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A lime–sand pile is a three-phase particle composite material composed of a lime matrix, sand, and a loess aggregate at the meso level. Establishing a random aggregate model that can reflect the actual aggregate gradation, content, and morphology is the premise of numerical simulations of the meso-mechanics of lime–sand piles. In this paper, the secondary development of Abaqus 2022 is realized by writing Python 3.12 scripts, and a parameterized three-phase mixed lime–sand pile random meso-spherical aggregate model is obtained. A meso-modeling idea of lime–sand piles is creatively proposed, the integrated-generation algorithm of a spherical aggregate of different materials is written, and the material's properties and mesh generation are given by the algorithm. Finally, a numerical simulation of temperature–expansion statics is carried out using an established mesoscopic model. Under different mixing ratios, the expansion force increases with an increase in the lime proportion. The increase in the expansion force is approximately 45% of that without an increased lime proportion. The simulated expansion forces are 8.81 kN, 12.61 kN, and 18.89 kN, respectively, which are similar to the experimental results for laboratory specimens, and the relative error is less than 3%. In the case of different height ratios, with increases in height, the change in the expansion force is very small, and the relative error between the simulated value and the experimental value is less than 2%, which further verifies the reliability of the mesoscopic random model of lime–sand piles. The model can be used to guide the practical application of engineering. [ABSTRACT FROM AUTHOR]

Time-domain numerical simulation is generally considered an accurate method to predict the mooring system performance, but it is also time and resource-consuming. This paper attempts to completely replace the time-domain numerical simulation with machine learning approaches, using a catenary anchor leg mooring (CALM) system design as an example. An adaptive sampling method is proposed to determine the dataset of various parameters in the CALM mooring system in order to train and validate the generated machine learning models. Reasonable prediction accuracy is achieved by the five assessed machine learning algorithms, namely random forest, extremely randomized trees, K-nearest neighbor, decision tree, and gradient boosting decision tree, among which random forest is found to perform the best if the sampling density is high enough. [ABSTRACT FROM AUTHOR]

This paper takes a tunnel through a landslide in Northwest China as an example, constructs a mechanical model of a tunnel–landslide orthogonal system, and explores the deformation mechanism of a tunnel–landslide system and the technology of early warnings of near-slips. Given the problem that it is difficult to accurately monitor the deformation and damage characteristics of the tunnel–landslide system using conventional methods, FLAC3D was used to analyze the deformation mechanism of the tunnel–landslide orthogonal system and numerical simulation of the NPR constant resistance large deformation anchors for the early warning of near-slips. Based on the strength reduction method, by reducing the mechanical parameters of the shear strength of the slip zone and simulating different degrees of landslides, we obtained the change rules of the displacement and the axial force of the NPR constant-resistance large deformation anchor cable in the tunnel–landslide orthogonal system, established the warning mode of the Newtonian force tunnel–landslide orthogonal system, and successfully issued a near-slip warning in actual engineering applications. The above research is of great significance to the stability monitoring and risk assessment of tunnel–landslide systems. [ABSTRACT FROM AUTHOR]

In this paper, we consider a mathematical model which describes the equilibrium of two elastic rods attached to a nonlinear spring. We derive the variational formulation of the model which is in the form of an elliptic quasivariational inequality for the displacement field. We prove the unique weak solvability of the problem, then we state and prove some convergence results, for which we provide the corresponding mechanical interpretation. Next, we turn to the numerical approximation of the problem based on a finite element scheme. We use a relaxation method to solve the discrete problems that we implement on the computer. Using this method, we provide numerical simulations which validate our convergence results. [ABSTRACT FROM AUTHOR]

Numerical simulations consist of many components that affect the simulation accuracy and the required computational resources. However, finding an optimal combination of components and their parameters under constraints can be a difficult, time-consuming and often manual process. Classical adaptivity does not fully solve the problem, as it comes with significant implementation cost and is difficult to expand to multi-dimensional parameter spaces. Also, many existing data-based optimization approaches treat the optimization problem as a black-box, thus requiring a large amount of data. We present a constrained, model-based Bayesian optimization approach that avoids black-box models by leveraging existing knowledge about the simulation components and properties of the simulation behavior. The main focus of this paper is on the stochastic modeling ansatz for simulation error and run time as optimization objective and constraint, respectively. To account for data covering multiple orders of magnitude, our approach operates on a logarithmic scale. The models use a priori knowledge of the simulation components such as convergence orders and run time estimates. Together with suitable priors for the model parameters, the model is able to make accurate predictions of the simulation behavior. Reliably modeling the simulation behavior yields a fast optimization procedure because it enables the optimizer to quickly indicate promising parameter values. We test our approach experimentally using the multi-scale muscle simulation framework OpenDiHu and show that we successfully optimize the time step widths in a time splitting approach in terms of minimizing the overall error under run time constraints. [ABSTRACT FROM AUTHOR]

