Homogeneous Model Research Articles

Bending shape memory properties and multi-scale viscoelastic behaviors of knitted-fabric reinforced polymer composites

Knitted fabrics with easily deformable loop structure have the potential in the development of shape memory polymeric composites with large recovery deformations. The knitted fabric reinforced shape memory epoxy polymer composites (SMPC) were prepared in this work. The effects of loop densities, orientations and bending radii on shape memory properties of SMPC were investigated. The shape fixity ratio and shape recovery ratio of SMPC subjected to U-shaped bending radius of 5 mm are above 98 %. The shape recovery force of SMPC can reach up to 5.9 N. The thermodynamic properties of SMP were also characterized to obtain mechanical parameters and a user-defined material subroutine (UMAT) of shape memory epoxy polymer (SMEP) was written. Based on viscoelastic theory and the multi-scale geometrical structures, the macroscopic homogeneous thermodynamic model and mesoscopic thermodynamic model of knitted fabric reinforced SMPC were established to study the macro-scale stress distribution and meso-scale deformation evolution during shape memory process, respectively. The neutral surface position of SMPC during bending deformation is offset inner. The unique anisotropic loop structure of knitted fabric determines the shape memory behavior of the SMPC. Finally, micro-CT characterizations of knitted fabric reinforced SMPC were conducted to further understand the loop deformation mechanism during shape memory process. This study will provide important theoretical and technical support for large deformation structure design and deformation prediction of smart composites.

Predicting mechanical heterogeneity in glassy polymer nanocomposites via an inverse computational approach based on atomistic molecular simulations and homogenization methods

Probing the mechanical behavior of the region formed between a nanoparticle reinforcement and a polymer matrix in a polymer nanocomposite structure, denoted as the “interphase”, is a main challenge as such regions are difficult to investigate by experimental methods. Here, we accurately characterize the heterogeneous mechanical behavior of polymer nanocomposites, focusing on polymer/nanofiller interphases via a combination of nanomechanical simulations and numerical homogenization techniques. Initially, the global mechanical performance of a glassy poly(ethylene oxide) polymer nanocomposite reinforced with silica nanoparticles is studied using detailed atomistic molecular dynamics simulations for 1.9% and 12.7% silica volume fractions. Next, the polymer/silica interphase thickness is identified by probing the polymer atom-based density distribution profile in the vicinity of the nanofiller at equilibrium. On the basis of this thickness, the interphase is subdivided to check the position-dependent change in mechanical properties. Then, using continuum mechanics and atomistic simulations, we proceed to compute the effective Young’s modulus and Poisson’s ratio of the polymer/nanoparticle interphase as function of the distance from the nanoparticle. In the last step, an inverse numerical homogenization model is proposed to predict the mechanical properties of the interphase on the basis of a comparison criteria with the data from MD. The results were found to be acceptable, raising the possibility of accurately and efficiently predicting interfacial properties in nanostructured materials.

Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt

The purpose of this paper is to assess and predict sovereign credit risk for Egypt, Morroco and Saudi Arabia using credit default swap (CDS) spreads obtained from the DataStream database for the period from 2009 to 2022. Our approach consists of generating the implied default probability and the corresponding credit rating in order to estimate the term structure of the implied default probability using the Nelson–Siegel model. In order to validate the prediction from the probability term structure, we calculate the transition matrices based on the implied rating using the homogeneous Markov model. The main results show that, overall, the probabilities of defaulting in the long term are higher than those in the short term, which implies that the future outlook is more pessimistic given the events that occurred during the study period. Egypt seems to be the country with the most fragile economy, especially after 2009, likely because of the political events that marked the country at that time. The economies of Morocco and Saudi Arabia are more resilient in terms of both default probability and credit rating. These findings can help policymakers develop targeted strategies to mitigate economic risks and enhance stability, and they provide investors with valuable insights for managing long-term investment risks in these countries.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

A cell-centered implicit finite difference scheme to study wave propagation in acoustic media: A numerical modeling

