Search results for: computational error

Authors: Janneth Gonzalez, Andres Pinzon Velasco, Maria Angarita, Nicolas Mendoza

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Astrocytes play an important role in various processes in the brain, including pathological conditions such as neurodegenerative diseases. Recent studies have shown that the increase in saturated fatty acids such as palmitic acid (PA) triggers pro-inflammatory pathways in the brain. The use of synthetic neurosteroids such as tibolone has demonstrated neuro-protective mechanisms. However, there are few studies on the neuro-protective mechanisms of tibolone, especially at the systemic (omic) level. In this study, we performed the integration of multi-omic data (transcriptome and proteome) into a human astrocyte genomic scale metabolic model to study the astrocytic response during palmitate treatment. We evaluated metabolic fluxes in three scenarios (healthy, induced inflammation by PA, and tibolone treatment under PA inflammation). We also use control theory to identify those reactions that control the astrocytic system. Our results suggest that PA generates a modulation of central and secondary metabolism, showing a change in energy source use through inhibition of folate cycle and fatty acid β-oxidation and upregulation of ketone bodies formation.We found 25 metabolic switches under PA-mediated cellular regulation, 9 of which were critical only in the inflammatory scenario but not in the protective tibolone one. Within these reactions, inhibitory, total, and directional coupling profiles were key findings, playing a fundamental role in the (de)regulation in metabolic pathways that increase neurotoxicity and represent potential treatment targets. Finally, this study framework facilitates the understanding of metabolic regulation strategies, andit can be used for in silico exploring the mechanisms of astrocytic cell regulation, directing a more complex future experimental work in neurodegenerative diseases.

Keywords: astrocytes, data integration, palmitic acid, computational model, multi-omics, control theory

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Authors: Khaled Al-Badani, Andrew Norbury, Essam Elmshawet, Glynn Rotwell, Ian Jenkinson , James Ren

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Micro welding procedures are widely used for joining materials, developing duplex components or functional surfaces, through various methods such as Micro Discharge Welding or Spot Welding process, which can be found in the engineering, aerospace, automotive, biochemical, biomedical and numerous other industries. The relationship between the material properties, structure and processing is very important to improve the structural integrity and the final performance of the welded joints. This includes controlling the shape and the size of the welding nugget, state of the heat affected zone, residual stress, etc. Nowadays, modern high volume productions require the welding of much versatile shapes/sizes and material systems that are suitable for various applications. Hence, an improved understanding of the micro welding process and the digital tools, which are based on computational numerical modelling linking key welding parameters, dimensional attributes and functional performance of the weldment, would directly benefit the industry in developing products that meet current and future market demands. This paper will introduce recent work on developing an integrated experimental and numerical modelling code for micro welding techniques. This includes similar and dissimilar materials for both ferrous and non-ferrous metals, at different scales. The paper will also produce a comparative study, concerning the differences between the micro discharge welding process and the spot welding technique, in regards to the size effect of the welding zone and the changes in the material structure. Numerical modelling method for the micro welding processes and its effects on the material properties, during melting and cooling progression at different scales, will also be presented. Finally, the applications of the integrated numerical modelling and the material development for the digital manufacturing of welding, is discussed with references to typical application cases such as sensors (thermocouples), energy (heat exchanger) and automotive structures (duplex steel structures).

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

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Authors: Majid Bayatian, Mohammadreza Ashouri

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Releasing hazardous chemicals is one of the major problems for office buildings in the chemical industry and, therefore, environmental risks are inherent to these environments. The adverse health effects of the airborne concentration of benzene have been a matter of significant concern, especially in oil refineries. The chronic and acute adverse health effects caused by benzene exposure have attracted wide attention. Acute exposure to benzene through inhalation could cause headaches, dizziness, drowsiness, and irritation of the skin. Chronic exposures have reported causing aplastic anemia and leukemia at the occupational settings. Association between chronic occupational exposure to benzene and the development of aplastic anemia and leukemia were documented by several epidemiological studies. Numerous research works have investigated benzene emissions and determined benzene concentration at different locations of the refinery plant and stated considerable health risks. The high cost of industrial control measures requires justification through lifetime health risk assessment of exposed workers and the public. In the present study, a Computational Fluid Dynamics (CFD) model has been proposed to assess the exposure risk of office building around a refinery due to its release of benzene. For simulation, GAMBIT, FLUENT, and CFD Post software were used as pre-processor, processor, and post-processor, and the model was validated based on comparison with experimental results of benzene concentration and wind speed. Model validation results showed that the model is highly validated, and this model can be used for health risk assessment. The simulation and risk assessment results showed that benzene could be dispersion to an office building nearby, and the exposure risk has been unacceptable. According to the results of this study, a validated CFD model, could be very useful for decision-makers for control measures and possibly support them for emergency planning of probable accidents. Also, this model can be used to assess exposure to various types of accidents as well as other pollutants such as toluene, xylene, and ethylbenzene in different atmospheric conditions.