The phenomenon of a hollow droplet impacting on a solid surface is widely found in various fields. The dynamic characteristics of hollow diesel droplets impacting on a solid surface are studied by combining numerical simulation and theoretical analysis. The dynamic contact angle model presented in this paper couples the advantages of existing dynamic contact angle models for simulating both the spreading and retracting stages. It also considers the continuous variation of the contact angle during the maximum spreading state. Compared to existing models, the maximum error has been reduced from 14.9% to 4.6%. The effects of impact velocity, impact angle, and volume ratio of a hollow droplet on the spreading and jetting characteristics are investigated by three-dimensional numerical simulations. It is found that air entrainment occurred in the counter-jet, and the presence of the impact angle increased the asymmetry of the counter-jet and spreading liquid film, promoting fingerlike splashing at the front liquid film. Based on energy conservation law, the theoretical prediction models of the maximum spreading coefficient of the hollow droplet impacting on the surface and the velocity of the counter-jet at the maximum spreading state are established using the multi-regional modeling method and the energy distribution principle. Compared with existing hollow droplet theoretical models, the proposed theoretical models exhibit a more concise expression, higher accuracy, and wider applicability range. [ABSTRACT FROM AUTHOR]

In this paper, we present a hybrid intelligent simulation system for optimization of mesh routers in Wireless Mesh Networks (WMNs) called WMN-PSOHCDGA. We implemented six mesh router replacement methods: CM, RIWM, LDIWM, LDVM, RDVM and FC-RDVM and consider Two Islands distribution of mesh clients. We carry out a comparison study of these router replacement methods for small and middle scale WMNs. We assessed the performance by computer simulations. The simulation results show that six methods have a good performance for connectivity and coverage metrics, for both small and middle scale WMNs. However, they have different behavior for load balancing. For small scale WMNs, the load balancing of LDIWM, RIWM and FC-RDVM is better than CM, LDVM and RDVM. While, comparing LDIWM, RIWM and FC-RDVM, the LDIWM has better load balancing. We found that the load balancing for small scale WMNs is not good, because there is a concentration of mesh routers in some areas. For middle scale WMNs, the CM, LDIWM, LDVM and RDVM have not a good load balancing. While, the RIWM and FC-RDVM have better performance. Comparing RIWM and FC-RDVM, we found that the load balancing of FC-RDVM is better than RIWM. [ABSTRACT FROM AUTHOR]

The present paper deals with the photovoltaic performance‐based numerical evaluation of copper–zinc–tin–sulfur (CZTS) solar cells embedded with CZTSe as a back surface field (BSF) layer. CZTS has been considered a leading candidate for the fabrication of solar devices owing to its availability and absence of toxicity. Adding a BSF layer to a solar device is a novel way to boost efficiency. It reduces the recombination of the carriers at the back surface, thus increasing the overall current output of the solar cells. SCAPS 1D simulator is used to study the impact of several parameters on electrical properties like temperature, the thickness of the CZTS layer, acceptor doping concentration, and the impact of series and shunt resistances. Considering the optimized parameters in each layer of the solar cells, this work delivers 24.7% efficiency with the BSF layer, which is 8% more than that without the BSF layer. The results of this modeling will facilitate researchers to fabricate a highly efficient CZTS solar cell. [ABSTRACT FROM AUTHOR]