In the present paper, we present a Cell-Centered Implicit Finite Difference (CCIFD) operator-based numerical scheme for the propagation of acoustic waves that is very effective, accurate, and small in size. This scheme requires fewer estimation points than the traditional central difference derivative operator. Any numerical simulation is significantly impacted by the precision of a numerical derivative. Long stencils can deliver excellent accuracy while also minimizing numerical anisotropy error. However, a long stencil requires a lot of computational resources, and as these derivatives get bigger, they could start to look physically unrealistic due to contributions from nodes located extremely far, wherein the derivative is local in nature. Furthermore, using such lengthy stencils at boundary nodes may result in errors. The present article investigates a cell-centered fourth order finite difference scheme to model acoustic wave propagation which utilizes a lesser number of nodes in comparison to the traditional Central Difference (CD) operator. However, in general the implicit derivative operator has high computational cost and therefore despite its significant advantages it is generally avoided to be implemented in applications. This serves as a motivation for the present paper to explore a technique called CCIFD that significantly decreases the computational expense by nearly fifty percent. Additionally, spectral characterization of the CCIFD derivative operator has been analyzed and discussed. Finally, the wave propagation has been numerically simulated in 2-dimensional homogeneous and Marmousi model using CCIFD scheme to validate the applicability and stability of the scheme.

Characterization of petrophysical and seismic properties for CO2 storage with sensitivity analysis

Saline aquifers are considered as highly favored reservoirs for CO2 sequestration due to their favorable properties. Understanding the impact of saline aquifer properties on the migration and distribution of CO2 plume is crucial. This study focuses on four key parameters—permeability, porosity, formation pressure, and temperature—to characterize the reservoir and analyse the petrophysical and elastic response of CO2. First, we performed reservoir simulations to simulate CO2 saturation, using multiple sets of these four parameters to examine their significance on CO2 saturation and the plume migration speed. Subsequently, the effect of these parameters on the elastic properties is tested using rock physics theory. We established a relationship of compressional wave velocity (Vp) and quality factor (Qp) with the four key parameters, and conducted a sensitivity analysis to test their sensitivity to Vp and Qp. Finally, we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed Vp and Qp models, and analysed the impact of CO2 saturation changes on seismic data. As for the above numerical simulations and analysis, we conducted sensitivity analysis using both homogeneous and heterogeneous models. Consistent results are found between homogeneous and heterogeneous models. The permeability is the most sensitive parameter to the CO2 saturation, while porosity emerges as the primary factor affecting both Qp and Vp. Both Qp and Vp increase with the porosity, which contradicts the observations in gas reservoirs. The seismic simulations highlight significant variations in the seismic response to different parameters. We provided analysis for these observations, which serves as a valuable reference for comprehensive CO2 integrity analysis, time-lapse monitoring, injection planning and site selection.

Innovación educativa con sistemas de aprendizaje adaptativo impulsados por Inteligencia Artificial

The emergence of artificial intelligence (AI) is transforming education through adaptive learning systems. These systems, based on AI algorithms, personalize the educational experience by adjusting to the needs and learning styles of each student. Using techniques such as machine learning and deep learning, they analyze large volumes of data to generate personalized learning itineraries, breaking with the homogeneous teaching model. Their implementation requires a suitable technological platform, a solid data infrastructure and the training of teachers in the use of these tools. The benefits are multiple: students receive real-time feedback and progress at their own pace, improving their motivation and learning effectiveness, while teachers can focus their efforts on higher value-added tasks and obtain valuable information on their students' progress, facilitating adaptive and personalized teaching.

