Search results for: multi-scale computational modelling

Authors: Begum Serim-Yildiz

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The aim of this study is to examine the role of parents' emotional and behavioral reactions on fears of children in the COVID-19 pandemic considering Rachman’s Three Pathways Theory. For this purpose, a phenomenological qualitative study was conducted. Thirteen participants living with their children were utilized through criterion and snowball sampling. In semi-structured interviews parents were asked about their own and their children’s beahavioral and emotional reactions in the COVID-19 pandemic, and they were expected to give detailed information about fears of their children before and in pandemic. Firstly, parents were asked about their behavioral and emotional reactions in the COVID-19 pandemic. As behavioral reactions, precautions taken by parents to protect the rest of the family from negative physical and emotional impact of the pandemic were mentioned, while emotional reactions were defined as acquisition of negative emotions like fear, anxiety, and worry. Secondly, parents were asked about their children’s behavioral and emotional reactions. Some of the parents talked about positive behavioral changes such as gaining self-control, while some others explained negative behavioral changes like increased time spent with technological tools. In the emotional changes section, all of the parents explained at least one negative emotion. All of the parents stated that their children had COVID-19 related fears. According to parents’ expressions, fears of children in pandemic were examined in two dimensions. Fears directly related to COVID-19 were fear of virus/microbes, illness or death of someone in family and death and fears. Fears indirectly related to COVID-19 were fear of going out, sleep alone at night, separation, touching stuff outside the home, and cold. Considering existing literature and based on the findings of this study, it can be concluded that children’s modelling experiences have impact on acquisition of negative emotions, especially fear, therefore, preventive interventions involving caregivers should be provided by mental health professionals working with children.

Keywords: children’s fears, COVID-19 pandemic, modelling experiences, parents’ reactions

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Authors: Kyoungwoo Park, Gil Dong Kim, Seong Joon Moon, Ho Kil Lee

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The Urea-SCR is one of the most efficient technologies to reduce NOx emissions in diesel engines. In the present work, the computational prediction of internal flow and spray characteristics in the Urea-SCR system was carried out by using 3D-CFD simulation to evaluate NH3 uniformity index (NH3 UI) and its activation time according to the official New European Driving Cycle (NEDC). The number of nozzle and its diameter, two types of injection directions, and penetration length were chosen as the design variables. The optimal solutions were obtained by coupling the CFD analysis with Taguchi method. The L16 orthogonal array and small-the-better characteristics of the Taguchi method were used, and the optimal values were confirmed to be valid with 95% confidence and 5% significance level through analysis of variance (ANOVA). The results show that the optimal solutions for the NH3 UI and activation time (NH3 UI 0.22) are obtained by 0.41 and 0,125 second, respectively, and their values are improved by 85.0% and 10.7%, respectively, compared with those of the base model.

Keywords: computational fluid dynamics, NH3 uniformity index, optimization, Taguchi method, Urea-SCR system, UWS injector

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Authors: Andrea Macruz

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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience

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Authors: Zdzislaw Piotr Kaminski, Miroslaw Wendeker, Zbigniew Czyz

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The paper describes the geometric model, calculation algorithm and results of the CFD simulation of the airflow around a rotor in the vertical axis wind turbine (VAWT) with the ANSYS Fluent computational solver. The CFD method enables creating aerodynamic characteristics of forces acting on rotor working surfaces and determining parameters such as torque or power generated by the rotor assembly. The object of the research was a rotor whose construction is based on patent no.PL219985. The conducted tests enabled a mathematical model with a description of the generation of aerodynamic forces acting on each rotor blade. Additionally, this model was compared to the results of the wind tunnel tests. The analysis also focused on the influence of the blade angle on turbine power and the TSR. The research has shown that the turbine blade angle has a significant impact on the optimal value of the TSR.

