Search results for: firm dynamics

Authors: Javier Varillas, Jorge Alcalá

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We investigate dislocation avalanche phenomena in face-centered cubic (FCC) and body-centered cubic (BCC) crystals using massive, large-scale molecular dynamics (MD) simulations. The analysis is focused on the intermittent development of dense dislocation arrangements subjected to uniaxial tensile straining under displacement control. We employ a novel computational scheme that allows us to inject an entangled dislocation structure in periodic MD domains. We assess the emission of plastic bursts (or dislocation avalanches) in terms of the sharp stress drops detected in the stress-strain curve. The plastic activity corresponds to the sporadic operation of specific dislocation glide processes exhibiting quiescent periods between successive avalanche events. We find that the plastic intermittences in our simulations do not overlap in time under sufficiently low strain rates as dissipation operates faster than driving, where the dense dislocation networks evolve through the emission of dislocation avalanche events whose carried slip adheres to self-organized power-law distributions. These findings enable the extension of the slip distributions obtained from strict displacement-controlled micropillar compression experiments towards smaller values of slip size. Our results furnish further understanding upon the development of entangled dislocation networks in metal plasticity, including specific mechanisms of dislocation propagation and annihilation, along with the evolution of specific dislocation populations through dislocation density analyses.

Keywords: dislocations, intermittent plasticity, molecular dynamics, slip distributions

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Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

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Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

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Authors: Geuna Kim, Sanghyun Kim

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This study investigates various factors that may influence the ISM process, including the organization’s internal needs and external pressure, and examines the role of regulatory pressure in ISM development and performance. The 105 sets of data collected in a survey were tested against the research model using SEM. The results indicate that NP and TP had positive effects on the ISM process, except for perceived benefits. Regulatory pressure had a positive effect on the relationship between ISM awareness and ISM development and performance.

Keywords: information security management, need pull, technology push, regulatory pressure

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: Ernesto A. Lagarda-Leyva, Manuel A. Valenzuela L., José G. Oshima C., Arnulfo A. Naranjo-Flores

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From August to December of 2016, a diagnostic and strategic planning study was carried out on the supply chain of the company Agropecuaria GABO S.A. de C.V. The final product of the study was the development of the strategic plan and a project portfolio to meet the demands of the three links in the supply chain of the Roma tomato exported annually to the United States of America. In this project, the strategic objective of ensuring the proper handling of the product was selected and one of the goals associated with this was the employment of quantitative methods to support decision making. Considering the antecedents, the objective of this case study was to develop a model to analyze the behavioral dynamics in the distribution chain, from the logistics of storage and shipment of Roma tomato in 81-case pallets (11.5 kg per case), to the two pre-cooling rooms and eventual loading onto transports, seeking to reduce the bottleneck and the associated costs by means of a dynamic interface. The methodology used was that of system dynamics, considering four phases that were adapted to the purpose of the study: 1) the conceptualization phase; 2) the formulation phase; 3) the evaluation phase; and 4) the communication phase. The main practical conclusions lead to the possibility of reducing both the bottlenecks in the cooling rooms and the costs by simulating scenarios and modifying certain policies. Furthermore, the creation of the dynamic interface between the model and the stakeholders was achieved by generating interaction with buttons and simple instructions that allow making modifications and observing diverse behaviors.

Keywords: agrilogistics, distribution, scenarios, system dynamics

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Authors: Aakash Chhunchha, Assma Begum

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The qualitative aspects of hypersonic flow over a range of blunt bodies have been extensively analyzed in the past. It is well known that the curvature of a body’s geometry in the sonic region predominantly dictates the bow shock shape and its standoff distance from the body, while the surface pressure distribution depends on both the sonic region and on the local body shape. The present study is an extension to analyze the hypersonic flow characteristics over several blunt-nosed bodies using modern Computational Fluid Dynamics (CFD) tools to determine the shock shape and its effect on the heat flux around the body. 4 blunt-nosed models with cylindrical afterbodies were analyzed for a flow at a Mach number of 10 corresponding to the standard atmospheric conditions at an altitude of 50 km. The nose radii of curvature of the models range from a hemispherical nose to a flat nose. Appropriate numerical models and the supplementary convergence techniques that were implemented for the CFD analysis are thoroughly described. The flow contours are presented highlighting the key characteristics of shock wave shape, shock standoff distance and the sonic point shift on the shock. The variation of heat flux, due to different shock detachments for various models is comprehensively discussed. It is observed that the more the bluntness of the nose radii, the farther the shock stands from the body; and consequently, the less the surface heating at the nose. The results obtained from the CFD analyses are compared with approximated theoretical engineering correlations. Overall, a satisfactory agreement is observed between the two.