Keywords: health risk assessment, office building, Benzene, numerical simulation, CFD

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Authors: Alok Agrawal, Alok Satapathy

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In this paper, an attempt to determine the effective thermal conductivity (keff) of particulate filled polymer composites using finite element method (FEM) a powerful computational technique is made. A commercially available finite element package ANSYS is used for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructures of micro-sized particulate filled polymer composites with filler content ranging from 2.35 to 26.8 vol %. Based on the temperature profiles across the composite body, the keff of each composition is estimated theoretically by FEM. Composites with similar filler contents are than fabricated using compression molding technique by reinforcing micro-sized aluminium oxide (Al2O3) in polypropylene (PP) resin. Thermal conductivities of these composite samples are measured according to the ASTM standard E-1530 by using the Unitherm™ Model 2022 tester, which operates on the double guarded heat flow principle. The experimentally measured conductivity values are compared with the numerical values and also with those obtained from existing empirical models. This comparison reveals that the FEM simulated values are found to be in reasonable good agreement with the experimental data. Values obtained from the theoretical model proposed by the authors are also found to be in even closer approximation with the measured values within percolation limit. Further, this study shows that there is gradual enhancement in the conductivity of PP resin with increase in filler percentage and thereby its heat conduction capability is improved. It is noticed that with addition of 26.8 vol % of filler, the keff of composite increases to around 6.3 times that of neat PP. This study validates the proposed model for PP-Al2O3 composite system and proves that finite element analysis can be an excellent methodology for such investigations. With such improved heat conduction ability, these composites can find potential applications in micro-electronics, printed circuit boards, encapsulations etc.

Keywords: analytical modelling, effective thermal conductivity, finite element method, polymer matrix composite

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Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

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Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

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Authors: Esmaeil Abbaszadeh Molaei, Zongyan Zhou, Aibing Yu

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The applications of liquid fluidizations have been increased in many parts of industries such as particle classification, backwashing of granular filters, crystal growth, leaching and washing, and bioreactors due to high-efficient liquid–solid contact, favorable mass and heat transfer, high operation flexibilities, and reduced back mixing of phases. In most of these multiphase operations the particles properties, i.e. size, density, and shape, may change during the process because of attrition, coalescence or chemical reactions. Previous studies, either experimentally or numerically, mainly have focused on studies of liquid-solid fluidized beds containing spherical particles; however, the role of particle shape on the hydrodynamics of liquid fluidized beds is still not well-known. A three-dimensional Discrete Element Model (DEM) and Computational Fluid Dynamics (CFD) are coupled to study the influence of particles shape on particles and liquid flow patterns in liquid-solid fluidized beds. In the simulations, ellipsoid particles are used to study the shape factor since they can represent a wide range of particles shape from oblate and sphere to prolate shape particles. Different particle shapes from oblate (disk shape) to elongated particles (rod shape) are selected to investigate the effect of aspect ratio on different flow characteristics such as general particles and liquid flow pattern, pressure drop, and particles orientation. First, the model is verified based on experimental observations, then further detail analyses are made. It was found that spherical particles showed a uniform particle distribution in the bed, which resulted in uniform pressure drop along the bed height. However for particles with aspect ratios less than one (disk-shape), some particles were carried into the freeboard region, and the interface between the bed and freeboard was not easy to be determined. A few particle also intended to leave the bed. On the other hand, prolate particles showed different behaviour in the bed. They caused unstable interface and some flow channeling was observed for low liquid velocities. Because of the non-uniform particles flow pattern for particles with aspect ratios lower (oblate) and more (prolate) than one, the pressure drop distribution in the bed was not observed as uniform as what was found for spherical particles.

Keywords: CFD, DEM, ellipsoid, fluidization, multiphase flow, non-spherical, simulation

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Authors: Hamza Javar Magnier, Leslie V. Woodcock