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

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Authors: Saeed Khandan Siar, Stefan Tenbohlen, Christian Breuer, Raphael Lebreton

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The goal of this article is to investigate the detailed temperature distribution and the fluid flow of an oil cooled winding of a power transformer by means of computational fluid dynamics (CFD). The experimental setup consists of three passes of a zig-zag cooled disc type winding, in which losses are modeled by heating cartridges in each winding segment. A precise temperature sensor measures the temperature of each turn. The laboratory setup allows the exact control of the boundary conditions, e.g. the oil flow rate and the inlet temperature. Furthermore, a simulation model is solved using the open source computational fluid dynamics solver OpenFOAM and validated with the experimental results. The model utilizes the laminar and turbulent flow for the different mass flow rate of the oil. The good agreement of the simulation results with experimental measurements validates the model.

Keywords: CFD, conjugated heat transfer, power transformers, temperature distribution

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Authors: Taher S. Ababneh, Taghreed M. A. Jazzazi, Tareq M. A. Alshboul

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The inhibiting action against aluminum corrosion by three derivatives of 1,8-bis (benzylideneamino) naphthalene (BN) Schiff base has been investigated by means of DFT quantum chemical calculations at the B3LYP/6-31G(d) level of theory. The derivatives (CBN, NBN and MBN) were prepared from the condensation reaction of 1,8-diaminonaphthalene with substituted benzaldehyde (4-CN, 3-NO₂ and 3,4-(OMe)₂, respectively). Calculations were conducted to study the adsorption of each Schiff base on aluminum surface to evaluate its potential as a corrosion inhibitor. The computational structural features and electronic properties of each derivative such as relative energies and energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) have been reported. Thermodynamic functions and quantum chemical parameters such as the hardness of the inhibitor, the softness and the electrophilicity index were calculated to determine the derivative of the highest inhibition efficiency.

Keywords: corrosion, aluminum, DFT calculation, 1, 8-diaminonaphthalene, benzaldehyde

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Authors: Jerome Joshi

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The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

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Authors: Nijanthan Mohan, Rolf Gross, Fabian Theis

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The conventional method used in the construction industries often resulted in significant rework since most of the decisions were taken onsite under the pressure of project deadlines and also due to the improper information flow, which results in ineffective coordination. However, today’s architecture, engineering, and construction (AEC) stakeholders demand faster and accurate deliverables, efficient buildings, and smart processes, which turns out to be a tall order. Hence, the building information modelling (BIM) concept was developed as a solution to fulfill the above-mentioned necessities. Even though BIM is successfully implemented in most of the world, it is still in the early stages in Germany, since the stakeholders are sceptical of its reliability and efficiency. Due to the huge capital requirement, the small and medium-sized construction companies are still reluctant to implement BIM workflow in their projects. The purpose of this paper is to analyse the opportunities and obstacles to implementing BIM for prefabrication. Among all other advantages of BIM, pre-fabrication is chosen for this paper because it plays a vital role in creating an impact on time as well as cost factors of a construction project. The positive impact of prefabrication can be explicitly observed by the project stakeholders and participants, which enables the breakthrough of the skepticism factor among the small scale construction companies. The analysis consists of the development of a process workflow for implementing prefabrication in building construction, followed by a practical approach, which was executed with two case studies. The first case study represents on-site prefabrication, and the second was done for off-site prefabrication. It was planned in such a way that the first case study gives a first-hand experience for the workers at the site on the BIM model so that they can make much use of the created BIM model, which is a better representation compared to the traditional 2D plan. The main aim of the first case study is to create a belief in the implementation of BIM models, which was succeeded by the execution of offshore prefabrication in the second case study. Based on the case studies, the cost and time analysis was made, and it is inferred that the implementation of BIM for prefabrication can reduce construction time, ensures minimal or no wastes, better accuracy, less problem-solving at the construction site. It is also observed that this process requires more planning time, better communication, and coordination between different disciplines such as mechanical, electrical, plumbing, architecture, etc., which was the major obstacle for successful implementation. This paper was carried out in the perspective of small and medium-sized mechanical contracting companies for the private building sector in Germany.