Keywords: aero-thermodynamics, blunt-nosed bodies, computational fluid dynamics (CFD), hypersonic flow

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Authors: Minh Quang Le, Dane Taylor

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Convection is a well-studied topic in fluid dynamics, yet it is less understood in the context of networks flows. Here, we incorporate techniques from topological data analysis (namely, persistent homology) to automate the detection and characterization of convective/cyclic/chiral flows over networks, particularly those that arise for irreversible Markov chains (MCs). As two applications, we study convection cycles arising under the PageRank algorithm, and we investigate chiral edges flows for a stochastic model of a bi-monomer's configuration dynamics. Our experiments highlight how system parameters---e.g., the teleportation rate for PageRank and the transition rates of external and internal state changes for a monomer---can act as homology regularizers of convection, which we summarize with persistence barcodes and homological bifurcation diagrams. Our approach establishes a new connection between the study of convection cycles and homology, the branch of mathematics that formally studies cycles, which has diverse potential applications throughout the sciences and engineering.

Keywords: homology, persistent homolgy, markov chains, convection cycles, filtration

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Authors: Alix Limoges, William Bruch, Christophe Yohia, Jacques Piazzola

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A number of questions arise concerning the long-term impact of the contribution of marine aerosol fluxes generated at the air-sea interface on the occurrence of intense events (storms, floods, etc.) in the coastal environment. To this end, knowledge is needed on sea-spray emission rates and the atmospheric dynamics of the corresponding particles. Our aim is to implement the mesoscale model MESO-NH on the study area using an accurate sea-spray source function to estimate heat fluxes and impact on the precipitations. Based on an original and complete sea-spray source function, which covers a large size spectrum since taking into consideration the sea-spray produced by both bubble bursting and surface tearing process, we propose a comparison between model simulations and experimental data obtained during an oceanic scientific cruise on board the navy ship Atalante. The results show the relevance of the sea-spray flux calculations as well as their impact on the heat fluxes and AOD.

Keywords: atmospheric models, sea-spray source, sea-spray dynamics, aerosols

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Authors: M. Şimşek

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Additive manufacturing (AM) or generally known as three dimensional (3D) printing provides great opportunities for both civilian and military applications by which 3D has become the biggest nominee of breakthrough of 21th century. When properly used, it has a wide spectrum of applications that make production easier and more profitable. Considering the advantages of AM, every firm has an intention of catching up with this new trend. As well as reducing costs and thus increasing benefits, 3D printing provides opportunities for national armies by reducing maintenance and repair time and increasing operational readiness.

Keywords: additive manufacturing, operational cost, operational readiness, supply chain, three dimensional printing

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Authors: N. G. Thangan, A. B. Deoghare, P. M. Padole

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Computational Fluid Dynamics (CFD) aids in modeling the prototype of a real world processes. CFD approach is useful in predicting the fluid flow, heat transfer mass transfer and other flow related phenomenon. In present study, hydrodynamic characteristics of gas-solid cylindrical fluidized bed is compared with conical fluidized beds. A 2D fluidized bed consists of different configurations of particle size of iron oxide, bed height and superficial velocities of nitrogen. Simulations are performed to capture the complex physics associated with it. The Eulerian multiphase model is prepared in ANSYS FLUENT v.14 which is used to simulate fluidization process. It is analyzed with nitrogen as primary phase and iron oxide as secondary phase. The bed hydrodynamics is assessed prominently to examine effect on fluidization time, pressure drop, minimum fluidization velocity, and gas holdup in the system.