This paper presents a novel 2D analytical model for investigating the influence of the ferroelectric dielectric on the performance of pocket doped double gate tunnel FET. It takes into account the effect of the gate and drain voltages, the thickness of the gate insulator, the capacitance of the gate insulator, and source and drain depletions. The surface potential thus carefully obtained is utilized for calculating lateral electric field, drain current, gate‐to‐drain capacitance, and transconductance. As a result, it has been demonstrated that the result of our model with several device structures matches very well with the data obtained through the technology computer‐aided design (TCAD) simulation. In addition, it has also been shown that the proposed tunnel field‐effect transistors (TFET) structure, which incorporates the ferroelectric dielectric and SiGe/Si heterostructure, has the best ON current, ON/OFF ratio, transconductance, and cut‐off frequency (fT). [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research paper investigates the numerical solutions of the predator–prey model through five recent numerical schemes (Adomian decomposition, El Kalla, cubic B‐spline, extended cubic B‐spline, exponential cubic B‐spline). We investigate the obtained computational solutions via the modified Khater methods. This model is considered as a well‐known bimathematical model to describe the prototype of an excitable system. The obtained solitary solutions emerge the localized wave packet as a persistent and dominant feature. The accuracy of the obtained numerical solutions is investigated by calculating the absolute error between the exact and numerical solutions. Many sketches are given to illustrate the matching between the exact and numerical solutions. [ABSTRACT FROM AUTHOR]

A new simulation model for the development of gas condensate reservoirs is introduced based on the influence that phase change, non-Darcy flow, and capillary pressure have on the production of gas condensates. The model predicts well performance, including bottom-hole pressure, oil/gas production rate, oil/gas recovery, gaseoil ratio, and the change in produced fluid composition. It also calculates dynamic characters, such as the change of pressure field and oil/gas saturation field during the development of gas condensate reservoirs. The model is applicable to different boundary conditions (both constant-pressure and sealed boundary) and different production modes (both constant-pressure and constant-volume production modes). Model validation attempted using numerical simulation results for sealed boundary conditions with constant-pressure production mode has shown a relatively good match, proving its validity. For constant-pressure boundary conditions with constant-volume production mode, four stages are defined according to the dynamic behavior of production performance in the development of gas condensate reservoirs. [ABSTRACT FROM AUTHOR]

A system of diffusion–reaction equations coupled with a dissolution–precipitation model is discussed in this paper. We start by introducing a microscale model together with its homogenized version. In the present paper, we first derive the corrector results to justify the obtained theoretical results. Furthermore, we perform the numerical simulations to compare the outcome of the effective (homogenized) model with the original heterogeneous microscale model. [ABSTRACT FROM AUTHOR]

In this paper, a novel numerical simulation approach based on the finite element method for dynamically modeling the excavation process of shield tunneling is proposed, with the shield-ground interactions well captured. This method is capable of mimicking the alternating modes of advancing and stopping of a shield boring machine during underground construction, with the important effects of the cutterhead rotation and slurry support pressure considered. Under the cutting action, the soil at the excavation face would experience irreversible deformation and damage, such that additional support needs to be provided by the cutterhead blades and slurry to maintain stability. The impacts of key construction parameters are examined, including cutterhead rotary speed, advance rate, and slurry support pressure, on shield tunneling operations and ground responses. The numerical model is rigorously validated against physical model experiments. This work provides useful insights into the mechanistic processes in the stratum during shield tunneling, including the spatiotemporal evolution of ground deformation patterns and stress redistributions. The results offer valuable guidance for optimizing shield tunneling operations and enhancing tunneling safety and efficiency. [ABSTRACT FROM AUTHOR]

This paper aims to improve existing models for drag, lift, and pitching torque coefficients of cylindrical disc particles with a wider range of aspect ratios and particle Reynolds numbers. The full body-fitted direct numerical simulations (DNS) are carried out for three-dimensional flow past cylindrical discs in order to quantify the coefficients at aspect ratios from 0.2 to 0.6, incidence angles from 0°to 90°, and Reynolds numbers from 0.1 to 300. The CFD results are validated against the aerodynamic coefficients of both spherical and non-spherical particles presented in the literature. A full set of new correlations for the coefficients, dependent on aspect ratio, incidence angle, and Reynolds number, is further derived according to the CFD predicted data. The results show that the new correlations have a promising performance for the disc particles considered in this study. [Display omitted] • CFD simulations are performed for drag, lift, and pitching torque coefficients. • A complete set of correlations for C D , C L , and C T is proposed. • Proposed correlations work well outside the Stokes regime. • The correlation predictions agree with the CFD simulations. [ABSTRACT FROM AUTHOR]

