Search results for: multi-scale computational modelling

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Laila A. H. F. Dashti, Tom Jackson, Andrew West, Lisa Jackson

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Traceability systems are important in the agri-food and halal food sectors for monitoring ingredient movements, tracking sources, and ensuring food integrity. However, designing a traceability system for the halal food supply chain is challenging due to diverse stakeholder requirements and complex needs. Existing literature on stakeholder mapping and identifying requirements for halal food supply chains is limited. To address this gap, a pilot study was conducted to identify the objectives, requirements, and recommendations of stakeholders in the Kuwaiti halal food industry. The study collected data through semi-structured interviews with an international halal food manufacturer based in Kuwait. The aim was to gain a deep understanding of stakeholders' objectives, requirements, processes, and concerns related to the design of a traceability system in the country's halal food sector. Traceability systems are being developed and tested in the agri-food and halal food sectors due to their ability to monitor ingredient movements, track sources, and detect potential issues related to food integrity. Designing a traceability system for the halal food supply chain poses significant challenges due to diverse stakeholder requirements and the complexity of their needs (including varying food ingredients, different sources, destinations, supplier processes, certifications, etc.). Achieving a halal food traceability solution tailored to stakeholders' requirements within the supply chain necessitates prior knowledge of these needs. Although attempts have been made to address design-related issues in traceability systems, literature on stakeholder mapping and identification of requirements specific to halal food supply chains is scarce. Thus, this pilot study aims to identify the objectives, requirements, and recommendations of stakeholders in the halal food industry. The paper presents insights gained from the pilot study, which utilized semi-structured interviews to collect data from a Kuwait-based international halal food manufacturer. The objective was to gain an in-depth understanding of stakeholders' objectives, requirements, processes, and concerns pertaining to the design of a traceability system in Kuwait's halal food sector. The stakeholder mapping results revealed that government entities, food manufacturers, retailers, and suppliers are key stakeholders in Kuwait's halal food supply chain. Lessons learned from this pilot study regarding requirement capture for traceability systems include the need to streamline communication, focus on communication at each level of the supply chain, leverage innovative technologies to enhance process structuring and operations and reduce halal certification costs. The findings also emphasized the limitations of existing traceability solutions, such as limited cooperation and collaboration among stakeholders, high costs of implementing traceability systems without government support, lack of clarity regarding product routes, and disrupted communication channels between stakeholders. These findings contribute to a broader research program aimed at developing a stakeholder requirements framework that utilizes "business process modelling" to establish a unified model for traceable stakeholder requirements.

Keywords: supply chain, traceability system, halal food, stakeholders’ requirements

Procedia PDF Downloads 113

Authors: Ani Kojoyan

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Linguistic studies have been investigating a connection between gender and linguistic development since 1970s. Scholars claim that gender differences in first and second language learning are socially constructed. Recent studies to language learning and gender reveal that second language acquisition is also a social phenomenon directly influencing one’s gender identity. Those responsible for designing language learning-teaching materials should be encouraged to understand the importance of and address the gender sensitivity accurately in textbooks. Writing or compiling a textbook is not an easy task; it requires strong academic abilities, patience, and experience. For a long period of time Armenia has been involved in the compilation process of a number of foreign language textbooks. However, there have been very few discussions or evaluations of those textbooks which will allow specialists to theorize that practice. The present paper focuses on the analysis of gender sensitivity issues and policy aspects involved in an EFL textbook. For the research the following material has been considered – “A Basic English Grammar: Morphology”, first printed in 2011. The selection of the material is not accidental. First, the mentioned textbook has been widely used in university teaching over years. Secondly, in Armenia “A Basic English Grammar: Morphology” has considered one of the most successful English grammar textbooks in a university teaching environment and served a source-book for other authors to compile and design their textbooks. The present paper aims to find out whether an EFL textbook is gendered in the Armenian teaching environment, and whether the textbook compilers are aware of gendered messages while compiling educational materials. It also aims at investigating students’ attitude toward the gendered messages in those materials. And finally, it also aims at increasing the gender sensitivity among book compilers and educators in various educational settings. For this study qualitative and quantitative research methods of analyses have been applied, the quantitative – in terms of carrying out surveys among students (45 university students, 18-25 age group), and the qualitative one – by discourse analysis of the material and conducting in-depth and semi-structured interviews with the Armenian compilers of the textbook (interviews with 3 authors). The study is based on passive and active observations and teaching experience done in a university classroom environment in 2014-2015, 2015-2016. The findings suggest that the discussed and analyzed teaching materials (145 extracts and examples) include traditional examples of intensive use of language and role-modelling, particularly, men are mostly portrayed as active, progressive, aggressive, whereas women are often depicted as passive and weak. These modeled often serve as a ‘reliable basis’ for reinforcing the traditional roles that have been projected on female and male students. The survey results also show that such materials contribute directly to shaping learners’ social attitudes and expectations around issues of gender. The applied techniques and discussed issues can be generalized and applied to other foreign language textbook compilation processes, since those principles, regardless of a language, are mostly the same.