An electrochemical biosensor with homogeneous dual amplification strategy for sensitive analysis of Pb2+

Herein, a homogeneous double amplified electrochemical biosensing system was designed on the basis of rolling circle amplification (RCA) and DNAzyme-assisted Pb2+ recycling amplification with the assistance of the signal molecule methylene blue (MB), which was used for highly sensitive analysis of Pb2+. In comparison with the conventional electrochemical biosensor, the homogeneous strategy adopted in this work can avoid the complex electrode modification and immobilization processes, and address the issues of the large steric hindrance and the restricted probe freedom on the sensing interface, thus achieving high recognition efficiency between recognition unit and target molecule as well as excellent detection performance of biosensor. In addition, the double amplified method assembling RCA and DNAzyme-assisted Pb2+ recycling amplification can convert a handful of target Pb2+ into abundant signal molecule MB, which would lead to the double amplification of output signal and the significantly enhanced detection sensitivity. Taking advantages of homogeneous dual amplification strategy, the constructed electrochemical biosensor for Pb2+ analysis emerged a good linear range of 50 fM to 500 nM and a detection limit of 16.7 fM with significant selectivity and desirable stability. Impressively, the result presented herein comprise a valuable reference for establishing homogeneous multiple amplification model and constructing innovative biosensing system for sensitive detection of heavy metal ions.

3D reverse-time migration for pure P-wave in orthorhombic media

Compared with the transverse isotropic (TI) medium, the orthorhombic anisotropic medium has both horizontal and vertical symmetry axes and it can be approximated as a set of vertical fissures developed in a group of horizontal strata. Although the full-elastic orthorhombic anisotropic wave equation can accurately simulate seismic wave propagation in the underground media, a huge computational cost is required in seismic modeling, migration, and inversion. The conventional coupled pseudo-acoustic wave equations based on acoustic approximation can be used to significantly reduce the cost of calculation. However, these equations usually suffer from unwanted shear wave artifacts during wave propagation, and the presence of these artifacts can significantly degrade the imaging quality. To solve these problems, we derived a new pure P-wave equation for orthorhombic media that eliminates shear wave artifacts while compromising computational efficiency and accuracy. In addition, the derived equation involves pseudo-differential operators and it must be solved by 3D FFT algorithms. In order to reduce the number of 3D FFT, we utilized the finite difference and pseudo-spectral methods to conduct 3D forward modeling. Furthermore, we simplified the equation by using elliptic approximation and implemented 3D reverse-time migration (RTM). Forward modeling tests on several homogeneous and heterogeneous models confirm that the accuracy of the new equation is better than that of conventional methods. 3D RTM imaging tests on three-layer and SEG/EAGE 3D salt models confirm that the ORT media have better imaging quality.

Homogeneous Equilibrium Modeling for Subcritical Flows in Liquid Rocket Engine Cooling Systems

During off-design operations of liquid rocket engines, the coolant operating conditions can easily extend from the subcritical to the supercritical regime. As a matter of fact, it is very useful to have a single software able to study the flow in this range of operating conditions, providing reliable simulations that are reasonably quick and able to accurately estimate and assess the increase in coolant temperature along the channel and the wall temperature field. This objective is pursued by extending an established approach for the study of supercritical flows to the case of subcritical heating, where a two-phase flow may occur. This is done by exploiting the so-called homogeneous equilibrium model, which has been shown to be sufficiently predictive and accurate for specific applications. With the aim of demonstrating and discussing the potential and limitations of such a single software approach, analyses are conducted on different test cases where two-phase flow is induced by cavitation or flow boiling, and results are compared with those of analytical models and experimental data. It is found that, in addition to some intrinsic limitations in the analysis of subcooled boiling flows, satisfactory agreement with experimental data is obtained in the post-critical-heat-flux regime.

Numerical simulation of ultrasonic P-wave propagation in water-bearing coal based on gas-liquid homogeneous wave velocity model

This paper establishes the equivalent density and equivalent P-wave velocity models of coal bodies with different water saturation, and investigates the P-wave propagation evolution law of coal bodies with different water saturation from the perspective of numerical simulation. When the experimental coal samples continue to use high-pressure water after reaching the natural saturation state, the water saturation can be further increased, and the increase in water saturation is larger, and the corresponding P-wave velocity also appears to be increased more substantially, and this phenomenon also occurs in numerical simulation results, which indicates that the P-wave velocity will have an obvious increasing trend when the coal body is from nearly saturated to fully saturated. The experimental and numerical simulation results show that the P-wave velocity of coal samples increases with the water saturation degree in a similar exponential function, which further verifies the reasonableness and feasibility of the modelling based on the assumption of gas-liquid homogeneous medium. In addition, the propagation of P-wave in coal samples is affected by the pore and fracture structure, and the pore and fracture with small pore size has less influence on the P-wave, and vice versa.