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We report extensive molecular dynamics (MD) computational investigations into the thermodynamic description of supercritical properties for a model fluid that is the simplest realistic representation of atoms or molecules. The pair potential is a hard-sphere repulsion of diameter σ with a very short attraction of length λσ. When λ = 1.005 the range is so short that the model atoms are referred to as “adhesive spheres”. Molecular dimers, trimers …etc. up to large clusters, or droplets, of many adhesive-sphere atoms are unambiguously defined. This then defines percolation transitions at the molecular level that bound the existence of gas and liquid phases at supercritical temperatures, and which define the existence of a supercritical mesophase. Both liquid and gas phases are seen to terminate at the loci of percolation transitions, and below a second characteristic temperature (Tc2) are separated by the supercritical mesophase. An analysis of the distribution of clusters in gas, meso- and liquid phases confirms the colloidal nature of this mesophase. The general phase behaviour is compared with both experimental properties of the water-steam supercritical region and also with formally exact cluster theory of Mayer and Mayer. Both are found to be consistent with the present findings that in this system the supercritical mesophase narrows in density with increasing T > Tc and terminates at a higher Tc2 at a confluence of the primary percolation loci. The expended plot of the MD data points in the mesophase of 7 critical and supercritical isotherms in highlight this narrowing in density of the linear-slope region of the mesophase as temperature is increased above the critical. This linearity in the mesophase implies the existence of a linear combination rule between gas and liquid which is an extension of the Lever rule in the subcritical region, and can be used to obtain critical parameters without resorting to experimental data in the two-phase region. Using this combination rule, the calculated critical parameters Tc = 0.2007 and Pc = 0.0278 are found be agree with the values found by of Largo and coworkers. The properties of this supercritical mesophase are shown to be consistent with an alternative description of the phenomenon of critical opalescence seen in the supercritical region of both molecular and colloidal-protein supercritical fluids.

Keywords: critical opalescence, supercritical, square-well, percolation transition, critical parameters.

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Paolo Sassi, Jorge Freiria, Gabriel Usera

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In this work, a finite volume fluid flow solver is coupled with a discrete element method module for the simulation of the dynamics of free and elastic bodies in interaction with the fluid and between themselves. The open source fluid flow solver, caffa3d.MBRi, includes the capability to work with nested overlapping grids in order to easily refine the grid in the region where the bodies are moving. To do so, it is necessary to implement a recognition function able to identify the specific mesh block in which the device is moving in. The set of overlapping finer grids might be displaced along with the set of bodies being simulated. The interaction between the bodies and the fluid is computed through a two-way coupling. The velocity field of the fluid is first interpolated to determine the drag force on each object. After solving the objects displacements, subject to the elastic bonding among them, the force is applied back onto the fluid through a Gaussian smoothing considering the cells near the position of each object. The fishnet is represented as lumped masses connected by elastic lines. The internal forces are derived from the elasticity of these lines, and the external forces are due to drag, gravity, buoyancy and the load acting on each element of the system. When solving the ordinary differential equations system, that represents the motion of the elastic and flexible bodies, it was found that the Runge Kutta solver of fourth order is the best tool in terms of performance, but requires a finer grid than the fluid solver to make the system converge, which demands greater computing power. The coupled solver is demonstrated by simulating the interaction between the fluid, an elastic fishnet and a set of free bodies being captured by the net as they are dragged by the fluid. The deformation of the net, as well as the wake produced in the fluid stream are well captured by the method, without requiring the fluid solver mesh to adapt for the evolving geometry. Application of the same strategy to the simulation of elastic structures subject to the action of wind is also possible with the method presented, and one such application is currently under development.

Keywords: computational fluid dynamics, discrete element method, fishnets, nested overlapping grids

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Authors: Quan Wen, Tianxiao Chang, Shaolu Shi, Yushi Wang, Guangyu Wang

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As a kind of working environment of the fuze, the spin rate decaying law of projectile in exterior trajectory is of great value in the design of the rotation count fixed distance fuze. In addition, it is significant in the field of devices for simulation tests of fuze exterior ballistic environment, flight stability, and dispersion accuracy of gun projectile and opening and scattering design of submunition and illuminating cartridges. Besides, the self-destroying mechanism of the fuze in small-caliber projectile often works by utilizing the attenuation of centrifugal force. In the theory of projectile aerodynamics and fuze design, there are many formulas describing the change law of projectile angular velocity in external ballistic such as Roggla formula, exponential function formula, and power function formula. However, these formulas are mostly semi-empirical due to the poor test conditions and insufficient test data at that time. These formulas are difficult to meet the design requirements of modern fuze because they are not accurate enough and have a narrow range of applications now. In order to provide more accurate ballistic environment parameters for the design of a hemispherical head projectile fuze, the projectile’s spin rate decaying law in exterior trajectory under the effect of air resistance was studied. In the analysis, the projectile shape was simplified as hemisphere head, cylindrical part, rotating band part, and anti-truncated conical tail. The main assumptions are as follows: a) The shape and mass are symmetrical about the longitudinal axis, b) There is a smooth transition between the ball hea, c) The air flow on the outer surface is set as a flat plate flow with the same area as the expanded outer surface of the projectile, and the boundary layer is turbulent, d) The polar damping moment attributed to the wrench hole and rifling mark on the projectile is not considered, e) The groove of the rifle on the rotating band is uniform, smooth and regular. The impacts of the four parts on aerodynamic moment of the projectile rotation were obtained by aerodynamic theory. The surface friction stress of the projectile, the polar damping moment formed by the head of the projectile, the surface friction moment formed by the cylindrical part, the rotating band, and the anti-truncated conical tail were obtained by mathematical derivation. After that, the mathematical model of angular spin rate attenuation was established. In the whole trajectory with the maximum range angle (38°), the absolute error of the polar damping torque coefficient obtained by simulation and the coefficient calculated by the mathematical model established in this paper is not more than 7%. Therefore, the credibility of the mathematical model was verified. The mathematical model can be described as a first-order nonlinear differential equation, which has no analytical solution. The solution can be only gained as a numerical solution by connecting the model with projectile mass motion equations in exterior ballistics.