Keywords: EFL textbooks, gender policy, gender sensitivity, qualitative and quantitative research methods

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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: 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: 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: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: electric propulsion, mass gauging, propellant, PVT, xenon

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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: Trevor C. Brown, David J. Miron

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Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

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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: O. Anwar Beg, Armghan Zubair, Sireetorn Kuharat, Meisam Babaie

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In this work, motivated by rocket channel cooling applications, we describe recent CFD simulations of turbulent convective heat transfer in mini-channels at different aspect ratios. ANSYS FLUENT software has been employed with a mean average error of 5.97% relative to Forrest’s MIT cooling channel study (2014) at a Reynolds number of 50,443 with a Prandtl number of 3.01. This suggests that the simulation model created for turbulent flow was suitable to set as a foundation for the study of different aspect ratios in the channel. Multiple aspect ratios were also considered to understand the influence of high aspect ratios to analyse the best performing cooling channel, which was determined to be the highest aspect ratio channels. Hence, the approximate 28:1 aspect ratio provided the best characteristics to ensure effective cooling. A mesh convergence study was performed to assess the optimum mesh density to collect accurate results. Hence, for this study an element size of 0.05mm was used to generate 579,120 for proper turbulent flow simulation. Deploying a greater bias factor would increase the mesh density to the furthest edges of the channel which would prove to be useful if the focus of the study was just on a single side of the wall. Since a bulk temperature is involved with the calculations, it is essential to ensure a suitable bias factor is used to ensure the reliability of the results. Hence, in this study we have opted to use a bias factor of 5 to allow greater mesh density at both edges of the channel. However, the limitations on mesh density and hardware have curtailed the sophistication achievable for the turbulence characteristics. Also only linear rectangular channels were considered, i.e. curvature was ignored. Furthermore, we only considered conventional water coolant. From this CFD study the variation of aspect ratio provided a deeper appreciation of the effect of small to high aspect ratios with regard to cooling channels. Hence, when considering an application for the channel, the geometry of the aspect ratio must play a crucial role in optimizing cooling performance.

Keywords: rocket channel cooling, ANSYS FLUENT CFD, turbulence, convection heat transfer

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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

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Authors: Óscar Muñoz Garrigós, José Manuel Bernabeu Aubán

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Time-sensitive services are the base of the cloud services industry. Keeping low service saturation is essential for controlling response time. All auto-scalable services make use of reactive auto-scaling. However, reactive auto-scaling has few in-depth studies. This presentation shows a model for reactive auto-scaling methodologies with a MAPE-k architecture. Queuing theory can compute different properties of static services but lacks some parameters related to the transition between models. Our model uses queuing theory parameters to relate the transition between models. It associates MAPE-k related times, the sampling frequency, the cooldown period, the number of requests that an instance can handle per unit of time, the number of incoming requests at a time instant, and a function that describes the acceleration in the service's ability to handle more requests. This model is later used as a solution to horizontally auto-scale time-sensitive services composed of microservices, reevaluating the model’s parameters periodically to allocate resources. The solution requires limiting the acceleration of the growth in the number of incoming requests to keep a constrained response time. Business benefits determine such limits. The solution can add a dynamic number of instances and remains valid under different system sizes. The study includes performance recommendations to improve results according to the incoming load shape and business benefits. The exposed methodology is tested in a simulation. The simulator contains a load generator and a service composed of two microservices, where the frontend microservice depends on a backend microservice with a 1:1 request relation ratio. A common request takes 2.3 seconds to be computed by the service and is discarded if it takes more than 7 seconds. Both microservices contain a load balancer that assigns requests to the less loaded instance and preemptively discards requests if they are not finished in time to prevent resource saturation. When load decreases, instances with lower load are kept in the backlog where no more requests are assigned. If the load grows and an instance in the backlog is required, it returns to the running state, but if it finishes the computation of all requests and is no longer required, it is permanently deallocated. A few load patterns are required to represent the worst-case scenario for reactive systems: the following scenarios test response times, resource consumption and business costs. The first scenario is a burst-load scenario. All methodologies will discard requests if the rapidness of the burst is high enough. This scenario focuses on the number of discarded requests and the variance of the response time. The second scenario contains sudden load drops followed by bursts to observe how the methodology behaves when releasing resources that are lately required. The third scenario contains diverse growth accelerations in the number of incoming requests to observe how approaches that add a different number of instances can handle the load with less business cost. The exposed methodology is compared against a multiple threshold CPU methodology allocating/deallocating 10 or 20 instances, outperforming the competitor in all studied metrics.