Keywords: building information modelling, construction wastes, pre-fabrication, small and medium sized company

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Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

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The two stage assembly flowshop scheduling problem has lots of application in real life. To the best of our knowledge, the two stage assembly flowshop scheduling problem with total tardiness performance measure and separate setup times has not been addressed so far, and hence, it is addressed in this paper. Different dominance relations are developed and several algorithms are proposed. Extensive computational experiments are conducted to evaluate the proposed algorithms. The computational experiments have shown that one of the algorithms performs much better than the others. Moreover, the experiments have shown that the best performing algorithm performs much better than the best existing algorithm for the case of zero setup times in the literature. Therefore, the proposed best performing algorithm not only can be used for problems with separate setup times but also for the case of zero setup times.

Keywords: scheduling, assembly flowshop, total tardiness, algorithm

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Authors: Mohammad Jamalabadi, Noemi Zabari, Lukasz Bratasz

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Panel paintings -complex multi-layer structures consisting of wood support and a paint layer composed of a preparatory layer of gesso, paints, and varnishes- are among the category of cultural objects most vulnerable to relative humidity fluctuations and frequently found in museum collections. The current environmental specifications in museums have been derived using the criterion of crack initiation in an undamaged, usually new gesso layer laid on wood. In reality, historical paintings exhibit complex crack patterns called craquelures. The present paper analyses the structural response of a paint layer with a virtual network of rectangular cracks under environmental loadings using a three-dimensional model of a panel painting. Two modes of loading are considered -one induced by one-dimensional moisture response of wood support, termed the tangential loading, and the other isotropic induced by drying shrinkage of the gesso layer. The superposition of the two modes is also analysed. The modelling showed that minimum distances between cracks parallel to the wood grain depended on the gesso stiffness under the tangential loading. In spite of a non-zero Poisson’s ratio, gesso cracks perpendicular to the wood grain could not be generated by the moisture response of wood support. The isotropic drying shrinkage of gesso produced cracks that were almost evenly spaced in both directions. The modelling results were cross-checked with crack patterns obtained on a mock-up of a panel painting exposed to a number of extreme environmental variations in an environmental chamber.

Keywords: fracture saturation, surface cracking, paintings on wood, wood panels

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Authors: Oğuzhan Hasançebi, Saeid Kazemzadeh Azad

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Keywords: structural design optimization, optimal sizing, metaheuristics, self-adaptive step-size search, steel trusses, steel frames

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Authors: D. Ramajo, S. Corzo, M. Nigro

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A Multi-dimensional computational fluid dynamics (CFD) two-phase model was developed with the aim to simulate the in-core coolant circuit of a pressurized heavy water reactor (PHWR) of a commercial nuclear power plant (NPP). Due to the fact that this PHWR is a Reactor Pressure Vessel type (RPV), three-dimensional (3D) detailed modelling of the large reservoirs of the RPV (the upper and lower plenums and the downcomer) were coupled with an in-house finite volume one-dimensional (1D) code in order to model the 451 coolant channels housing the nuclear fuel. Regarding the 1D code, suitable empirical correlations for taking into account the in-channel distributed (friction losses) and concentrated (spacer grids, inlet and outlet throttles) pressure losses were used. A local power distribution at each one of the coolant channels was also taken into account. The heat transfer between the coolant and the surrounding moderator was accurately calculated using a two-dimensional theoretical model. The implementation of subcooled boiling and condensation models in the 1D code along with the use of functions for representing the thermal and dynamic properties of the coolant and moderator (heavy water) allow to have estimations of the in-core steam generation under nominal flow conditions for a generic fission power distribution. The in-core mass flow distribution results for steady state nominal conditions are in agreement with the expected from design, thus getting a first assessment of the coupled 1/3D model. Results for nominal condition were compared with those obtained with a previous 1/3D single-phase model getting more realistic temperature patterns, also allowing visualize low values of void fraction inside the upper plenum. It must be mentioned that the current results were obtained by imposing prescribed fission power functions from literature. Therefore, results are showed with the aim of point out the potentiality of the developed model.

