Computer Simulation Research Articles

Radiation Pattern Reconfigurable Arch-Shaped Dual-Band Antenna for Wi-Fi and WLAN Applications

This paper describes the design and analysis of a reconfigurable radiation pattern dual-band antenna for Wi-Fi and WLAN applications. The antenna patch comprises two parts: the upper part, which consists of three symmetrical oval rings, and the lower part, which is shaped like a lotus flower. By controlling the ON and OFF states of lumped p-i-n switches to control the direction of the radiation beams, the proposed pattern reconfigurable antenna achieves three reconfigurable states. The beam's direction change is performed by two switches that are connected in the gap between the feedline and the arch. The proposed antenna operates at 2.4 and 5.5 GHz, covering the bands from 2.1882 to 2.55 GHz and from 5.31 to 5.96 GHz, respectively. Additionally, the directivity over the working bands is about 1.92 to 4 dBi while the gain lies in the range of 1.66 to 3.5 dB. Moreover, the voltage standing wave ratio (VSWR) varies from 1 to 1.20. The size of the antenna is 47×59.5 mm2 which is printed on a 1.6 mm thickness FR-4 substrate of 4.4 relative permittivity. Computer simulation technology Microwave Studio is used to design and study the recommended constructions. The proposed design achieves an acceptable value of VSWR, stable gain, and good directivity, which makes it a suitable choice for future radiation pattern reconfiguration applications. The proposed antenna is distinguished by a simple shape, compact size, respectable return loss, good radiation characteristics, and high efficiency. The obtained results from measurements are quite close to the simulations.

Efficient signal sequence of mRNA vaccines enhances the antigen expression to expand the immune protection against viral infection

The signal sequence played a crucial role in the efficacy of mRNA vaccines against virus pandemic by influencing antigen translation. However, limited research had been conducted to compare and analyze the specific mechanisms involved. In this study, a novel approach was introduced by substituting the signal sequence of the mRNA antigen to enhance its immune response. Computational simulations demonstrated that various signal peptides differed in their binding capacities with the signal recognition particle (SRP) 54 M subunit, which positively correlated with antigen translation efficiency. Our data revealed that the signal sequences of tPA and IL-6-modified receptor binding domain (RBD) mRNA vaccines sequentially led to higher antigen expression and elicited more robust humoral and cellular immune protection against the SARS-CoV-2 compared to the original signal sequence. By highlighting the importance of the signal sequence, this research provided a foundational and safe approach for ongoing modifications in signal sequence-antigen design, aiming to optimize the efficacy of mRNA vaccines.

Physical and Numerical Modeling of Flow in a Meandering Channel

In this study, flow behavior in a meandering channel was investigated experimentally and numerically. The experiments were carried out for nine different cases on a channel consisting of 180° and 120° angle bends following successively. Measurements were conducted employing Acoustic Doppler Velocimetry (ADV) at 13 different points in the inner, middle, and outer bends of the sections located at significant bends along the channel. Depth-averaged velocity, velocity profiles, bed shear stress, and turbulence kinetic energy parameters were considered to understand the flow behavior in the meandering channel. A 1:1 scale numerical model of the experimental setup was generated using the Computational Fluid Dynamics (CFD) method through the verified FLOW-3D software (HYDRO 2022R1). It was found to be successful in estimating all parameters and was capable of investigating the flow behavior in the meandering channel. Additionally, a mesh independence study was performed, and four different turbulence models were compared. As a result, as the flow encountered the first meander in the channel, secondary flow occurred, and lateral momentum transfer took place. Therefore, velocity increased by approximately 30% from the first meander of 180° angles to the second meander of 120° angles. Therefore, the most critical zone was the inner bend of the 120-angle meander.

Disk Wind Feedback from High-mass Protostars. IV. Shock-ionized Jets

Massive protostars launch accretion-powered, magnetically collimated outflows, which play crucial roles in the dynamics and diagnostics of the star formation process. Here we calculate the shock heating and resulting free–free radio emission in numerical models of outflows of massive star formation within the framework of the Turbulent Core Accretion model. We postprocess 3D magnetohydrodynamic simulation snapshots of a protostellar disk wind interacting with an infalling core envelope, and calculate shock temperatures, ionization fractions, and radio free–free emission. We find heating up to ∼107 K and near-complete ionization in shocks at the interface between the outflow cavity and infalling envelope. However, line-of-sight averaged ionization fractions peak around ∼10%, in agreement with values reported from observations of massive protostar G35.20-0.74N. By calculating radio-continuum fluxes and spectra, we compare our models with observed samples of massive protostars. We find our fiducial models produce radio luminosities similar to those seen from low- and intermediate-mass protostars that are thought to be powered by shock ionization. Comparing to more massive protostars, we find our model radio luminosities are ∼10–100 times less luminous. We discuss how this apparent discrepancy either reflects aspects of our modeling related to the treatment of cooling of the post-shock gas or a dominant contribution in the observed systems from photoionization. Finally, our models exhibit 10 yr radio flux variability of ∼5%, especially in the inner 1000 au region, comparable to observed levels in some hypercompact H ii regions.