Keywords: reactive auto-scaling, auto-scaling, microservices, cloud computing

Procedia PDF Downloads 93

Authors: Tapiwa Brine Mutsauri

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The MEROPS system is an information resource for proteases that classifies them into clans according to their catalytic type. Within the Plant kingdom, cysteine ​​proteases are one of the best known, as they are the catalytic type on which the first studies on plant proteases were focused. Plant cysteine ​​proteases have a similar mechanism of action to serine proteases, and some are known to have activity on factors of the blood coagulation cascade, such as a potent antithrombotic effect, and also cause increased fibrinolysis. Of a few plant cysteine ​​proteases, the three-dimensional structure is known, so a method of interest to be able to predict their potential activity on the factors of the coagulation cascade would be to know their structure. Phylogenetics is the study of the evolutionary relationships between biological entities, often species, individuals, or genes (which can be called taxa). It is essential to identify the evolutionary position and the possible distribution of these enzymes in the plant kingdom, particularly those that act on coagulation factors. Bioinformatic tools, such as Clustal Omega / Jalview and Mega6, can be used to create phylogenetic trees. From the results of the alignment, it can be seen that although there is a certain degree of conservation (Conservation) and consensus (Consensus) among the eleven sequences, the functionally important motifs (those corresponding to the active site), the degree of conservation and consensus is very low. We could then infer that although activity on coagulation is reported for these enzymes, linked to their structural and mechanistic similarity with serine proteases, this activity may not have a direct or primary relationship with the proteolytic activity associated with their common, poorly conserved active site in this case. This ultimately could be related to modifications in the reaction mechanism of several of the enzymes studied, which would require more detailed study. Also, below, we will deal with factors that may have a greater influence on this result. The results of this work enrich the understanding of how species (and molecular sequences in general) evolve. Through phylogenetics, we learn not only how sequences came to be the way they are today but also the general principles that allow us to predict how they will change in the future. For pharmaceutical sciences, phylogenetic selection of biologically related species can help identify closely related members of a species with compounds of pharmacological importance, such as plant cysteine ​​proteases, in addition to identifying structural features that may influence their pharmacological activity and which can be valuable for drug design.

Keywords: computational simulation, proteases, coagulation, bioinformatics

Procedia PDF Downloads 17

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

Procedia PDF Downloads 108

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

Procedia PDF Downloads 365

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

Procedia PDF Downloads 126

Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

Procedia PDF Downloads 101

Authors: M. Eickermann, F. Ronellenfitsch, J. Junk

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Oilseed rape (Brassica napus L.) is one of the most important crops throughout Europe, but pressure due to pest insects and pathogens can reduce yield amount substantially. Therefore, the usage of pesticide applications is outstanding in this crop. In addition, climate change effects can interact with phenology of the host plant and their pests and can apply additional pressure on the yield. Next to the pollen beetle, Meligethes aeneus L., the seed-damaging pest insects, cabbage seed weevil (Ceutorhynchus obstrictus Marsham) and the brassica pod midge (Dasineura brassicae Winn.) are of main economic impact to the yield. While females of C. obstrictus are infesting oilseed rape by depositing single eggs into young pods, the females of D. brassicae are using this local damage in the pod for their own oviposition, while depositing batches of 20-30 eggs. Without a former infestation by the cabbage seed weevil, a significant yield reduction by the brassica pod midge can be denied. Based on long-term, multisided field experiments, a comprehensive data-set on pest migration to crops of B. napus has been built up in the last ten years. Five observational test sides, situated in different climatic regions in Luxembourg were controlled between February until the end of May twice a week. Pest migration was recorded by using yellow water pan-traps. Caught insects were identified in the laboratory according to species specific identification keys. By a combination of pest observations and corresponding meteorological observations, the set-up of models to predict the migration periods of the seed-damaging pests was possible. This approach is the basis for a computer-based decision support tool, to assist the farmer in identifying the appropriate time point of pesticide application. In addition, the derived algorithms of that decision support tool can be combined with climate change projections in order to assess the future potential threat caused by the seed-damaging pest species. Regional climate change effects for Luxembourg have been intensively studied in recent years. Significant changes to wetter winters and drier summers, as well as a prolongation of the vegetation period mainly caused by higher spring temperature, have also been reported. We used the COSMO-CLM model to perform a time slice experiment for Luxembourg with a spatial resolution of 1.3 km. Three ten year time slices were calculated: The reference time span (1991-2000), the near (2041-2050) and the far future (2091-2100). Our results projected a significant shift of pest migration to an earlier onset of the year. In addition, a prolongation of the possible migration period could be observed. Because D. brassiace is depending on the former oviposition activity by C. obstrictus to infest its host plant successfully, the future dependencies of both pest species will be assessed. Based on this approach the future risk potential of both seed-damaging pests is calculated and the status as pest species is characterized.