Keywords: ammunition engineering, fuze technology, spin rate, numerical simulation

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Authors: Kenneth A. Rostowsky, Alexander S. Maher, Nahian F. Chowdhury, Andrei Irimia

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The clinical significance of cerebral microbleeds (CMBs) due to mild traumatic brain injury (mTBI) remains unclear. Here we use magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and connectomic analysis to investigate the statistical association between mTBI-related CMBs, post-TBI changes to the human connectome and neurological/cognitive deficits. This study was undertaken in agreement with US federal law (45 CFR 46) and was approved by the Institutional Review Board (IRB) of the University of Southern California (USC). Two groups, one consisting of 26 (13 females) mTBI victims and another comprising 26 (13 females) healthy control (HC) volunteers were recruited through IRB-approved procedures. The acute Glasgow Coma Scale (GCS) score was available for each mTBI victim (mean µ = 13.2; standard deviation σ = 0.4). Each HC volunteer was assigned a GCS of 15 to indicate the absence of head trauma at the time of enrollment in our study. Volunteers in the HC and mTBI groups were matched according to their sex and age (HC: µ = 67.2 years, σ = 5.62 years; mTBI: µ = 66.8 years, σ = 5.93 years). MRI [including T1- and T2-weighted volumes, gradient recalled echo (GRE)/susceptibility weighted imaging (SWI)] and gradient echo (GE) DWI volumes were acquired using the same MRI scanner type (Trio TIM, Siemens Corp.). Skull-stripping and eddy current correction were implemented. DWI volumes were processed in TrackVis (http://trackvis.org) and 3D Slicer (http://www.slicer.org). Tensors were fit to DWI data to perform DTI, and tractography streamlines were then reconstructed using deterministic tractography. A voxel classifier was used to identify image features as CMB candidates using Microbleed Anatomic Rating Scale (MARS) guidelines. For each peri-lesional DTI streamline bundle, the null hypothesis was formulated as the statement that there was no neurological or cognitive deficit associated with between-scan differences in the mean FA of DTI streamlines within each bundle. The statistical significance of each hypothesis test was calculated at the α = 0.05 level, subject to the family-wise error rate (FWER) correction for multiple comparisons. Results: In HC volunteers, the along-track analysis failed to identify statistically significant differences in the mean FA of DTI streamline bundles. In the mTBI group, significant differences in the mean FA of peri-lesional streamline bundles were found in 21 out of 26 volunteers. In those volunteers where significant differences had been found, these differences were associated with an average of ~47% of all identified CMBs (σ = 21%). In 12 out of the 21 volunteers exhibiting significant FA changes, cognitive functions (memory acquisition and retrieval, top-down control of attention, planning, judgment, cognitive aspects of decision-making) were found to have deteriorated over the six months following injury (r = -0.32, p < 0.001). Our preliminary results suggest that acute post-TBI CMBs may be associated with cognitive decline in some mTBI patients. Future research should attempt to identify mTBI patients at high risk for cognitive sequelae.

Keywords: traumatic brain injury, magnetic resonance imaging, diffusion tensor imaging, connectomics

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Salah Belaidi

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We have carried out extensive and in-depth research to search for bioactive compounds based on Algerian plants. A selection of 50 ligands from Algerian medicinal plants. Several compounds used in herbal medicine have been drawn using Marvin Sketch software. We determined the three-dimensional structures of the ligands with the MMFF94 force field in order to prepare these ligands for molecular docking. The 3D protein structure of the SARS-CoV-2 main protease was taken from the Protein Data Bank. We used AutoDockVina software to apply molecular docking. The hydrogen atoms were added during the molecular docking process, and all the twist bonds of the ligands were added using the (ligand) module in the AutoDock software. The COVID-19 main protease (Mpro) is a key enzyme that plays a vital role in viral transcription and mediating replication, so it is a very attractive drug target for SARS-CoV-2. In this work, an evaluation was carried out on the biologically active compounds present in these selected medicinal plants as effective inhibitors of the protease enzyme of COVID-19, with an in-depth computational calculation of the molecular docking using the Autodock Vina software. The top 7 ligands: Phloroglucinol, Afzelin, Myricetin-3-O- rutinosidTricin 7-neohesperidoside, Silybin, Silychristinthat and Kaempferol are selected among the 50 molecules studied which are Algerian medicinal plants, whose selection is based on the best binding energy which is relatively low compared to the reference molecule with binding affinities of -9.3, -9.3, -9, -8.9, -8 .5, 8.3 and -8.3 kcal mol-1 respectively. Then, we analyzed the ADME properties of the best7 ligands using the web server SwissADME. Two ligands (Silybin, Silychristin) were found to be potential candidates for the discovery and design of novel drug inhibitors of the protease enzyme of SARS-CoV-2. The stability of the two ligands in complexing with the Mpro protease was validated by molecular dynamics simulation; they revealed a stable trajectory in both techniques, RMSD and RMSF, by showing molecular properties with coherent interactions in molecular dynamics simulations. Finally, we conclude that the Silybin ligand forms a more stable complex with the Mpro protease compared to the Silychristin ligand.