Keywords: fluidized bed, bed hydrodynamics, Eulerian multiphase approach, computational fluid dynamics

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Authors: Nigar Kantarci Carsibasi

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Coarse-grained elastic network models, namely Gaussian network model (GNM) and Anisotropic network model (ANM), are utilized in order to investigate the fluctuation dynamics of Murine Double Minute 2 (MDM2), which is the native inhibitor of p53. Conformational dynamics of MDM2 are elucidated in unbound, p53 bound, and non-peptide small molecule inhibitor bound forms. With this, it is aimed to gain insights about the alterations brought to global dynamics of MDM2 by native peptide inhibitor p53, and two small molecule inhibitors (HDM201 and NVP-CGM097) that are undergoing clinical stages in cancer studies. MDM2 undergoes significant conformational changes upon inhibitor binding, carrying pieces of evidence of induced-fit mechanism. Small molecule inhibitors examined in this work exhibit similar fluctuation dynamics and characteristic mode shapes with p53 when complexed with MDM2, which would shed light on the design of novel small molecule inhibitors for cancer therapy. The results showed that residues Phe 19, Trp 23, Leu 26 reside in the minima of slowest modes of p53, pointing to the accepted three-finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct regions are identified in MDM2, for which significant conformational changes are observed upon binding. Regions I (residues 50-77) and III (residues 90-105) correspond to the binding interface of MDM2, including (α2, L2, and α4), which are stabilized during complex formation. Region II (residues 77-90) exhibits a large amplitude motion, being highly flexible, both in the absence and presence of p53 or other inhibitors. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 domains, clearly distinguishing the kinetically hot regions. Mode shape analysis revealed that the α4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states for proper penetration and binding of p53 and inhibitors, which points to the induced-fit mechanism of p53 binding. P53 interacts with α2 and α4 in a synchronized manner. Collective modes are shifted upon inhibitor binding, i.e., second mode characteristic motion in MDM2-p53 complex is observed in the first mode of apo MDM2; however, apo and bound MDM2 exhibits similar features in the softest modes pointing to pre-existing modes facilitating the ligand binding. Although much higher amplitude motions are attained in the presence of non-peptide small molecule inhibitor molecules as compared to p53, they demonstrate close similarity. Hence, NVP-CGM097 and HDM201 succeed in mimicking the p53 behavior well. Elucidating how drug candidates alter the MDM2 global and conformational dynamics would shed light on the rational design of novel anticancer drugs.

Keywords: cancer, drug design, elastic network model, MDM2

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Authors: Sara Dehaiman Alqahtani

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This study investigates the effects of cybersecurity breaches on critical audit outcomes, specifically focusing on auditor changes, engagement partner rotations, and the issuance of going concern opinions. Utilizing an extensive dataset of U.S.-based firms spanning from 2006 to 2023, the research employs propensity score matching (PSM) to address selection bias and control for confounding variables. The analysis reveals that, contrary to conventional expectations, firms that experience cybersecurity breaches are less likely to change their audit firms and engagement partners. Additionally, these breached firms are less likely to receive going concern opinions from their auditors. However, an exception is noted within the technology sector, where breached firms show a higher propensity to switch auditors, potentially to demonstrate a commitment to enhanced cybersecurity measures. The findings suggest a strong preference for continuity in auditor-client relationships following cybersecurity incidents. This preference underscores the importance of auditors' existing knowledge of a firm's systems and controls, which is deemed valuable during periods of heightened risk. The study extends the existing literature by moving beyond the well-documented impact of breaches on audit fees to explore other significant dimensions of the auditor-client relationship. It challenges the traditional assumption that increased risk from breaches leads to higher auditor turnover or more conservative audit opinions, highlighting instead a tendency towards maintaining stability. Methodologically, the research leverages PSM to create a balanced comparison between breached and non-breached firms, ensuring robustness in the findings. Logistic regression analyses further substantiate the associations between breaches and audit outcomes, controlling for various firm-specific characteristics such as size, financial performance, and industry classification. Supplemental analyses explore additional factors, including litigation risk, breach frequency, and industry-specific responses, providing a nuanced understanding of the dynamics at play. The study’s main contributions are threefold. First, it broadens the scope of research on cybersecurity breaches by examining their impact on auditor changes and going concern opinions, areas previously underexplored. Second, it offers empirical evidence that breached firms tend to retain their auditors and engagement partners, suggesting that continuity is valued over potential audit quality improvements through auditor changes. Third, it highlights sector-specific behaviors, particularly within the technology industry, where breaches do lead to higher auditor turnover, indicating industry-specific risk management strategies. Implications of this research are significant for auditors, clients, and regulators. Auditors may need to enhance their risk assessment frameworks to better incorporate cybersecurity risks, ensuring that audit practices remain robust in the face of evolving cyber threats. Clients should evaluate the benefits of retaining existing auditors against the potential advantages of engaging new auditors who might offer fresh perspectives and specialized cybersecurity expertise. Regulators might consider updating auditing standards to more explicitly address cybersecurity risks, ensuring that such threats are adequately reflected in audit procedures and disclosures. Overall, this study provides a comprehensive analysis of how cybersecurity breaches influence audit outcomes, revealing a preference for auditor continuity and questioning whether current auditing frameworks sufficiently account for cyber risks. By highlighting these trends, the research calls for a reassessment of audit practices and regulatory standards to better address the complexities introduced by the increasing prevalence of cyber threats in the digital age.