In this work, a multispectral aptasensor structure, including a sub-layer and two side walls, was presented. The cells are positioned at the down and top of the structure, with the down cells oriented perpendicular to the walls and the top cells aligned parallel to the walls. The validity of the findings was verified by the utilization of a numerical simulation technique known as 3D Finite Difference Time Domain (FDTD). The biosensor under consideration exhibits sensitivities of 1093.7 nm/RIU, 754 nm/RIU, and 707.43 nm/RIU in mode III, mode II, and mode I, respectively. In the majority of instances, the quantity of analyte available is insufficient to coat the surface of the sensor thoroughly. Consequently, in this study, the evaluation of surface sensitivity was undertaken alongside bulk sensitivity. The surface sensitivity of the suggested structure for mode II in the sensor layer, with thicknesses of 10, 20, 30, and 70 nm, is measured to be 25, 78, 344, and 717.636 nm/RIU, respectively. Our design incorporates a unique arrangement of sub-layer and side walls, with cells positioned to maximize interaction with the target analyte. This innovative configuration, combined with Ag for its superior plasmonic properties, enables the detection of E. coli O157 with remarkable sensitivity. [ABSTRACT FROM AUTHOR]

Background: Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. Methods: A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. Results: The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. Conclusions: The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management. [ABSTRACT FROM AUTHOR]

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in the scientific literature based on various approaches, tools, and techniques. The present study proposes a new approach to numerical modeling and simulation based on the Holm contact theory, aiming to study the dependence between the electric potential and the temperature within an electrical contact. Structured in five sections, the research was conducted using COMSOL Multiphysics software (version 5.3) and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, electric field amplitude, variation of the electrical potential along the current path, temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation, and are graphically represented. The results show that the temperature increase follows a parabolic curve, and that for values higher than 4 mV of voltage drop, the temperature of the contact increases to 79.25 degrees (and up to 123.81 degrees for 5 mV) over the ambient temperature, thus the integrity of insulation can be compromised. These values are close (10–12%) to the analytically calculated ones, and also in line with research assessed in the literature review. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic behavior of a Van der Pol oscillator (used as an archetypal self-sustained oscillator) coupled to a bistable nonlinear energy sink (BNES). We first show using numerical simulations that this system can undergo a multitude of motions including different types of periodic regimes and so-called strongly modulated responses (SMR) as well as chaotic regimes. We also show that a BNES can be much more efficient than a classical cubic NES but this is not robust since a little perturbation can switch the system from harmless to harmful situations. However, even in the most unfavorable cases, it is possible to find a set of parameters for which the BNES performs better than the NES. A multiple time scales approach is then addressed to analyze the system. In this context, we show that the so-called Multiple Scale/Harmonic Balance Method (MSHBM) must be modified (compared to its usual use) to consider the specific feature of the BNES, i.e., that it can have a nonzero-mean oscillating motion. This allows us to derive a so-called amplitude-phase modulation dynamics (APMD) which can reproduce the complex behavior of the initial system. Because of the presence of a small perturbation parameter (i.e., the mass ratio between the BNES and the VdP oscillator), the APMD is governed by two different time scales. More precisely, it appears as a (3,1)-fast–slow system whose motion is constituted in a succession of slow and fast epochs. Founding a (3,1)-fast–slow APMD is interesting since that implies a more complex dynamics than in the case of a classic NES whose APMD is only (2,1)-fast–slow. A fast–slow analysis is finally conducted within the framework of the geometric singular perturbation theory. From the computation of the so-called critical manifold and the analytical expressions of the APMD fixed points, a global stability analysis is performed. This enables us to interpret a certain number of regimes observed on numerical simulations of the initial system. • A Van der Pol oscillator is coupled to a Bistable Nonlinear Energy Sinks is studied. • The so-called MSHBM is modified to consider specific features of the BNES. • The obtained amplitude-phase modulation dynamics (APMD) is a (3,1)-fast–slow system. • Fast–slow analysis of the APMD is performed. • This enables to interpret a certain number of regimes observed on numerical simulations. [ABSTRACT FROM AUTHOR]

The subsea capping stack is crucial equipment for emergency rescue in a blowout scenario, which determines the success or failure of the emergency rescue. The secondary risk prevention of the blowout emergency continues to face a persistent challenge. This paper proposes a methodology framework for emergency risk of the subsea capping stack, which aims to realize the quantitative risk assessment of installation operation by integrating numerical simulation and an Artificial neural network (ANN) model. Herein, the numerical model of fluid impact for the capping stack is constructed, and the impact forces of the blowout fluid are analyzed. The calculation results indicate that the blowout pressure, water depth, and installation height significantly affect the impact force during emergency operations. Furthermore, a genetic algorithm optimizing the neural network (GA-BP) model for quickly predicting the blowout impact force is established to improve emergency response efficiency based on sufficient simulation data. The prediction model has a minor mean absolute percentage error (MAPE), and its accuracy is also verified compared with the SVM model. Besides, the developed model speeds up the processing time from hours to seconds compared to numerical simulation. Therefore, it can provide a decision-making basis for emergency engineers at the site of blowout accidents more efficiently. • An integrated methodology is proposed to quantify the installation risk for the subsea capping stack. • The simulation model of the capping stack during the installation process is constructed to predict the impact forces. • A prediction model is developed to speed up the processing time from hours to seconds compared to numerical simulation. [ABSTRACT FROM AUTHOR]