Global climate modeling of the Jupiter troposphere and effect of dry and moist convection on jets

The atmosphere of Jupiter is characterized by banded jets, including an equatorial super-rotating jet, by an intense moist convective activity, and by perturbations exerted by vortices, waves, and turbulence. Even after space exploration missions to Jupiter and detailed numerical modeling of Jupiter, questions remain about the mechanisms underlying the banded jets and the role played by dry and moist convection in maintaining these jets. We report three-dimensional simulations of the Jupiter weather layer using a global climate model (GCM) called Jupiter-DYNAMICO, which couples hydrodynamical integrations on an icosahedral grid with detailed radiative transfer computations. We added a thermal plume model for Jupiter that emulates the effect of mixing of heat, momentum, and tracers by dry and moist convective plumes that are left unresolved in the GCM mesh spacing with a physics-based approach. Our Jupiter-DYNAMICO global climate simulations show that the large-scale Jovian flow, in particular the jet structure, could be highly sensitive to the water abundance in the troposphere and that an abundance threshold exists at which equatorial super-rotation develops. In contrast to our dry (or weakly moist) simulations, simulations that include the observed amount of tropospheric water exhibit a clear-cut super-rotating eastward jet at the equator and a dozen eastward mid-latitude jets that do not migrate poleward. The magnitudes agree with the observations. The convective activity simulated by our thermal plume model is weaker in the equatorial regions than in mid to high latitudes, as indicated by lightning observations. Regardless of whether they are dry or moist, our simulations exhibit the observed inverse energy cascade from small (eddies) to large scales (jets) in a zonostrophic regime.

Hygrothermal response to air movements in wall junctions: Comparison between two numerical approaches and experiments

Airflow in wall-to-wall junctions is known to have a major hygrothermal impact on building performance. However, current and validated modeling options to simulate such phenomena are limited. This paper develops and compares two numerical models to study the heat and moisture transfer due to air infiltrations through a prefabricated wall-to-wall junction. The first model explicitly accounts for the airflow with a pipe flow approach. The second model is a modification to a typical approach to simulate ventilated cavities in building envelope simulation tools and mimics the effect of the airflow through source terms. Both approaches were introduced in a heat and moisture transfer 2D finite element model. Additionally, laboratory measurements were conducted in a climatic chamber to validate the simulation results. Six scenarios were tested experimentally under steady-state conditions. These datasets were used to calibrate different parameters of the models, such as material properties, the junction air gap thickness, and the magnitude of the heat and moisture source terms. Both sets of numerical results provided reasonable agreement with the measurements. The first approach outputs more accurate temperature and relative humidity values than the second one. However, considering uncertainties, no method predicted a perfect fit with the relative humidity profiles. Close to the junction, the first method estimates better the relative humidity than the second one. This work provides guidelines to better model and account for wall junctions in building envelope simulators.

W-HYDRA: a new experimental platform for the Water-Cooled Lead Lithium Breeding Blanket

Abstract In the framework of the activities coordinated by the EUROfusion consortium, the Water thermal-HYDRAulic (W-HYDRA) experimental platform is being built at the ENEA Brasimone Research Centre in order to support the development of the Water-Cooled Lead Lithium (WCLL) Breeding Blanket (BB). In particular, this infrastructure will make possible the installation and testing of prototypical mock-ups under relevant working conditions, such as the First Wall (FW), the manifold and the Steam Generator (SG). Moreover, it will represent an integral test facility for the investigation of phenomena characteristic of WCLL BB concept, such as the PbLi/water interaction. Finally, the collection of data coming from the different planned experimental campaigns will allow to qualify and validate numerical models and codes currently adopted for the design of components, as well as for the modelling of complex phenomena typical of the WCLL BB.
In order to come to a definitive design of the different facilities constituting the experimental platform, several design analyses assessing the thermal, hydraulic and structural performances of the different facilities and components are necessary. The paper reports a highlight of the W-HYDRA platform with a general description of the facilities. Some of the most relevant design studies carried out so far are reported as well, highlighting their impact on the evolution of the design.