Keywords: cybersecurity breaches, auditor changes, engagement partner rotations, going concern opinions, auditor-client relationships, audit risk assessment

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Authors: Virendra Nath, Vipin Kumar

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Background: TypeII Diabetes mellitus is a foremost health problem worldwide, predisposing to increased mortality and morbidity. Undesirable effects of the current medications have prompted the researcher to develop more potential drug(s) against the disease. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptors family and take part in a vital role in the regulation of metabolic equilibrium. They can induce or repress genes associated with adipogenesis, lipid, and glucose metabolism. Aims: Investigation of PPARα/γ agonistic hits were screened by hierarchical virtual screening followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) analysis using approved PPAR α/γ dual agonist. Methods: The PPARα/γ agonistic activity of compounds was searched by using Maestro through structure-based virtual screening and molecular dynamics (MD) simulation application. Virtual screening of nuclear-receptor ligands was done, and the binding modes with protein-ligand interactions of newer entity(s) were investigated. Further, binding energy prediction, Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit along with the structural comparative analysis of approved PPARα/γ agonists with screened hit was done for knowledge-based SAR. Results and Discussion: The silicone chip-based approach recognized the most capable nine hits and had better predictive binding energy as compared to the reference drug compound (Tesaglitazar). In this study, the key amino acid residues of binding pockets of both targets PPARα/γ were acknowledged as essential and were found to be associated in the key interactions with the most potential dual hit (ChemDiv-3269-0443). Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit and found root mean square deviation (RMSD) stabile around 2Å and 2.1Å, respectively. Frequency distribution data also revealed that the key residues of both proteins showed maximum contacts with a potent hit during the MD simulation of 20 nanoseconds (ns). The knowledge-based SAR studies of PPARα/γ agonists were studied using 2D structures of approved drugs like aleglitazar, tesaglitazar, etc. for successful designing and synthesis of compounds PPARγ agonistic candidates with anti-hyperlipidimic potential.

Keywords: computational, diabetes, PPAR, simulation

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Authors: Khushi, Simrat

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The study aims to investigate the relationship between emotions and employee's social cognition and decision-making among employees. The sample of the study was the total number of participants, which included employees from various industries and job positions. Research papers in the same area were reviewed, providing a comprehensive review of existing literature and theoretical frameworks and shedding light on the interpersonal effects of emotions in the workplace. It emphasizes how one worker's emotions can significantly impact the overall work environment and productivity as well as the work of a common phenomenon known as Emotional contagion at the workplace, affecting social interactions and group dynamics. Therefore, this study concludes that Emotional contagion can lead to a ripple effect within the workplace, influencing the overall atmosphere and productivity. Emotions can shape how employees process information and make choices, ultimately impacting organizational outcomes.