Keywords: COVID-19, medicinal plants, molecular docking, ADME properties, molecular dynamics

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Authors: Mohamed Moussaoui, Mouna Baassi, Soukayna Baammi, Hatim Soufi, Mohammed Salah, Rachid Daoud, Achraf EL Allali, Mohammed Elalaoui Belghiti, Said Belaaouad

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The present study aims to investigate the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the density functional theory (DFT) method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R²= 0.725, R²ₐ𝒹ⱼ= 0.653, MSE = 0.060, R²ₜₑₛₜ= 0.827, Q²𝒸ᵥ = 0.536). The energy of the highest occupied molecular orbital (EHOMO) orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Additional Thiazole derivatives were then designed and their activities and pharmacokinetic properties were predicted using the validated QSAR model. These designed molecules underwent evaluation through molecular docking (MD) and molecular dynamic (MD) simulations, with binding affinity calculated using the MMPBSA script according to a 100 ns simulation trajectory. This process aimed to study both their affinity and stability towards Cyclin-Dependent Kinase 2 (CDK2), a target protein for cancer disease treatment. The research concluded by identifying four CDK2 inhibitors - A1, A3, A5, and A6 - displaying satisfactory pharmacokinetic properties. MDs results indicated that the designed compound A5 remained stable in the active center of the CDK2 protein, suggesting its potential as an effective inhibitor for the treatment of hepatocellular carcinoma. The findings of this study could contribute significantly to the development of effective CDK2 inhibitors.

Keywords: QSAR, ADMET, Thiazole, anticancer, molecular docking, molecular dynamic simulations, MMPBSA calculation

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Authors: Yuna Lee

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In the current policy process, there has been a growing interest in more open approaches that incorporate creativity and innovation based on the forecasting groups composed by the public and experts together into scientific data-driven foresight methods to implement more effective policymaking. Especially, citizen participation as collective intelligence in policymaking with design and deep scale of innovation at the global level has been developed and human-centred design thinking is considered as one of the most promising methods for strategic foresight. Yet, there is a lack of a common theoretical foundation for a comprehensive approach for the current situation of and post-COVID-19 era, and substantial changes in policymaking practice are insignificant and ongoing with trial and error. This project hypothesized that rigorously developed policy systems and tools that support strategic foresight by considering the public understanding could maximize ways to create new possibilities for a preferable future, however, it must involve a better understating of Behavioural Insights, including individual and cultural values, profit motives and needs, and psychological motivations, for implementing holistic and multilateral foresight and creating more positive possibilities. To what extent is the policymaking system theoretically possible that incorporates the holistic and comprehensive foresight and policy process implementation, assuming that theory and practice, in reality, are different and not connected? What components and environmental conditions should be included in the strategic foresight system to enhance the capacity of decision from policymakers to predict alternative futures, or detect uncertainties of the future more accurately? And, compared to the required environmental condition, what are the environmental vulnerabilities of the current policymaking system? In this light, this research contemplates the question of how effectively policymaking practices have been implemented through the synthesis of scientific, technology-oriented innovation with the strategic design for tackling complex societal challenges and devising more significant insights to make society greener and more liveable. Here, this study conceptualizes the notions of a new collaborative way of strategic foresight that aims to maximize mutual benefits between policy actors and citizens through the cooperation stemming from evolutionary game theory. This study applies mixed methodology, including interviews of policy experts, with the case in which digital transformation and strategic design provided future-oriented solutions or directions to cities’ sustainable development goals and society-wide urgent challenges such as COVID-19. As a result, artistic and sensual interpreting capabilities through strategic design promote a concrete form of ideas toward a stable connection from the present to the future and enhance the understanding and active cooperation among decision-makers, stakeholders, and citizens. Ultimately, an improved theoretical foundation proposed in this study is expected to help strategically respond to the highly interconnected future changes of the post-COVID-19 world.