Metadata and feature importance analyses of membrane capacitive deionization models: Is a water treatment artificial intelligence panacea possible?

Membrane capacitive deionization (MCDI) is an emerging technology for water purification and desalination. Artificial intelligence (AI) techniques using machine learning (ML) and deep learning (DL) have been widely applied to overcome the drawbacks of conventional numerical models in predicting effluent concentrations, an important parameter to estimate the energy consumption and degree of desalination of the MCDI process. However, despite the remarkable progress of these ML/DL models, relevant studies have only been conducted with limited datasets, leading to a substantial controversy regarding model accuracy. Therefore, in this study, we comprehensively evaluated the performances and applicability of multiple ML/DL models for MCDI using metadata (i.e., performance indices) and feature importance analyses. One MCDI dataset containing both constant-current and constant-voltage operations was reconfigured uniformly or unevenly depending on operation modes. Subsequently, six ML models and one DL model were used to execute the analyses using performance indices. Collectively, this study suggests that a perfect ML/DL model for the water treatment process may not exist, and understanding data types is as important as selecting appropriate models to build a data-driven AI model when process performance is greatly affected by specific input variables (i.e., current and voltage).

A Numerical Time Integration Procedure for Secondary Dendrite Arm Spacing in Hyper-Peritectic Steel Alloys

AbstractA numerical time integration procedure for the calculation of the secondary dendrite arm spacing (SDAS) in FeC hyper-peritectic alloys is presented, a preferred group of low-carbon casting steel. The procedure incorporates a three-stage thin arm dissolution model, which is solved at each time step using Newton–Raphson iteration. This is coupled to a coarsening model based on the integral forms of the dissolution model, which are solved using Gaussian quadrature, as well as a growth model for solid fraction evolution. The procedure can easily be embedded into numerical models for solidification, in which the space–time evolution of the SDAS is required for determining the dynamic permeability in the mushy zone. Higher order approximations for both growth and solute concentration evolution can easily be incorporated. Temperature dependence of thermophysical parameters is taken into account using inter-dendritic solidification empirical models, and an alloy-specific peritectic reaction constant is used to determine the isothermal peritectic holding time. The procedure is validated against experimental data presented in literature. Various cases of SDAS as a function of local solidification time, cooling rate and carbon composition are investigated. The method is compared to experimental results of SDAS obtained from test castings of a hyper-peritectic steel alloy and can be used to iteratively determine the alloy-specific peritectic reaction constant by comparing the solid fraction evolution during the peritectic reaction with that found from the experimental cooling curve.

Response Comparisons of Prefabricated and Cast-in-Place Subway Station Structures in Liquefiable Soil Foundation with the Ground Surface Slight Inclined

In recent years, the prefabricated subway station structure (PSSS) has become a hot spot of underground structure research. In this paper, the numerical model of a soil–subway station structure in a slowly inclined liquefiable site at the surface is established by using FLAC3D finite difference software. And the applicability of the PSSS under the gently inclined liquefiable site is investigated through the foundation pore water pressure, lateral movement of liquefied soil, and dynamic response and uplift characteristics of the subway station structure. It is found that under the gently inclined liquefiable site conditions, the PSSS exhibits tilting and floating behaviors and has an anti-liquefaction effect within a certain range of surrounding soil layers. Compared with the same type of cast-in-place subway station structure (CIPSSS), it has better resistance to overturning and uplift, and the structure has less stress. Under the premise of ensuring static waterproofing, the PSSS can be applied to surface inclined liquefiable sites.

Computed Simulation of Transcatheter Edge-to-Edge Mitral Valve Repair - A Proof of Concept Study.

As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in preprocedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element (FE) computational simulation model to predict results of transcatheter edge-to-edge (TEER) interventions. We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. Three-dimensional (3D) transesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip(s) type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after simulation of the clip implantation was compared to the clinical results obtained at the end of the intervention. We analyzed the degree and location of residual MR and the shape and area of the diastolic mitral valve area. We performed computational simulation on 5 patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area. In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in 5 patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic mitral valve area.

Molecular Dynamics Simulation for the Acidic Compounds Retention Mechanism Study on Octyl-Quaternary Ammonium Mixed-Mode Stationary Phase.