Keywords: employee decision making, social cognition, emotions, industry, emotional contagion, workplace dynamics

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Authors: Pawel Skruch, Marek Dlugosz

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The paper starts with a general model of the temperature dynamics in buildings. The modelling approach relies on thermodynamics, in particular heat transfer, principles. The model considers heat loses by conduction and ventilation and internal heat gains. The parameters of the model can be determined uniquely from the geometry of the building and from thermal properties of construction materials. The model is presented using state space notation and this form is used in the control design procedure. A sliding surface is defined by the system output and the desired trajectory. The control law is designed to force the trajectory of the system from any initial condition to the sliding surface in finite time. The trajectory of the system after reaching the sliding surface remains on it. A simulation example is included to verify the approach and to demonstrate the achievable performance improvement by the proposed solution in the temperature control in buildings.

Keywords: modelling, building, temperature dynamics, sliding-mode control, sliding surface

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Authors: Tivani Phosa Mashamba-Thompson, Mahmoud E. S. Soliman

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To date, the cause of neurodegeneration is not well understood and diseases that stem from neurodegeneration currently have no known cures. Cathepsin B (CB) enzyme is known to be involved in the production of peptide neurotransmitters and toxic peptides in neurodegenerative diseases (NDs). CA-074Me is a membrane-permeable irreversible selective cathepsin B (CB) inhibitor as confirmed by in vivo studies. Due to the lack of the crystal structure, the binding mode of CA-074Me with the human CB at molecular level has not been previously reported. The main aim of this study is to gain an insight into the binding mode of CB CA-074Me to human CB using various computational tools. Herein, molecular dynamics simulations, binding free energy calculations and per-residue energy decomposition analysis were employed to accomplish the aim of the study. Another objective was to identify novel CB inhibitors based on the structure of CA-074Me using fragment based drug design using scaffold hoping drug design approach. Results showed that two of the designed ligands (hit 1 and hit 2) were found to have better binding affinities than the prototype inhibitor, CA-074Me, by ~2-3 kcal/mol. Per-residue energy decomposition showed that amino acid residues Cys29, Gly196, His197 and Val174 contributed the most towards the binding. The Van der Waals binding forces were found to be the major component of the binding interactions. The findings of this study should assist medicinal chemist towards the design of potential irreversible CB inhibitors.

Keywords: cathepsin B, scaffold hopping, docking, molecular dynamics, binding-free energy, neurodegerative diseases

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Authors: Bello Gonzalez, Setten Van M., Brouwer M.

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The chicken small intestine represents a dynamic and complex organ in which the enzymatic digestion and absorption of nutrients take place. The development of an in vitro fermentation chicken small intestinal model could be used as an alternative to explore the interaction between the microbiota and nutrient metabolism and to enhance the efficacy of targeting interventions to improve animal health. In the present study we have developed an in vitro fermentation chicken ileum microbiota model for unrevealing the complex interaction of ileum microbial community under physiological conditions. A two-vessel continuous fermentation process simulating in real-time the physiological conditions of the ileum content (pH, temperature, microaerophilic/anoxic conditions, and peristaltic movements) has been standardized as a proof of concept. As inoculum, we use a pool of ileum microbial community obtained from chicken broilers at the age of day 14. The development and validation of the model provide insight into the initial characterization of the ileum microbial community and its dynamics over time-related to nutrient assimilation and fermentation. Samples can be collected at different time points and can be used to determine the microbial compositional structure, dynamics, and diversity over time. The results of studies using this in vitro model will serve as the foundation for the development of a whole small intestine in vitro fermentation chicken gastrointestinal model to complement our already established in vitro fermentation chicken caeca model. The insight gained from this model could provide us with some information about the nutritional strategies to restore and maintain chicken gut homeostasis. Moreover, the in vitro fermentation model will also allow us to study relationships between gut microbiota composition and its dynamics over time associated with nutrients, antimicrobial compounds, and disease modelling.