The intertwining relationship between sustainability and discrete probability distributions found its significance in decision-making processes and risk assessment frameworks. Count data modeling and its practical applications have gained attention in numerous research studies. This investigation focused on a particular discrete distribution characterized by a single parameter obtained through the survival discretization method. Statistical attributes of this distribution were accurately explicated using generalized hypergeometric functions. The unveiled characteristics highlighted its suitability for analyzing data displaying "right-skewed" asymmetry and possessing extended "heavy" tails. Its failure rate function effectively addressed scenarios marked by a consistent decrease in rates. Furthermore, it proved to be a valuable tool for probabilistic modeling of over-dispersed data. The study introduced various estimation methods such as maximum product of spacings, Anderson-Darling, right-tail Anderson-Darling, maximum likelihood, least-squares, weighted least-squares, percentile, and Cramer-Von-Mises, offering comprehensive explanations. A ranking simulation study was conducted to evaluate the performance of these estimators, employing ranking techniques to identify the most effective estimator across different sample sizes. Finally, real-world sustainability engineering and medical datasets were analyzed to demonstrate the significance and application of the newly introduced model. [ABSTRACT FROM AUTHOR]

Using mathematical models of physiological systems in medicine has allowed for the development of diagnostic, treatment, and medical educational tools. However, their complexity restricts, in most cases, their application for predictive, preventive, and personalized purposes. Although there are strategies that reduce the complexity of applying models based on fitting techniques, most of them are focused on a single instant of time, neglecting the effect of the system's temporal evolution. The objective of this research was to introduce a dynamic fitting strategy for physiological models with an extensive array of parameters and a constrained amount of experimental data. The proposed strategy focused on obtaining better predictions based on the temporal trends in the system's parameters and being capable of predicting future states. The study utilized a cardiorespiratory model as a case study. Experimental data from a longitudinal study of healthy adult subjects undergoing aerobic exercise were used for fitting and validation. The model predictions obtained in a steady state using the proposed strategy and the traditional single-fit approach were compared. The most successful outcomes were primarily linked to the proposed strategy, exhibiting better overall results regarding accuracy and behavior than the traditional population fitting approach at a single instant in time. The results evidenced the usefulness of the dynamic fitting strategy, highlighting its use for predictive, preventive, and personalized applications. [ABSTRACT FROM AUTHOR]

Ruptures of pipelines can result in dangerous fluids spreading toward populated areas. It is critical for designers to have tools that can accurately predict whether populated areas might be within a plume rupture zone. Numerical simulations using computational fluid dynamics (CFD) are compared here with experimental and real-world carbon dioxide ruptures. The experimental data were used to validate the computer model; subsequently, the algorithm was used for a real-world rupture from 2020 that occurred in the USA. From experiments, CFD predictions were superior to diffusion model results based on measurements made downstream of the release (within 1% concentration). Results from the real-world simulation confirm that a nearby town was in a plume pathway. Citizens in the town sought medical attention consistent with the calculated plume concentrations. CFD predictions of the airborne concentration of carbon dioxide in the town approximately 1 mile (1.5 km) downstream of the rupture reveal time-averaged concentrations of ~5%. One person was unconscious for ~45 min at a distance of 0.6 miles from the rupture site; other unconscious persons were in the center of the town (~1 mile from the rupture site) and ~1.2 miles from the rupture. These reports are in excellent agreement with the calculated plume concentrations in the region. [ABSTRACT FROM AUTHOR]

This study analyses the impact of initial conditions on the results of numerical simulations of the fan load with underwater detonation and simultaneously typical harmonic loads from the operating device. It was shown that different initial conditions affect both displacement and velocity results. Furthermore, significant differences were indicated when comparing the results with devices without harmonic loads. The results indicate the need for more detailed analyses at the initial stage of modelling the impact resistance of devices planned for ship installation. [ABSTRACT FROM AUTHOR]