Keywords: PHWR, CFD, thermo-hydraulic, two-phase flow

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Gajanan M. Sonwane

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The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity. This strategy of designing compounds possessing selectivity over specific tyrosine kinase has been achieved through G-QSAR and molecular docking studies. The objective of this research has been to design newer 2-phenazinamine derivatives as Bcr-Abl tyrosine kinase inhibitors by G-QSAR, molecular docking studies followed by wet-lab studies along with evaluation of their anticancer potential. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2 followed by wet-lab experiments for synthesizing 2-phenazinamine derivatives. The chemical structures of ligands in 2D were drawn by employing Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using a semi-empirical method called MOPAC. The protein structure was retrieved from RCSC protein data bank as a PDB file. The binding interactions of protein and ligands were done by using PYMOL. The molecular properties of the designed compounds were predicted in silico by using Osiris property explorer. The parent compound 2-phenazinamine was synthesized by reduction of 2, 4-dinitro-N-phenyl-benzenamine in the presence of tin chloride followed by cyclization in the presence of nitrobenzene and magnesium sulfate. The derivatization at the amino function of 2-phenazinamine was performed by treating parent compound with various aldehydes in the presence of dicyclohexylcarbodiimide (DCC) and urea to afford 2-(2-chlorophenyl)-3-(phenazine-2-yl) thiazolidine-4-one. Synthesized 39 novel derivatives of 2-phenazinamine and performed antioxidant activity, anti antiproliferative on the bulb of onion and anticancer activity on cell line showing significant competition with marked blockbuster drug imatinib.

Keywords: computer-aided drug design, tyrosin kinases, anticancer, docking

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Authors: Nizar Tayem, AbuMuhammad Moinuddeen, Ahmed A. Hussain, Redha M. Radaydeh

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This research paper introduces an approach for estimating the direction of arrival (DOA) of multiple RF noncoherent sources in a uniform linear array (ULA). The proposed method utilizes a Capon-like estimation algorithm and incorporates LU decomposition to enhance the accuracy of DOA estimation while significantly reducing computational complexity compared to existing methods like the Capon method. Notably, the proposed method does not require prior knowledge of the number of sources. To validate its effectiveness, the proposed method undergoes validation through both software simulations and practical experimentation on a prototype testbed constructed using a software-defined radio (SDR) platform and GNU Radio software. The results obtained from MATLAB simulations and real-time experiments provide compelling evidence of the proposed method's efficacy.

Keywords: DOA estimation, real-time validation, software defined radio, computational complexity, Capon's method, GNU radio

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Authors: Mohamed Gaafar, Evan Davies

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Many municipalities within Canada and abroad use chloramination to disinfect drinking water so as to avert the production of the disinfection by-products (DBPs) that result from conventional chlorination processes and their consequential public health risks. However, the long-lasting monochloramine disinfectant (NH2Cl) can pose a significant risk to the environment. As, it can be introduced into stormwater sewers, from different water uses, and thus freshwater sources. Little research has been undertaken to monitor and characterize the decay of NH2Cl and to study the parameters affecting its decomposition in stormwater networks. Therefore, the current study was intended to investigate this decay starting by building a stormwater model and validating its hydraulic and hydrologic computations, and then modelling water quality in the storm sewers and examining the effects of different parameters on chloramine decay. The presented work here is only the first stage of this study. The 30th Avenue basin in Southern Edmonton was chosen as a case study, because the well-developed basin has various land-use types including commercial, industrial, residential, parks and recreational. The City of Edmonton has already built a MIKE-URBAN stormwater model for modelling floods. Nevertheless, this model was built to the trunk level which means that only the main drainage features were presented. Additionally, this model was not calibrated and known to consistently compute pipe flows higher than the observed values; not to the benefit of studying water quality. So the first goal was to complete modelling and updating all stormwater network components. Then, available GIS Data was used to calculate different catchment properties such as slope, length and imperviousness. In order to calibrate and validate this model, data of two temporary pipe flow monitoring stations, collected during last summer, was used along with records of two other permanent stations available for eight consecutive summer seasons. The effect of various hydrological parameters on model results was investigated. It was found that model results were affected by the ratio of impervious areas. The catchment length was tested, however calculated, because it is approximate representation of the catchment shape. Surface roughness coefficients were calibrated using. Consequently, computed flows at the two temporary locations had correlation coefficients of values 0.846 and 0.815, where the lower value pertained to the larger attached catchment area. Other statistical measures, such as peak error of 0.65%, volume error of 5.6%, maximum positive and negative differences of 2.17 and -1.63 respectively, were all found in acceptable ranges.

