maged Assem Soliman Mossallam

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The conversion of solar thruster model to an upper stage hydrogen rocket is considered. Solar thruster categorization limits its capabilities to low and moderate thrust system with high specific impulse. The current study proposes a different concept for such systems by increasing the thrust which enables using as an upper stage rocket and for future launching purposes. A computational model for the thruster is discussed for solar thruster subsystems. The first module depends on ray tracing technique to determine the intercepted solar power by the hydrogen combustion chamber. The cavity receiver is modeled using finite volume technique. The final module imports the heated hydrogen properties to the nozzle using quasi one dimensional simulation. The probability of shock waves formulation inside the nozzle is almost diminished as the outlet pressure in space environment tends to zero. The computational model relates the high thrust hydrogen rocket conversion to the design parameters and operating conditions of the thruster. Three different designs for solar thruster systems are discussed. The first design is a low thrust high specific impulse design that produces about 10 Newton of thrust .The second one output thrust is about 250 Newton and the third design produces about 1000 Newton.

Keywords: space propulsion, hydrogen rocket, thrust, specific impulse

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Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

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Authors: Maritz Lourens Van Rensburg, Chantel Niebuhr

Abstract:

Utilizing all available renewable energy sources is an ever-growing necessity, this includes a newfound interest into hydrokinetic energy systems, which open the door to installations where conventional hydropower shows no potential. Optimization and obtaining high efficiencies are key in these installations. In this study a vertical axis Darrieus hydrokinetic turbine is designed and constructed to address certain drawbacks experience by axial flow horizontal axis turbines in an irrigation channel. Many horizontal axis turbines have been well developed and optimized to have high efficiencies but depending on the conditions experienced in an open channel, the performance of these turbines may be adversely affected. The study analyses how the designed vertical axis turbine addresses the problems experienced by a horizontal axis turbine while still achieving a satisfactory efficiency. To be able to optimize the vertical axis turbine, a computational fluid dynamics model was validated to the experimental results obtained from the power generated from a test turbine installation operating at various rotational speeds. It was found that an accurate validated model can be obtained through validation of generated power output.

Keywords: hydrokinetic, Darrieus, computational fluid dynamics, vertical axis turbine

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Authors: Harminder Kaur, Manpreet Kaur, Akanksha Kapila, Reenu

Abstract:

Schiff base with general formula H₂L was derived from condensation of o-vanillin and 3-nitro-o-phenylenediamine. This Schiff base was used for the synthesis of organotin(IV) complexes with general formula R₂SnL [R=Phenyl or n-octyl] using equimolar quantities. Elemental analysis UV-Vis, FTIR, and multinuclear spectroscopic techniques (¹H, ¹³C, and ¹¹⁹Sn) NMR were carried out for the characterization of the synthesized complexes. These complexes were coloured and soluble in polar solvents. Computational studies have been performed to obtain the details of the geometry and electronic structures of ligand as well as complexes. Geometry of the ligands and complexes have been optimized at the level of Density Functional Theory with B3LYP/6-311G (d,p) and B3LYP/MPW1PW91 respectively followed by vibrational frequency analysis using Gaussian 09. Observed ¹¹⁹Sn NMR chemical shifts of one of the synthesized complexes showed tetrahedral geometry around Tin atom which is also confirmed by DFT. HOMO-LUMO energy distribution was calculated. FTIR, ¹HNMR and ¹³CNMR spectra were also obtained theoretically using DFT. Further IRC calculations were employed to determine the transition state for the reaction and to get the theoretical information about the reaction pathway. Moreover, molecular docking studies can be explored to ensure the anticancer activity of the newly synthesized organotin(IV) complexes.

Keywords: DFT, molecular docking, organotin(IV) complexes, o-vanillin, 3-nitro-o-phenylenediamine

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Authors: Jay Ananth

Abstract:

The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

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Authors: N. Balamurugan, N. V. Mahalakshmi

Abstract:

Compression ignition (CI) engines are known for their high thermal efficiency in comparison with spark-ignited (SI) engines. This makes CI engines a potential candidate for the future prime source of power for transportation sector to reduce greenhouse gas emissions and to shrink carbon footprint. However, CI engines produce high levels of NOx and soot emissions. Conventional methods to reduce NOx and soot emissions often result in the infamous NOx-soot trade-off. The injection parameters are one of the most important factors in the working of CI engines. The engine performance, power output, economy etc., is greatly dependent on the effectiveness of the injection parameters. The injection parameter has their direct impact on combustion process and pollutant formation. The injection parameter’s values are required to be optimised according to the application of the engine. Control of fuel injection mode is one method for reduction of NOx and soot emissions that is achievable. This study aims to assess, compare and analyse the influence of the effect of injection characteristics that is SOI timing studied on combustion and emissions in in-cylinder combustion processes with that of conventional DI Diesel Engine system using the commercial Computational Fluid Dynamic (CFD) package STAR- CD ES-ICE.