Keywords: CORDEX projections, decision support tool, Brassica napus, pests

Procedia PDF Downloads 382

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 337

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 389

Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

Procedia PDF Downloads 217

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 223

Authors: Maria Amelia V. C. Araujo, Billy J. Araujo, Brian Greenwood

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The flow over a backward-facing step is characterized by the presence of flow separation, recirculation and reattachment, for a simple geometry. This type of fluid behaviour takes place in many practical engineering applications, hence the reason for being investigated. Historically, fluid flows over a backward-facing step have been examined in many experiments using a variety of measuring techniques such as laser Doppler velocimetry (LDV), hot-wire anemometry, particle image velocimetry or hot-film sensors. However, some of these techniques cannot conveniently be used in separated flows or are too complicated and expensive. In this work, the applicability of the acoustic Doppler velocimetry (ADV) technique is investigated to such type of flows, at various Reynolds numbers corresponding to different flow regimes. The use of this measuring technique in separated flows is very difficult to find in literature. Besides, most of the situations where the Reynolds number effect is evaluated in separated flows are in numerical modelling. The ADV technique has the advantage in providing nearly non-invasive measurements, which is important in resolving turbulence. The ADV Nortek Vectrino+ was used to characterize the flow, in a recirculating laboratory flume, at various Reynolds Numbers (Reh = 3738, 5452, 7908 and 17388) based on the step height (h), in order to capture different flow regimes, and the results compared to those obtained using other measuring techniques. To compare results with other researchers, the step height, expansion ratio and the positions upstream and downstream the step were reproduced. The post-processing of the AVD records was performed using a customized numerical code, which implements several filtering techniques. Subsequently, the Vectrino noise level was evaluated by computing the power spectral density for the stream-wise horizontal velocity component. The normalized mean stream-wise velocity profiles, skin-friction coefficients and reattachment lengths were obtained for each Reh. Turbulent kinetic energy, Reynolds shear stresses and normal Reynolds stresses were determined for Reh = 7908. An uncertainty analysis was carried out, for the measured variables, using the moving block bootstrap technique. Low noise levels were obtained after implementing the post-processing techniques, showing their effectiveness. Besides, the errors obtained in the uncertainty analysis were relatively low, in general. For Reh = 7908, the normalized mean stream-wise velocity and turbulence profiles were compared directly with those acquired by other researchers using the LDV technique and a good agreement was found. The ADV technique proved to be able to characterize the flow properly over a backward-facing step, although additional caution should be taken for measurements very close to the bottom. The ADV measurements showed reliable results regarding: a) the stream-wise velocity profiles; b) the turbulent shear stress; c) the reattachment length; d) the identification of the transition from transitional to turbulent flows. Despite being a relatively inexpensive technique, acoustic Doppler velocimetry can be used with confidence in separated flows and thus very useful for numerical model validation. However, it is very important to perform adequate post-processing of the acquired data, to obtain low noise levels, thus decreasing the uncertainty.