Keywords: stormwater, urban drainage, simulation, validation, MIKE URBAN

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Xavier Bertrand, Alexandre Cayrel

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The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

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Authors: Makenzy Lee Gilbert

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This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, reinforcement, retrieval, and forgetting. Key mathematical foundations, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus's role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future exploration areas.

Keywords: attractor neural networks, connectionism, computational modeling, cognitive neuroscience

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Authors: Dairo Jose Hernandez Paez

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The quantum theory of atoms in molecules (QTAIM) allows us to obtain topological information on electronic density in quantum mechanical systems. The QTAIM starts by considering the electron density as a continuous mathematical object. On the other hand, the discretization of electron density is also a mathematical object, which, from discrete mathematics, would allow a new approach to its topological study. From this point of view, it is necessary to develop a series of steps that provide the theoretical support that guarantees its application. Some of the steps that we consider most important are mentioned below: (1) obtain good representations of the electron density through computational calculations, (2) design a methodology for the discretization of electron density, and construct the simplicial complex. (3) Make an analysis of the discrete vector field associating the simplicial complex. (4) Finally, in this research, we propose to use the discrete Morse theory as a mathematical tool to carry out studies of electron density topology.

Keywords: discrete mathematics, Discrete Morse theory, electronic density, computational calculations

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Authors: Maryam Hamlehdar, Guillermo A. Narsilio

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To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

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Authors: Yu T. Tsai, Jin H. Huang

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In this paper, the specific sound transmission loss (TL) of the laminated composite plate (LCP) with different material properties in each layer is investigated. The numerical method to obtain the TL of the LCP is proposed by using elastic plate theory. The transfer matrix approach is novelty presented for computational efficiency in solving the numerous layers of dynamic stiffness matrix (D-matrix) of the LCP. Besides the numerical simulations for calculating the TL of the LCP, the material properties inverse method is presented for the design of a laminated composite plate analogous to a metallic plate with a specified TL. As a result, it demonstrates that the proposed computational algorithm exhibits high efficiency with a small number of iterations for achieving the goal. This method can be effectively employed to design and develop tailor-made materials for various applications.

Keywords: sound transmission loss, laminated composite plate, transfer matrix approach, inverse problem, elastic plate theory, material properties

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Authors: I. Inuaeyen, L. Phil, O. Eni