Sliding Mode Control for Markov Jump Singularly Perturbed Systems Under Piecewise Homogeneous Stochastic Communication Protocol.

This work involves the sliding mode control (SMC) issue for a class of Markov jump singularly perturbed systems (MJSPSs) under consideration of unmatched external disturbances and communication constraints. For the first time, the piecewise homogeneous Markov chain (MC) which depends on the system mode and the controller mode is applied to control the scheduling of stochastic communication protocol (SCP), so that the MCs in the system models, the controller and the SCP constitute a three-layer nonstationary Markov model (NMM). This model perfectly describes the different objects of the three MCs and reflects the mutual regulation among them. The critical issue is to devise an adaptive controller and a sliding surface (SS) simultaneously under SCP scheduling. By applying a standard singular sliding mode surface, an appropriate nonstationary SMC law is established to promise the accessibility of the SS and the stability of the closed-loop system (CLS), and meet the expected performance indicator. Further, using the mode-dependent Lyapunov function and piecewise homogeneous Markov model method, sufficient criteria are obtained. The specific expression of the control gain is obtained by matrix decoupling technology. Finally, a numerical simulation is furnished to testify the correctness of the conclusion.

Coseismic deformation and seismogenic structure of the 2024 Hualien Earthquake measured by InSAR and GNSS

On April 3, 2024, an M7.3 earthquake occurred in the offshore area of Hualien County, Taiwan, China. The seismogenic structure at the epicentral location was highly complex, and studying this earthquake is paramount for understanding regional fault activity. In this study, we employed ascending and descending orbit Sentinel-1 Synthetic Aperture Radar (SAR) data and utilized differential interferometry (InSAR) technique to obtain the co-seismic deformation field of this event. The line-of-sight deformation field revealed that the main deformation caused by this earthquake was predominantly uplift, with maximum uplift values of approximately 38.8 ​cm and 46.1 ​cm for the ascending and descending orbits, respectively. By integrating the three-dimensional GNSS co-seismic deformation field, we identified the seismogenic fault located in the offshore thrust zone east of Hualien, trending towards the northwest. The fault geometry parameters, obtained through the inversion of an elastic half-space homogeneous model, indicated an optimal fault strike of 196°, a dip angle of 30.9°, and an average strike-slip of 0.4 ​m and dip-slip of −2.6 ​m. This suggests that the predominant motion along the seismogenic fault is thrusting. The distribution of post-seismic Coulomb stress changes revealed that aftershocks mainly occurred in stress-loaded regions. However, stress loading was observed along the northern segment of the Longitudinal Valley Fault, with fewer aftershocks. This highlights the importance of closely monitoring the seismic hazard associated with this fault segment.

Field-scale SAGD Performance Evaluation Utilizing Homogeneous Reservoir Model Based on Vertical Wells

Field-scale SAGD Performance Evaluation Utilizing Homogeneous Reservoir Model Based on Vertical Wells

Improved energy retrofit decision making through enhanced bottom-up building stock modelling

Modelling the performance of building stocks is crucial in facilitating the renovation at the building stock level. Bottom-up building stock modelling begins by detailing individual buildings and then aggregates them into stock level. Its primary advantage lies in capturing the inherent heterogeneity among distinct buildings, which enables tailored retrofitting. Naturally, this approach requires a comprehensive dataset with detailed building information such as geometry and envelope thermal properties. However, a common challenge is the incompleteness of available data in individual datasets. To address this, previous bottom-up studies have filled the missing data with representative or statistical data. Such practice could lead to homogeneous modelling of distinctbuildings within the same statistical group. This limits the utilization of key ability of bottom-up building stock modelling in capturing heterogeneity, such as tailored retrofitting to explore potential retrofitting areas and strategies.To address this challenge of homogeneous modelling, we utilize data fusion framework for bottom-up building stock modelling, employing probabilistic record linkage and inverse modelling techniques to integrate multiple incomplete building performance datasets. This framework fills the missing data in one dataset with information from another, thus capturing inherent heterogeneity in the building stock. An empirical study was conducted in Umeå, Sweden, to investigate the framework’s effectiveness by modelling building stock with various retrofitting strategies. This study contribution lies in enhancing bottom-up building stock modelling by capturing inherent heterogeneity, to provide tailored retrofitting solutions.