Keywords: broilers, in vitro model, ileum microbiota, fermentation

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Authors: Shuenn-Yih Chang, Chiu-Li Huang

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Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Keywords: dynamic analysis, high frequency, integration method, overshoot, weak instability

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: K. G. R. M. Jayathilake, S. Rudra

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Wood degradation in hot compressed water is modeled with a Computational Fluid Dynamics (CFD) code using cellulose, xylan, and lignin as model compounds. Model compounds are reacted under catalyst-free conditions in a temperature range from 250 to 370 °C. Using a simplified reaction scheme where water soluble products, methanol soluble products, char like compounds and gas are generated through intermediates with each model compound. A modified multistage shrinking core model is developed to simulate particle degradation. In the modified shrinking core model, each model compound is hydrolyzed in separate stages. Cellulose is decomposed to glucose/oligomers before producing degradation products. Xylan is decomposed through xylose and then to degradation products where lignin is decomposed into soluble products before producing the total guaiacol, organic carbon (TOC) and then char and gas. Hydrolysis of each model compound is used as the main reaction of the process. Diffusion of water monomers to the particle surface to initiate hydrolysis and dissolution of the products in water is given importance during the modeling process. In the developed model the temperature variation depends on the Arrhenius relationship. Kinetic parameters from the literature are used for the mathematical model. Meanwhile, limited initial fast reaction kinetic data limit the development of more accurate CFD models. Liquefaction results of the CFD model are analyzed and validated using the experimental data available in the literature where it shows reasonable agreement.

Keywords: computational fluid dynamics, liquefaction, shrinking-core, wood

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Authors: Afia Naheed, Manmohan Singh, David Lucy

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This work is based on a mathematical as well as statistical study of an SEIJTR deterministic model for the interpretation of transmission of severe acute respiratory syndrome (SARS). Based on the SARS epidemic in 2003, the parameters are estimated using Runge-Kutta (Dormand-Prince pairs) and least squares methods. Possible graphical and numerical techniques are used to validate the estimates. Then effect of the model parameters on the dynamics of the disease is examined using sensitivity and uncertainty analysis. Sensitivity and uncertainty analytical techniques are used in order to analyze the affect of the uncertainty in the obtained parameter estimates and to determine which parameters have the largest impact on controlling the disease dynamics.

Keywords: infectious disease, severe acute respiratory syndrome (SARS), parameter estimation, sensitivity analysis, uncertainty analysis, Runge-Kutta methods, Levenberg-Marquardt method

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Authors: Anvar Atayev, Karl Steinborn, Aleksander Lovric, Saif Al-Ibadi, Jorg Fliege

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In this paper, we present results obtained from optimising the aerodynamic performance of aerostructures in external ow. The optimisation method used was developed to efficiently handle multi-variable problems with numerous black-box objective functions and constraints. To demonstrate these capabilities, a series of CFD problems were considered; (1) a two-dimensional NACA aerofoil with three variables, (2) a two-dimensional morphing aerofoil with 17 variables, and (3) a three-dimensional morphing aeroplane tail with 33 variables. The objective functions considered were related to combinations of the mean aerodynamic coefficients, as well as their relative variations/oscillations. It was observed that for each CFD problem, an improved objective value was found. Notably, the scale-up in variables for the latter problems did not greatly hinder optimisation performance. This makes the method promising for scaled-up CFD problems, which require considerable computational resources.

Keywords: computational fluid dynamics, optimisation algorithms, aerodynamic design, engineering design

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Authors: M. J. Uddin, M. M. Rahman

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Transient natural convective flow dynamics of nanofluids in a horizontal homocentric annulus using nonhomogeneous dynamic model has been experimented numerically. The simulation is carried out for four different shapes of the inner wall, which is either cylindrical, elliptical, square or triangular. The outer surface of the annulus is maintained at constant low temperature while the inner wall is maintained at a uniform temperature; higher than the outer one. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic deposition phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To find the best performer, the local Nusselt number is demonstrated for different shapes of the inner wall. The heat transfer enhancement for different nanofluids for four different shapes of the inner wall is exhibited.

Keywords: nanofluids, annulus, nonhomogeneous dynamic model, heat transfer

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Authors: Ramazan Kadiev, Arkadi Ponossov

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Semidiscrete systems contain both continuous and discrete components. This means that the dynamics is mostly continuous, but at certain instants, it is exposed to abrupt influences. Such systems naturally appear in applications, for example, in biological and ecological models as well as in the control theory. Therefore, the study of semidiscrete systems has recently attracted the attention of many specialists. Stochastic effects are an important part of any realistic approach to modeling. For example, stochasticity arises in the population dynamics, demographic and ecological due to a change in time of factors external to the system affecting the survival of the population. In control theory, random coefficients can simulate inaccuracies in measurements. It will be shown in the presentation how to incorporate such effects into semidiscrete systems. Stability analysis is an essential part of modeling real-world problems. In the presentation, it will be explained how sufficient conditions for the moment stability of solutions in terms of the coefficients for linear semidiscrete stochastic equations can be derived using non-Lyapunov technique.