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Fossil fuels have been the main source of global energy for many decades, accounting for about 80% of global energy need. This is beginning to change however with increasing concern about greenhouse gas emissions which comes mostly from fossil fuel combustion. Greenhouse gases such as carbon dioxide are responsible for stimulating climate change. As a result, there has been shift towards more clean and renewable energy sources of energy as a strategy for stemming greenhouse gas emission into the atmosphere. The production of bio-products such as bio-fuel, bio-electricity, bio-chemicals, and bio-heat etc. using biomass materials in accordance with the bio-refinery concept holds a great potential for reducing high dependence on fossil fuel and their resources. The bio-refinery concept promotes efficient utilisation of biomass material for the simultaneous production of a variety of products in order to minimize or eliminate waste materials. This will ultimately reduce greenhouse gas emissions into the environment. In Nigeria, cassava solid waste from cassava processing facilities has been identified as a vital feedstock for bio-refinery process. Cassava is generally a staple food in Nigeria and one of the most widely cultivated foodstuff by farmers across Nigeria. As a result, there is an abundant supply of cassava waste in Nigeria. In this study, the aim is to explore opportunities for converting cassava waste to a range of bio-products such as butanol, ethanol, electricity, heat, methanol, furfural etc. using a combination of biochemical, thermochemical and chemical conversion routes. . The best process scenario will be identified through the evaluation of economic analysis, energy efficiency, life cycle analysis and social impact. The study will be carried out by developing a model representing different process options for cassava waste conversion to useful products. The model will be developed using Aspen Plus process simulation software. Process economic analysis will be done using Aspen Icarus software. So far, comprehensive survey of literature has been conducted. This includes studies on conversion of cassava solid waste to a variety of bio-products using different conversion techniques, cassava waste production in Nigeria, modelling and simulation of waste conversion to useful products among others. Also, statistical distribution of cassava solid waste production in Nigeria has been established and key literatures with useful parameters for developing different cassava waste conversion process has been identified. In the future work, detailed modelling of the different process scenarios will be carried out and the models validated using data from literature and demonstration plants. A techno-economic comparison of the various process scenarios will be carried out to identify the best scenario using process economics, life cycle analysis, energy efficiency and social impact as the performance indexes.

Keywords: bio-refinery, cassava waste, energy, process modelling

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Authors: Hyun-Woo Cho

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Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: Xuan Zhou, Litian Zhang, Shuixiang Li

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Mesh deformation using radial basis function interpolation method has been demonstrated to produce quality meshes with relatively little computational cost using a concise algorithm. However, it still suffers from the limited deformation ability, especially in large deformation. In this paper, a pre-displacement improvement is proposed to improve the problem that illegal meshes always appear near the moving inner boundaries owing to the large relative displacement of the nodes near inner boundaries. In this improvement, nodes near the inner boundaries are first associated to the near boundary nodes, and a pre-displacement based on the displacements of associated boundary nodes is added to the nodes near boundaries in order to make the displacement closer to the boundary deformation and improve the deformation capability. Several 2D and 3D numerical simulation cases have shown that the pre-displacement improvement for radial basis function (RBF) method significantly improves the mesh quality near inner boundaries and deformation capability, with little computational burden increasement.

Keywords: mesh deformation, mesh quality, background mesh, radial basis function

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Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

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Authors: Juni C. Kim, Anna R. Robuck, Douglas I. Walker

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The human exposome, which includes chemical exposures over the lifetime and their effects, is now recognized as an important measure for understanding human health; however, the complexity of the data makes the identification of environmental chemicals challenging. The goal of our project was to establish a computational workflow for the improved identification of environmental pollutants containing chlorine or bromine. Using the “pattern. search” function available in the R package NonTarget, we wrote a multifunctional script that searches mass spectral clusters from untargeted gas-chromatography high-resolution mass spectrometry (GC-HRMS) for the presence of spectra consistent with chlorine and bromine-containing organic compounds. The “pattern. search” function was incorporated into a different function that allows the evaluation of clusters containing multiple analyte fragments, has multi-core support, and provides a simplified output identifying listing compounds containing chlorine and/or bromine. The new function was able to process 46,000 spectral clusters in under 8 seconds and identified over 150 potential halogenated spectra. We next applied our function to a deidentified dataset from patients diagnosed with primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and healthy controls. Twenty-two spectra corresponded to potential halogenated compounds in the PSC and PBC dataset, including six significantly different in PBC patients, while four differed in PSC patients. We have developed an improved algorithm for detecting halogenated compounds in GC-HRMS data, providing a strategy for prioritizing exposures in the study of human disease.

Keywords: exposome, metabolome, computational metabolomics, high-resolution mass spectrometry, exposure, pollutants

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Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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Authors: W. P. Hu, J. V. Kumar, Jeffrey J. P. Tsai

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The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.

Keywords: nonpeptide inhibitor, Src SH2 domain, LibDock, molecular dynamics simulation

Procedia PDF Downloads 269