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

A Hybrid Normal Mode‐Collocation Method for Finding the Response of Laterally Homogeneous Compressible Maxwell Viscoelastic Earth Models

A Hybrid Normal Mode‐Collocation Method for Finding the Response of Laterally Homogeneous Compressible Maxwell Viscoelastic Earth Models

HomoR-CS: A homogeneous region-based compressed sensing method for SAR tomography

The performance of most existing tomographic synthetic aperture radar (SAR) (TomoSAR) methods that reconstruct the scene pixel-by-pixel is degraded by speckle noise and low signal-to-noise ratio. To solve these problems, we propose a homogeneous region-based compressed sensing (HomoR-CS) method for SAR tomography. This method enhances the processing approach by transitioning from the traditional pixel-by-pixel processing to the joint processing based on multiple adjacent pixels in homogeneous regions. First, a similarity measure is designed to cluster pixels that have similar electromagnetic scattering intensities and three-dimensional (3-D) positions into homogeneous regions. Then, the homogeneous region-oriented TomoSAR signal model is proposed and the solution is given. Sparse approximation at the homogeneous region level is used to estimate the elevation for every pixel. The multiple adjacent pixels within the homogeneous region are jointly processed to determine the initial elevation centers, which are used as the prior information for the subsequent accurate elevation estimation of each pixel. Finally, the experimental analyses using both simulated and measured data validate the effectiveness of the HomoR-CS method. The results show that the HomoR-CS method reduces the outliers of 3-D reconstruction results and enhances the recovery of weak scattering targets.

Rumor spreading and control in both homogeneous and heterogeneous networks with guidance mechanism

In this paper, we study the influence of authoritative institutions on rumor propagation and establish an IHSQR model, where Q represents the guided individuals. We consider the homogeneous and heterogeneous network models, respectively. By analyzing the conditions for the global asymptotically stable of equilibria in these models, we show their behavior under various scenarios. For the homogeneous network model, a case study of the Haze rumor is given, which verifies the effectiveness of the model. For the heterogeneous network model, we introduce optimal control to determine the minimum guidance strength and cost. The results show that the guiding role has a significant impact on rumor spread. Specifically, the stronger the guiding role, the smaller the size of rumor spreading. Therefore, to control the spread of rumors, authoritative institutions can play an important guiding role in managing and mitigating rumor propagation.

Multiscale modeling on the multi-physical behaviors of high temperature superconducting magnets based on a combined global homogenization and local refinement scheme

The safe and stable operation is a crucial issue in the development of high-field high temperature superconducting (HTS) magnets. In this paper, we construct a multiscale model which couples the homogenized global (macroscopic) behavior and the refined local (mesoscopic) characteristics to simulate the coupled electromagnetic-mechanical-thermal behaviors of the HTS magnets. In the model, the numerical homogenization method is adopted to simulate the macroscopic behavior of the magnets and identify the ‘dangerous region’ of the magnet which are prone to damage or quench. Then, a refined local sub-model which coupling with the macroscopic homogenization model is established by considering the microstructure and physical parameters of each components of the HTS tapes in the ‘dangerous region’. Thus, a combined global homogenization and local refinement scheme which balances the computational efficiency and numerical accuracy is developed to simulate the coupled multi-physical behaviors of the HTS magnets including the quench and its propagation. Our results show that the refined local sub-model can simulate the electromagnetic field and the stress-strain at the scale of the tape more accurately. Characteristics, such as the discontinuous stress distribution across the interfaces between different layers and the current shunt from the HTS layer to metallic layers during the quench process of HTS tapes, which are beyond the capability of the homogenization model, have also been well depicted by the refined sub-model.