Keywords: abrupt changes, exponential stability, regularization, stochastic noises

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Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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Authors: Abdous Noureddine

Abstract:

The problem of funding in Algeria emerged as a problem you need to study after many Algerians researchers pointed out that the faltering Algerian public economic institution due to the imbalance in the financial structures and lower steering and marketing efficiency, as well as a result of severe expansion of borrowing because of inadequate own resources, and the consequent inability This institution to repay loans and interest payments, in addition to increasing reliance on overdraft so used to finance fixed assets, no doubt that this deterioration requires research and study of the causes and aspects of treatment, which addresses the current study, aside from it.

Keywords: financial structure, financial capital, equity, debt, firm’s value, return, leverage

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Authors: Oleg Oborin

Abstract:

This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: Javier Navarro Garcia, Narciso Vazquez Carretero

Abstract:

Eurocode 1, part 1-4, wind actions, includes in its article 1.5 the possibility of using numerical calculation methods to obtain information on the loads acting on a building. On the other hand, the analysis using computational fluids dynamics (CFD) in aerospace, aeronautical, and industrial applications is already in widespread use. The application of techniques based on CFD analysis on the building to study its aerodynamic behavior now opens a whole alternative field of possibilities for civil engineering and architecture; optimization of the results with respect to those obtained by applying the regulations, the possibility of obtaining information on pressures, speeds at any point of the model for each moment, the analysis of turbulence and the possibility of modeling any geometry or configuration. The present work compares the results obtained on a building, with respect to its aerodynamic behavior, from a mathematical model based on the analysis by CFD with the results obtained by applying Eurocode1, part1-4, wind actions. It is verified that the results obtained by CFD techniques suppose an optimization of the wind action that acts on the building with respect to the wind action obtained by applying the Eurocode1, part 1-4, wind actions. In order to carry out this verification, a 45m high square base truncated pyramid building has been taken. The mathematical model on CFD, based on finite volumes, has been calculated using the FLUENT commercial computer application using a scale-resolving simulation (SRS) type large eddy simulation (LES) turbulence model for an atmospheric boundary layer wind with turbulent component in the direction of the flow.

Keywords: aerodynamic, CFD, computacional fluids dynamics, computational mechanics

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Authors: Iftekhar Hassan, Sayedil Morsalin, Easir A Khan

Abstract:

Accidents involving fire occur frequently in recent times and their causes showing a great deal of variety which require intervention methods and risk assessment strategies are unique in each case. On September 4, 2020, a fire and explosion occurred in a confined space caused by a methane gas leak from an underground pipeline in Baitus Salat Jame mosque during Night (Esha) prayer in Narayanganj District, Bangladesh that killed 34 people. In this research, this incident is simulated using Fire Dynamics Simulator (FDS) software to analyze and understand the nature of the accident and associated consequences. FDS is an advanced computational fluid dynamics (CFD) system of fire-driven fluid flow which solves numerically a large eddy simulation form of the Navier–Stokes’s equations for simulation of the fire and smoke spread and prediction of thermal radiation, toxic substances concentrations and other relevant parameters of fire. This study focuses on understanding the nature of the fire and consequence evaluation due to thermal radiation caused by vapor cloud explosion. An evacuation modeling was constructed to visualize the effect of evacuation time and fractional effective dose (FED) for different types of agents. The results were presented by 3D animation, sliced pictures and graphical representation to understand fire hazards caused by thermal radiation or smoke due to vapor cloud explosion. This study will help to design and develop appropriate respond strategy for preventing similar accidents.

Keywords: consequence modeling, fire and explosion, fire dynamics simulation (FDS), thermal radiation

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Authors: Dany Ng Cheong Vee, Preethee Nunkoo Gonpot, Noor Sookia

Abstract:

In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that 'fat-tailedness' alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.

Keywords: extreme value theory, financial crisis 2008, value at risk, frontier markets

Procedia PDF Downloads 276