Keywords: variation of injection timing, compression ignition engine, spark-ignited, Computational Fluid Dynamic

Procedia PDF Downloads 264

Authors: K. Jagannath, Akhilesh Kotian, S. S. Sharma, Achutha Kini U., P. R. Prabhu

Abstract:

Boiling process is characterized by the rapid formation of vapour bubbles at the solid–liquid interface (nucleate boiling) with pre-existing vapour or gas pockets. Computational fluid dynamics (CFD) is an important tool to study bubble dynamics. In the present study, CFD simulation has been carried out to determine the bubble detachment diameter and its terminal velocity. Volume of fluid method is used to model the bubble and the surrounding by solving single set of momentum equations and tracking the volume fraction of each of the fluids throughout the domain. In the simulation, bubble is generated by allowing water-vapour to enter a cylinder filled with liquid water through an inlet at the bottom. After the bubble is fully formed, the bubble detaches from the surface and rises up during which the bubble accelerates due to the net balance between buoyancy force and viscous drag. Finally when these forces exactly balance each other, it attains a constant terminal velocity. The bubble detachment diameter and the terminal velocity of the bubble are captured by the monitor function provided in FLUENT. The detachment diameter and the terminal velocity obtained is compared with the established results based on the shape of the bubble. A good agreement is obtained between the results obtained from simulation and the equations in comparison with the established results.

Keywords: bubble growth, computational fluid dynamics, detachment diameter, terminal velocity

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Authors: Ramiro Gustavo Ramirez Camacho, Waldir De Oliveira, Eraldo Cruz Dos Santos, Edna Raimunda Da Silva, Tania Marie Arispe Angulo, Carlos Eduardo Alves Da Costa, Tânia Cristina Alves Dos Reis

Abstract:

It presents a preliminary design methodology of an axial fan based on the lift wing theory and the potential vortex hypothesis. The literature considers a study of acoustic and engineering expertise to model a fan with low noise. Axial fans with inadequate intake geometry, often suffer poor condition of the flow at the entrance, varying from velocity profiles spatially asymmetric to swirl floating with respect to time, this produces random forces acting on the blades. This produces broadband gust noise which in most cases triggers the tonal noise. The analysis of the axial flow fan will be conducted for the solution of the Navier-Stokes equations and models of turbulence in steady and transitory (RANS - URANS) 3-D, in order to find an efficient aerodynamic design, with low noise and suitable for industrial installation. Therefore, the process will require the use of computational optimization methods, aerodynamic design methodologies, and numerical methods as CFD- Computational Fluid Dynamics. The objective is the development of the methodology of the construction axial fan, provide of design the geometry of the blade, and evaluate aerodynamic performance

Keywords: Axial fan design, CFD, Preliminary Design, Optimization

Procedia PDF Downloads 354

Authors: Geetanjali Yadav, Arpit Mishra, Parthsarathi Ghosh, Ramkrishna Sen

Abstract:

The world is facing problems of increasing global CO2 emissions, climate change and fuel crisis. Therefore, several renewable and sustainable energy alternatives should be investigated to replace non-renewable fuels in future. Algae presents itself a versatile feedstock for the production of variety of fuels (biodiesel, bioethanol, bio-hydrogen etc.) and high value compounds for food, fodder, cosmetics and pharmaceuticals. Microalgae are simple microorganisms that require water, light, CO2 and nutrients for growth by the process of photosynthesis and can grow in extreme environments, utilize waste gas (flue gas) and waste waters. Mixing, however, is a crucial parameter within the culture system for the uniform distribution of light, nutrients and gaseous exchange in addition to preventing settling/sedimentation, creation of dark zones etc. The overarching goal of the present study is to improve photobioreactor (PBR) design for enhancing dissolution of CO2 from ambient air (0.039%, v/v), pure CO2 and coal-fired flue gas (10 ± 2%) into microalgal PBRs. Computational fluid dynamics (CFD), a state-of-the-art technique has been used to solve partial differential equations with turbulence closure which represents the dynamics of fluid in a photobioreactor. In this paper, the hydrodynamic performance of the PBR has been characterized and compared with that of the conventional bubble column PBR using CFD. Parameters such as flow rate (Q), mean velocity (u), mean turbulent kinetic energy (TKE) were characterized for each experiment that was tested across different aeration schemes. The results showed that the modified PBR design had superior liquid circulation properties and gas-liquid transfer that resulted in creation of uniform environment inside PBR as compared to conventional bubble column PBR. The CFD technique has shown to be promising to successfully design and paves path for a future research in order to develop PBRs which can be commercially available for scale-up microalgal production.

Keywords: computational fluid dynamics, microalgae, bubble column photbioreactor, flue gas, simulation

Procedia PDF Downloads 207

Authors: Nurul Bin Ibrahim

Abstract:

Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

Procedia PDF Downloads 41