Keywords: ADV, experimental data, multiple Reynolds number, post-processing

Procedia PDF Downloads 148

Authors: Rajkumar Ghosh

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Water scarcity is a pressing issue in urban areas, even in smart cities where efficient resource management is a priority. This scarcity is mainly caused by factors such as lifestyle changes, excessive groundwater extraction, over-usage of water, rapid urbanization, and uncontrolled population growth. In the specific case of Gomti Nagar, Lucknow, Uttar Pradesh, India, the depletion of groundwater resources is particularly severe, leading to a water imbalance and posing a significant challenge for the region's sustainable development. The aim of this study is to address the water shortage in the Gomti Nagar region by focusing on the implementation of artificial groundwater recharge methods. Specifically, the research aims to investigate the effectiveness of rainwater collection through rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to reduce aquifer depletion and bridge the gap between groundwater recharge and extraction. The research methodology for this study involves the utilization of RTRWHs as the main method for collecting rainwater. This approach is considered effective in managing and conserving water resources in a sustainable manner. The focus is on implementing RTRWHs in residential and commercial buildings to maximize the collection of rainwater and its subsequent utilization for various purposes in the Gomti Nagar region. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage (0.04%) of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance of 24519 ML/yr in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. The findings of this study can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis. The data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. Statistical analysis and modelling techniques were employed to quantify the water imbalance and evaluate the effectiveness of RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. The study highlights the need for widespread adoption of RTRWHs in all buildings and emphasizes the importance of integrating such systems into the urban planning and development process. By doing so, smart cities like Gomti Nagar can achieve efficient water management, ensuring a better future with improved water availability for its residents.

Keywords: rooftop rainwater harvesting, rainwater, water management, aquifer

Procedia PDF Downloads 95

Authors: Małgorzata Golonka, Jadwiga Laska

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Among self-healing materials, the most unexplored group are thermoplastic polymers. These polymers are used not only to produce packaging with a relatively short life but also to obtain coatings, insulation, casings, or parts of machines and devices. Due to its exceptional resistance to weather conditions, hydrophobicity, sufficient mechanical strength, and ease of extrusion, polyethylene is used in the production of polymer pipelines and as an insulating layer for steel pipelines. Polyethylene or PE coated steel pipelines can be used in difficult conditions such as underground or underwater installations. Both installation and use under such conditions are associated with high stresses and consequently the formation of microdamages in the structure of the material, loss of its integrity and final applicability. The ideal solution would be to include a self-healing system in the polymer material. In the presented study the behavior of resin-coated microcapsules in the extrusion process of low-density polyethylene was examined. Microcapsules are a convenient element of the repair system because they can be filled with appropriate reactive substances to ensure the repair process, but the main problem is their durability under processing conditions. Rapeseed oil, which has a relatively high boiling point of 240⁰C and low volatility, was used as the core material that simulates the reactive agents. The capsule shell, which is a key element responsible for its mechanical strength, was obtained by in situ polymerising urea-formaldehyde, melamine-urea-formaldehyde or melamine-formaldehyde resin on the surface of oil droplets dispersed in water. The strength of the capsules was compared based on the shell material, and in addition, microcapsules with single- and multilayer shells were obtained using different combinations of the chemical composition of the resins. For example, the first layer of appropriate tightness and stiffness was made of melamine-urea-formaldehyde resin, and the second layer was a melamine-formaldehyde reinforcing layer. The size, shape, distribution of capsule diameters and shell thickness were determined using digital optical microscopy and electron microscopy. The efficiency of encapsulation (i.e., the presence of rapeseed oil as the core) and the tightness of the shell were determined by FTIR spectroscopic examination. The mechanical strength and distribution of microcapsules in polyethylene were tested by extruding samples of crushed low-density polyethylene mixed with microcapsules in a ratio of 1 and 2.5% by weight. The extrusion process was carried out in a mini extruder at a temperature of 150⁰C. The capsules obtained had a diameter range of 70-200 µm. FTIR analysis confirmed the presence of rapeseed oil in both single- and multilayer shell microcapsules. Microscopic observations of cross sections of the extrudates confirmed the presence of both intact and cracked microcapsules. However, the melamine-formaldehyde resin shells showed higher processing strength compared to that of the melamine-urea-formaldehyde coating and the urea-formaldehyde coating. Capsules with a urea-formaldehyde shell work very well in resin coating systems and cement composites, i.e., in pressureless processing and moulding conditions. The addition of another layer of melamine-formaldehyde coating to both the melamine-urea-formaldehyde and melamine-formaldehyde resin layers significantly increased the number of microcapsules undamaged during the extrusion process. The properties of multilayer coatings were also determined and compared with each other using computer modelling.

Keywords: self-healing polymers, polyethylene, microcapsules, extrusion

Procedia PDF Downloads 29

Authors: Asif Arshid, Ying Huang, Denver Tolliver

Abstract:

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

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