Keywords: policymaking, strategic design, sustainable innovation, evolution of cooperation

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Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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Authors: Sarath Chandran Nair S, Srinivas Kodati, Vasudevan R, Asraff A. K

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Spacecrafts generally employ liquid propulsion for their attitude and orbital maneuvers or raising it from geo-transfer orbit to geosynchronous orbit. Liquid propulsion systems use either mono-propellant or bi-propellants for generating thrust. These propellants are generally stored in either spherical tanks or cylindrical tanks with spherical end domes. The propellant tanks are provided with a propellant acquisition system/propellant management device along with vanes and their conical mounting structure to ensure propellant availability in the outlet for thrust generation even under a low/zero-gravity environment. Slosh is the free surface oscillations in partially filled containers under external disturbances. In a spacecraft, these can be due to control forces and due to varying acceleration. Knowledge of slosh and its effect due to internals is essential for understanding its stability through control stability studies. It is mathematically represented by a pendulum-mass model. It requires parameters such as slosh frequency, damping, sloshes mass and its location, etc. This paper enumerates various numerical and experimental methods used for evaluating the slosh parameters required for representing slosh. Numerical methods like finite element methods based on linear velocity potential theory and computational fluid dynamics based on Reynolds Averaged Navier Stokes equations are used for the detailed evaluation of slosh behavior in one of the spacecraft propellant tanks used in an Indian space mission. Experimental studies carried out on a scaled-down model are also discussed. Slosh parameters evaluated by different methods matched very well and finalized their dispersion bands based on experimental studies. It is observed that the presence of internals such as propellant management devices, including conical support structure, alters slosh parameters. These internals also offers one order higher damping compared to viscous/ smooth wall damping. It is an advantage factor for the stability of slosh. These slosh parameters are given for establishing slosh margins through control stability studies and finalize the spacecraft control system design.

Keywords: control stability, propellant tanks, slosh, spacecraft, slosh spacecraft

Procedia PDF Downloads 231

Authors: Subrat Partha Sarathi Pattnaik, Rajan N.K.S.

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Integrated rocket ramjet engines are highly suitable for long range missile applications. Designing the fixed geometry intakes for such missiles that can operate efficiently over a range of operating conditions is a highly challenging task. Hence, the present study aims to evaluate the effect of throat design on the performance of a rectangular mixed compression intake for operation in the Mach number range of 1.8 – 2.5. The analysis has been carried out at four different Mach numbers of 1.8, 2, 2.2, 2.5 and two angle-of-attacks of +5 and +10 degrees. For the throat design, three different throat heights have been considered, one corresponding to a 3- external shock design and two heights corresponding to a 2-external shock design leading to different internal contraction ratios. The on-design Mach number for the study is M 2.2. To obtain the viscous flow field in the intake, the theoretical designs have been considered for computational fluid dynamic analysis. For which Favre averaged Navier- Stokes (FANS) equations with two equation SST k-w model have been solved. The analysis shows that for zero angle of attack at on-design and high off-design Mach number operations the three-ramp design leads to a higher total pressure recovery (TPR) compared to the two-ramp design at both contraction ratios maintaining same mass flow ratio (MFR). But at low off-design Mach numbers the total pressure shows an opposite trend that is maximum for the two-ramp low contraction ratio design due to lower shock loss across the external shocks similarly the MFR is higher for low contraction ratio design as the external ramp shocks move closer to the cowl. At both the angle of attack conditions and complete range of Mach numbers the total pressure recovery and mass flow ratios are highest for two ramp low contraction design due to lower stagnation pressure loss across the detached bow shock formed at the ramp and lower mass spillage. Hence, low contraction design is found to be suitable for higher off-design performance.

Keywords: internal contraction ratio, mass flow ratio, mixed compression intake, performance, supersonic flows

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Authors: Arpit Kumar Shrivastava, Subrat Kumar, Rajani Kanta Mohapatra, Priyadarshi Soumyaranjan Sahu

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Computational approaches to predict structure, function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are not effective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical epitopic protein in C. hominis genome through BLASTP analysis. A 3D model of the hypothetical protein was generated using I-Tasser server through threading methodology. The quality of the model was validated through Ramachandran plot by PROCHECK server. The functional annotation of the hypothetical protein through DALI server revealed structural similarity with human Transportin 3. Phylogenetic analysis for this hypothetical protein also showed C. hominis hypothetical protein (CUV04613) was the closely related to human transportin 3 protein. The 3D protein model is further subjected to virtual screening study with inhibitors from the Zinc Database by using Dock Blaster software. Docking study reported N-(3-chlorobenzyl) ethane-1,2-diamine as the best inhibitor in terms of docking score. Docking analysis elucidated that Leu 525, Ile 526, Glu 528, Glu 529 are critical residues for ligand–receptor interactions. The molecular dynamic simulation was done to access the reliability of the binding pose of inhibitor and protein complex using GROMACS software at 10ns time point. Trajectories were analyzed at each 2.5 ns time interval, among which, H-bond with LEU-525 and GLY- 530 are significantly present in MD trajectories. Furthermore, antigenic determinants of the protein were determined with the help of DNA Star software. Our study findings showed a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for control as well as prevention of cryptosporidiosis among humans and animals.