With the widespread application of mixed-mode chromatography in separation analysis, it is becoming increasingly important to study its retention mechanism. The retention behavior of acidic compounds on mixed-mode octyl-quaternary ammonium (Sil-C8-QA) columns was investigated by computer simulation. Firstly, the benzoic acid homologues were used as the analytes, and the simulation model was constructed by the Materials Studio. Geometric optimization, annealing and molecular dynamics (MD) simulation of these complexes resulted in optimized conformations. The binding energy, mean square displacement (MSD) and torsion angle distribution generated by MD simulation were then analyzed. The results showed that the more negative binding energy, the greater the MSD and the narrower the torsion angle distribution, indicating that the stationary phase behaves with stronger interaction and retention. The retention behavior of five acidic drugs on the Sil-C8-QA column was then successfully explained by simulation. Acidic drugs are more retentive on the mixed-mode column due to the more substantial interaction brought by the reversed-phase/ion-exchange mixed-mode mechanism compared to other single-mode columns. This simulation method is expected to provide ideas for studying the separation mechanism and predicting the retention behavior of more complex samples.

Research on Alzheimer's Disease (AD) Involving the Use of In vivo and In vitro Models and Mechanisms.

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by the progressive formation of extracellular amyloid plaques, intracellular neurofibrillary tangles, inflammation, and impaired antioxidant systems. Early detection and intervention are vital for managing AD effectively. This review scrutinizes both in-vivo and in-vitro screening models employed in Alzheimer's disease research. In-vivo models, including transgenic mice expressing AD-related mutations, offer profound insights into disease progression and potential therapeutic targets. A thorough understanding of these models and mechanisms will facilitate the development of novel therapies and interventions for Alzheimer's disease. This review aims to provide an overview of the current experimental models in AD research, assess their strengths and weaknesses as model systems, and underscore the future prospects of experimental AD modeling. We conducted a systematic literature search across multiple databases, such as Pub- Med, Bentham Science, Elsevier, Springer Nature, Wiley, and Research Gate. The search strategy incorporated pertinent keywords related to Alzheimer's disease, in-vivo models, in-vitro models, and screening mechanisms. Inclusion criteria were established to identify studies focused on in-vivo and in-vitro screening models and their mechanisms in Alzheimer's disease research. Studies not meeting the predefined criteria were excluded from the review. A well-structured experimental animal model can yield significant insights into the neurobiology of AD, enhancing our comprehension of its pathogenesis and the potential for cutting-edge therapeutic strategies. Given the limited efficacy of current AD medications, there is a pressing need for the development of experimental models that can mimic the disease, particularly in pre-symptomatic stages, to investigate prevention and treatment approaches. To address this requirement, numerous experimental models replicating human AD pathology have been established, serving as invaluable tools for assessing potential treatments. In summary, this comprehensive review underscores the pivotal role of in-vivo and in-vitro screening models in advancing our understanding of Alzheimer's disease. These models offer invaluable insights into disease progression, pathological mechanisms, and potential therapeutic targets. By conducting a rigorous investigation and evaluation of these models and mechanisms, effective screening and treatment methods for Alzheimer's disease can be devised. The review also outlines future research directions and areas for enhancing AD screening models.

Screening approach by a combination of computational and in vitro experiments: identification of fluvastatin sodium as a potential SIRT2 inhibitor.

Sirtuins (SIRTs) are NAD+-dependent deacetylases that play various roles in numerous pathophysiological processes, holding promise as therapeutic targets worthy of further investigation. Among them, the SIRT2 subtype is closely associated with tumorigenesis and malignancies. Dysregulation of SIRT2 activation can regulate the expression levels of related genes in cancer cells, leading to tumor occurrence and metastasis. In this study, we used computer simulations to screen for novel SIRT2 inhibitors from the FDA database, based on which 10 compounds with high docking scores and good interactions were selected for in vitro anti-pancreatic cancer metastasis testing and enzyme binding inhibition experiments. The results showed that fluvastatin sodium may possess inhibitory activity against SIRT2. Subsequently, fluvastatin sodium was subjected to molecular docking experiments with various SIRT isoforms, and the combined results from Western blotting experiments indicated its potential as a SIRT2 inhibitor. Next, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were performed, revealing the binding mode of fluvastatin sodium at the SIRT2 active site, further validating the stability and interaction of the ligand-protein complex under physiological conditions. Overall, this study provides a systematic virtual screening workflow for the discovery of SIRT2 activity inhibitors, identifies the potential inhibitory effect of fluvastatin sodium as a lead compound on SIRT2, and opens up a new direction for developing highly active and selectively targeted SIRT2 inhibitors.