Keywords: cryptosporidium hominis, hypothetical protein, molecular docking, molecular dynamics simulation

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Authors: Tobias Strübing, Fatemeh Ziaeetabar

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Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Tytus Tulwin

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This paper describes the geometrical model, algorithm and CFD simulation of an airflow around a Vertical Axis Wind Turbine rotor. A solver, ANSYS Fluent, was applied for the numerical simulation. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed to avoid a costly preparation of a model or a prototype for a bench test. This research focuses on the rotor designed according to patent no PL 219985 with its blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on a regulation of blade angle α between the top and bottom parts of blades mounted on an axis. If angle α increases, the working surface which absorbs wind kinetic energy also increases. CFD calculations enable us to compare aerodynamic characteristics of forces acting on rotor working surfaces and specify rotor operation parameters like torque or turbine assembly power output. This paper is part of the research to improve an efficiency of a rotor assembly and it contains investigation of the impact of a blade angle of wind turbine working blades on the power output as a function of rotor torque, specific rotational speed and wind speed. The simulation was made for wind speeds ranging from 3.4 m/s to 6.2 m/s and blade angles of 30°, 60°, 90°. The simulation enables us to create a mathematical model to describe how aerodynamic forces acting each of the blade of the studied rotor are generated. Also, the simulation results are compared with the wind tunnel ones. This investigation enables us to estimate the growth in turbine power output if a blade angle changes. The regulation of blade angle α enables a smooth change in turbine rotor power, which is a kind of safety measures if the wind is strong. Decreasing blade angle α reduces the risk of damaging or destroying a turbine that is still in operation and there is no complete rotor braking as it is in other Horizontal Axis Wind Turbines. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, mathematical model, numerical analysis, power, renewable energy, wind turbine

Procedia PDF Downloads 330

Authors: Mahtab Makaremi Masouleh, Günter Wozniak

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This research is part of an interdisciplinary project, promoting the design of a light temporary installable textile defence system against flood. In case river water levels increase abruptly especially in winter time, one can expect massive extra load on a textile protective structure in term of impact as a result of floating debris and even tree trunks. Estimation of this impulsive force on such structures is of a great importance, as it can ensure the reliability of the design in critical cases. This fact provides the motivation for the numerical analysis of a fluid structure interaction application, comprising flexible slender shaped and free-surface water flow, where an accelerated heavy flotsam tends to approach the membrane. In this context, the analysis on both the behavior of the flexible membrane and its interaction with moving flotsam is conducted by finite elements based solvers of the explicit solver and implicit Abacus solver available as products of SIMULIA software. On the other hand, a study on how free surface water flow behaves in response to moving structures, has been investigated using the finite volume solver of Star CCM+ from Siemens PLM Software. An automatic communication tool (CSE, SIMULIA Co-Simulation Engine) and the implementation of an effective partitioned strategy in form of an implicit coupling algorithm makes it possible for partitioned domains to be interconnected powerfully. The applied procedure ensures stability and convergence in the solution of these complicated issues, albeit with high computational cost; however, the other complexity of this study stems from mesh criterion in the fluid domain, where the two structures approach each other. This contribution presents the approaches for the establishment of a convergent numerical solution and compares the results with experimental findings.

Keywords: co-simulation, flexible thin structure, fluid-structure interaction, implicit coupling algorithm, moving flotsam

Procedia PDF Downloads 377

Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

Procedia PDF Downloads 206

Authors: Jennifer Cuellar, Angie L. Parada, Kevin N. S. Chacon, Sol M. Mejia

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The purification of bio-ethanol through distillation methods is an unresolved issue at the biofuel industry because of the ethanol-water azeotrope formation, which increases the steps of the purification process and subsequently increases the production costs. Therefore, understanding the mixture nature at the molecular level could provide new insights for improving the current methods and/or designing new and more efficient purification methods. For that reason, the present study focuses on the evaluation and analysis of (ethanol)₉-water heterodecamers, as the systems with the minimum molecular proportion that represents the azeotropic concentration (96 %m/m in ethanol). The computational modelling was carried out with B3LYP-D3/6-311++G(d,p) in Gaussian 09. Initial explorations of the potential energy surface were done through two methods: annealing simulated runs and molecular dynamics trajectories besides intuitive structures obtained from smaller (ethanol)n-water heteroclusters, n = 7, 8 and 9. The energetic order of the seven stable heterodecamers determines the most stable heterodecamer (Hdec-1) as a structure forming a bicyclic geometry with the O-H---O hydrogen bonds (HBs) where the water is a double proton donor molecule. Hdec-1 combines 1 water molecule and the same quantity of every ethanol conformer; this is, 3 trans, 3 gauche 1 and 3 gauche 2; its abundance is 89%, its decamerization energy is -80.4 kcal/mol, i.e. 13 kcal/mol most stable than the less stable heterodecamer. Besides, a way to understand why methanol does not form an azeotropic mixture with water, analogous systems ((ethanol)10, (methanol)10, and (methanol)9-water)) were optimized. Topologic analysis of the electron density reveals that Hec-1 forms 33 weak interactions in total: 11 O-H---O, 8 C-H---O, 2 C-H---C hydrogen bonds and 12 H---H interactions. The strength and abundance of the most unconventional interactions (H---H, C-H---O and C-H---O) seem to explain the preference of the ethanol for forming heteroclusters instead of clusters. Besides, O-H---O HBs present a significant covalent character according to topologic parameters as the Laplacian of electron density and the relationship between potential and kinetic energy densities evaluated at the bond critical points; obtaining negatives values and values between 1 and 2, for those two topological parameters, respectively.

Keywords: ADMP, DFT, ethanol-water azeotrope, Grimme dispersion correction, simulated annealing, weak interactions

Procedia PDF Downloads 96

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

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

Keywords: automated, biomechanics, team-sports, sprint

Procedia PDF Downloads 111

Authors: Asif Arshid, Ying Huang, Denver Tolliver

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Finite Element (FE) method coupled with ever-increasing computational powers has substantially advanced the reliability of deterministic three dimensional structural analyses of a structure with uniform material properties. However, railways trackbed is made up of diverse group of materials including steel, wood, rock and soil, while each material has its own varying levels of heterogeneity and imperfections. It is observed that the application of probabilistic methods for trackbed structural analysis while incorporating the material and geometric variabilities is deeply underworked. The authors developed and validated a 3-dimensional FE based numerical trackbed model and in this study, they investigated the influence of variability in Young modulus and thicknesses of granular layers (Ballast and Subgrade) on the reliability index (-index) of the subgrade layer. The influence of these factors is accounted for by changing their Coefficients of Variance (COV) while keeping their means constant. These variations are formulated using Gaussian Normal distribution. Two failure mechanisms in subgrade namely Progressive Shear Failure and Excessive Plastic Deformation are examined. Preliminary results of risk-based probabilistic analysis for Progressive Shear Failure revealed that the variations in Ballast depth are the most influential factor for vertical stress at the top of subgrade surface. Whereas, in case of Excessive Plastic Deformations in subgrade layer, the variations in its own depth and Young modulus proved to be most important while ballast properties remained almost indifferent. For both these failure moods, it is also observed that the reliability index for subgrade failure increases with the increase in COV of ballast depth and subgrade Young modulus. The findings of this work is of particular significance in studying the combined effect of construction imperfections and variations in ground conditions on the structural performance of railroad trackbed and evaluating the associated risk involved. In addition, it also provides an additional tool to supplement the deterministic analysis procedures and decision making for railroad maintenance.

Keywords: finite element analysis, numerical modeling, probabilistic methods, risk and reliability analysis, subgrade

Procedia PDF Downloads 130

Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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Authors: Miguel Nino

Abstract:

When considering the challenges of a changing and demanding globalizing world, it is important to reflect on how university students will be prepared for the realities of internationalization, marketization and intercultural conversation. The present study is an interdisciplinary program designed to respond to the needs of the global community. The proposal bridges the humanities and science through three different fields: Languages, graphic design and computer science, specifically, fundamentals of programming such as python, java script and software animation. Therefore, the goal of the four year program is twofold: First, enable students for intercultural communication between English and other languages such as Spanish, Mandarin, French or German. Second, students will acquire knowledge in practical software and relevant employable skills to collaborate in assisted computer projects that most probable will require essential programing background in interpreted or compiled languages. In order to become inclusive and constructivist, the cognitive linguistics approach is suggested for the three different fields, particularly for languages that rely on the traditional method of repetition. This methodology will help students develop their creativity and encourage them to become independent problem solving individuals, as languages enhance their common ground of interaction for culture and technology. Participants in this course of study will be evaluated in their second language acquisition at the Intermediate-High level. For graphic design and computer science students will apply their creative digital skills, as well as their critical thinking skills learned from the cognitive linguistics approach, to collaborate on a group project design to find solutions for media web design problems or marketing experimentation for a company or the community. It is understood that it will be necessary to apply programming knowledge and skills to deliver the final product. In conclusion, the program equips students with linguistics knowledge and skills to be competent in intercultural communication, where English, the lingua franca, remains the medium for marketing and product delivery. In addition to their employability, students can expand their knowledge and skills in digital humanities, computational linguistics, or increase their portfolio in advertising and marketing. These students will be the global human capital for the competitive globalizing community.

Keywords: curriculum, international, languages, technology

Procedia PDF Downloads 435

Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

Procedia PDF Downloads 212