Laser-sound reproduction by pulse amplitude modulation audio streams

Recently, the possibility to reproduce complex continuous acoustic signals via pulsed laser-plasma sound sources was demonstrated. This was achieved by optoacoustic transduction of dense laser pulse trains, modulated via single- or multi-bit Sigma–Delta, in the air or on solid targets. In this work, we extend the laser-sound concept to amplitude modulation techniques. Particularly, we demonstrate the possibility of transcoding audio streams directly into acoustic pulse streams by analog pulsed amplitude modulation. For this purpose, an electro-optic modulator is used to achieve pulse-to-pulse amplitude modulation of the laser radiation, similarly to the multi-level Sigma–Delta method. The modulator is directly driven by the analog input stream through an audio interface. The performance of the system is evaluated at a proof-of-principle level for the reproduction of test audio signals such as single tones, double tones and sine sweeps, within a limited frequency range of the audible spectrum. The results are supported by computational simulations of the reproduced acoustic signals using a linear convolution model that takes as input the audio signal and the laser-generated acoustic pulse profile. The study shows that amplitude modulation allows for significant relaxation of the laser repetition rate requirements compared to the Sigma–Delta-based implementation, albeit at the potential cost of increased distortion of the reproduced sound signal. The nature of the distortions is analyzed and a preliminary experimental and computational investigation for their suppression is presented.

LinG3D: visualizing the spatio-temporal dynamics of clonal evolution.

Cancers are spatially heterogenous, thus their clonal evolution, especially following anti-cancer treatments, depends on where the mutated cells are located within the tumor tissue. For example, cells exposed to different concentrations of drugs, such as cells located near the vessels in contrast to those residing far from the vasculature, can undergo a different evolutionary path. However, classical representations of cell lineage trees do not account for this spatial component of emerging cancer clones. Here, we propose routines to trace spatial and temporal clonal evolution in computer simulations of the tumor evolution models. The LinG3D (Lineage Graphs in 3D) is an open-source collection of routines (in MATLAB, Python, and R) that enables spatio-temporal visualization of clonal evolution in a two-dimensional tumor slice from computer simulations of the tumor evolution models. These routines draw traces of tumor clones in both time and space, and may include a projection of a selected microenvironmental factor, such as the drug or oxygen distribution within the tumor, if such a microenvironmental factor is used in the tumor evolution model. The utility of LinG3D has been demonstrated through examples of simulated tumors with different number of clones and, additionally, in experimental colony growth assay. This routine package extends the classical lineage trees, that show cellular clone relationships in time, by adding the space component to show the locations of cellular clones within the 2D tumor tissue patch from computer simulations of tumor evolution models.

Systematic simulation of tumor cell invasion and migration in response to time-varying rotating magnetic field.

Cancer invasion and migration play a pivotal role in tumor malignancy, which is a major cause of most cancer deaths. Rotating magnetic field (RMF), one of the typical dynamic magnetic fields, can exert substantial mechanical influence on cells. However, studying the effects of RMF on cell is challenging due to its complex parameters, such as variation of magnetic field intensity and direction. Here, we developed a systematic simulation method to explore the influence of RMF on tumor invasion and migration, including a finite element method (FEM) model and a cell-based hybrid numerical model. Coupling with the data of magnetic field from FEM, the cell-based hybrid numerical model was established to simulate the tumor cell invasion and migration. This model employed partial differential equations (PDEs) and finite difference method to depict cellular activities and solve these equations in a discrete system. PDEs were used to depict cell activities, and finite difference method was used to solve the equations in discrete system. As a result, this study provides valuable insights into the potential applications of RMF in tumor treatment, and a series of in vitro experiments were performed to verify the simulation results, demonstrating the model's reliability and its capacity to predict experimental outcomes and identify pertinent factors. Furthermore, these findings shed new light on the mechanical and chemical interplay between cells and the ECM, offering new insights and providing a novel foundation for both experimental and theoretical advancements in tumor treatment by using RMF.

Analytical and Numerical Modelling of Debris Impact Events on Columns

Analytical and Numerical Modelling of Debris Impact Events on Columns

Directivity and Excitability of Ultrasonic Shear Waves Using Piezoceramic Transducers—Numerical Modeling and Experimental Investigations

In this paper, piezoceramic-based excitation of shear horizontal waves is investigated. A thickness-shear d15 piezoceramic transducer is modeled using the finite-element method. The major focus is on the directivity and excitability of the shear horizontal fundamental mode with respect to the maximization of excited shear and minimization of Lamb wave modes. The results show that the geometry of the transducer has more effect on the directivity than on the excitability of the analyzed actuator. Numerically simulated results are validated experimentally. The experimental results show that transducer bonding significantly affects the directivity and amplitude of the excited modes. In conclusion, when the selected actuator is used for shear excitation, the best solution is to tailor the transducer in such a way that at the resonant frequency the desired directivity is achieved.

Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability

Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability