Formulation Of Model Research Articles

Modelling a Response of Complex-Phase Steel at High Strain Rates.

In this article, a response of the complex-phase high-strength steel SZBS800 was modelled by considering the strain-rate influence. The material's response was first measured with a series of standard tensile tests at lower strain rates. Higher strain rates were achieved using the unconventional test of shooting the ball into flat specimens. A viscoplastic formulation of the Cowper-Symonds material model was applied to consider the strain-rate effects. The parameters SIGY, p, and C of the material model were estimated using a step-wise procedure. First, rough estimates of the three parameters were obtained from the tensile tests using the grid search method. Then, the parameters p and C were fine-tuned using the reverse engineering approach. With the help of explicit dynamic simulations and all the experimental data, a multi-criteria cost function was defined and applied to obtain a smooth response function for the parameters p and C. Its optimum was determined by a real-valued genetic algorithm. The optimal values of the estimated parameters model the material response well, although a domain of optimum candidates spans two orders of magnitude for the parameter p and a few orders of magnitude for the parameter C.

Modeling of heat conduction through rate equations

AbstractStarting from a classical thermodynamic approach, we derive rate-type equations to describe the behavior of heat flow in deformable media. Constitutive equations are defined in the material (Lagrangian) description where the standard time derivative satisfies the principle of objectivity. The statement of the Second Law is formulated in the classical form and the thermodynamic restrictions are then developed following a variant of the Coleman-Noll procedure where the entropy production too is given by a non-negative constitutive equation. Both the free energy and the entropy production are assumed to depend on a common set of independent variables involving, in addition to temperature, both temperature gradient and heat-flux vector together with their time derivatives. This approach results in rate-type constitutive function for the heat flux that are intrinsically consistent with the Second Law and easily amenable to analysis. In addition to providing already known models (e.g., Maxwell-Cattaneo-Vernotte’s and Jeffreys-like heat conductors), this scheme allows the formulation of new models of heat transport that are likely to apply also in nanosystems. This is consistent with the fact that higher-order time derivatives of the heat flux are in order when high-rate regimes occur.

Neuronal activity induces symmetry breaking in neurodegenerative disease spreading

Dynamical systems on networks typically involve several dynamical processes evolving at different timescales. For instance, in Alzheimer’s disease, the spread of toxic protein throughout the brain not only disrupts neuronal activity but is also influenced by neuronal activity itself, establishing a feedback loop between the fast neuronal activity and the slow protein spreading. Motivated by the case of Alzheimer’s disease, we study the multiple-timescale dynamics of a heterodimer spreading process on an adaptive network of Kuramoto oscillators. Using a minimal two-node model, we establish that heterogeneous oscillatory activity facilitates toxic outbreaks and induces symmetry breaking in the spreading patterns. We then extend the model formulation to larger networks and perform numerical simulations of the slow-fast dynamics on common network motifs and on the brain connectome. The simulations corroborate the findings from the minimal model, underscoring the significance of multiple-timescale dynamics in the modeling of neurodegenerative diseases.

A one-dimensional computational model for blood flow in an elastic blood vessel with a rigid catheter.

Strokes are one of the leading causes of death in the United States. Stroke treatment involves removal or dissolution of the obstruction (usually a clot) in the blocked artery by catheter insertion. A computer simulation to systematically plan such patient-specific treatments needs a network of about 105 blood vessels including collaterals. The existing computational fluid dynamic (CFD) solvers are not employed for stroke treatment planning as they are incapable of providing solutions for such big arterial trees in a reasonable amount of time. This work presents a novel one-dimensional mathematical formulation for blood flow modeling in an elastic blood vessel with a centrally placed rigid catheter. The governing equations are first-order hyperbolic partial differential equations, and the hypergeometric function needs to be computed to obtain the characteristic system of these hyperbolic equations. We employed the Discontinuous Galerkin method to solve the hyperbolic system and validated the implementation by comparing it against a well-established 3D CFD solver using idealized vessels and a realistic truncated arterial network. The results showed clinically insignificant differences in steady flow cases, with overall variations between 1D and 3D models remaining below 10%. Additionally, the solver accurately captured wave reflection phenomena at domain discontinuities in unsteady cases. A primary advantage of this model over 3D solvers is its ease in obtaining a discretized geometry of complex vasculatures with multiple arterial branches. Thus, the 1D computational model offers good accuracy and applicability in simulating complex vasculatures, demonstrating promising potential for investigating patient-specific endovascular interventions in strokes.

Wave setup estimation at regional scale: Empirical and modeling-based multi-approach analysis in the Mediterranean Sea

Wave setup is a physical process that induces a temporal increase of the mean water level due to wave dissipation by bottom friction and breaking in the surf zone, extending over tens to hundreds of meters in the cross-shore direction. Wave setup contribution to coastal sea level solely induced by wind and atmospheric effects can increase by more than 100% under extreme events and conditions favoring its formation. It is therefore crucial to consider this phenomenon when assessing sea-level-related coastal hazards. Previous studies estimated the wave setup effect by means of numerical modeling and empirical formulations at regional and global scale. Such analyses require either high computational capacity to implement high-resolution numerical models over large domains, and/or accurate information on coastal morphological features from global or regional databases. Although the Mediterranean Sea is a fetch-limited environment, waves generated from extra-tropical cyclones are powerful enough for wave setup to develop, and subsequently for a potential significant wave setup contribution to extreme coastal sea level. Through the use of both numerical and empirical methods, we investigate the uncertainty associated to wave setup representation on the frequency and magnitude of coastal extreme sea levels occurring on sandy beaches in the Mediterranean Sea. Wave setup values are compared at beach scale between process-based modeling and empirical approaches, showing highly variable results. We also quantify the impact of wave setup on return levels of coastal sea level extremes using reconstructed sea levels. We employ various methods to calculate the wave setup component. Results show high spatial dispersion, with clear differences between the numerical and empirical approaches, especially in regions prone to the development of energetic waves. The total inter-method dispersion of 100-year return levels is often higher than 30 cm for average values of 62.4 cm. We emphasize the important limitations related to wave setup modeling (i.e., its underestimation) at large scale, and call for caution when applying empirical formulations (generally developed from local studies) at regional to global scale, which can lead to unrealistic wave setup values.

A unified framework for prediction of liver steatosis dynamics in response to different diet and drug interventions

Background & AimsNon-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder, characterized by the accumulation of excess fat in the liver, and is a driving factor for various severe liver diseases. These multi-factorial and multi-timescale changes are observed in different clinical studies, but these studies have not been integrated into a unified framework. In this study, we aim to present such a unified framework in the form of a dynamic mathematical model. MethodsFor model training and validation, we collected data for dietary or drug-induced interventions aimed at reducing or increasing liver fat. The model was formulated using ordinary differential equations (ODEs) and the mathematical analysis, model simulation, model formulation and the model parameter estimation were all performed in MATLAB ResultsOur mathematical model describes accumulation of fat in the liver and predicts changes in lipid fluxes induced by both dietary and drug interventions. The model is validated using data from a wide range of drug and dietary intervention studies and can predict both short-term (days) and long-term (weeks) changes in liver fat. Importantly, the model computes the contribution of each individual lipid flux to the total liver fat dynamics. Furthermore, the model can be combined with an established bodyweight model, to simulate even longer scenarios (years), also including the effects of insulin resistance and body weight. To help prepare for corresponding eHealth applications, we also present a way to visualize the simulated changes, using dynamically changing lipid droplets, seen in images of liver biopsies. ConclusionIn conclusion, we believe that the minimal model presented herein might be a useful tool for future applications, and to further integrate and understand data regarding changes in dietary and drug induced changes in ectopic TAG in the liver. With further development and validation, the minimal model could be used as a disease progression model for steatosis.

Random Regret Minimization Approach to Commuting Mode Choice in São Paulo, Brazil

The random regret minimization (RRM) approach has been widely used in transport literature, but its application in the Global South is still marginal. In this paper we discuss individual commuting mode choice in the city of São Paulo (Brazil) from the perspective of the RRM modeling approach and its variants found in the literature. We estimated several multinomial logit models (random utility maximization [RUM], classical RRM, [Formula: see text]RRM, and hybrid formulations of RUM-RRM models) and explored regret scale and decision rule heterogeneities using latent class models with specific [Formula: see text] parameters. The results showed that the RRM approach outperformed its RUM counterpart in relation to model fit and suggested that it better captured the mode choice behavior of individuals in the analyzed context. We also found that accounting for heterogeneity in scale and decision rules improved the results of the models, and the specific [Formula: see text] parameters indicated that individuals displayed different regret behavior for travel time and travel cost attributes.

Patterns of riparian forest disturbance caused by tree dislodging on a subtropical river during large floods

AbstractRiparian forests contribute to the resilience and biocomplexity of floodplains but may be catastrophically impacted by large floods. Forest disturbances will expose floodplains to stripping and pulses of large wood recruitment to the floodplain and channel. The widespread uprooting of trees follows hydrodynamic loading from floodwaters and the associated moments of these forces about the tree bases. A tree will uproot when the drag moment exceeds the anchorage resistance capacity. Alternatively, trunks will rupture when the tensile stresses caused by bending exceed the tensile strength of the outer trunk fibres. The likelihood and pattern of trees dislodging during floods on a subtropical river was investigated by developing a tree stability model. The modeling framework included development of a drag moment model and testing several potential formulations for anchorage resistance. Model parameters were calibrated to data collected in experiments and from observations in aerial photographs before and after a large flood in 2011. The prediction accuracy for the adopted tree stability model was 78%. Results from design flood simulations suggest that less than a third of the forest will dislodge even during the largest floods conceivable. This remarkable stability moderates the quantity of large wood recruited from riparian forests during extreme floods, which can impact infrastructure such as bridges and culverts downstream. Low rates of wood recruitment from dislodged floodplain trees in extreme floods suggests bank erosion is the dominant source of wood recruitment in these catchments.

Dually Weighted Multi-matrix Models as a Path to Causal Gravity-Matter Systems

AbstractWe introduce a dually-weighted multi-matrix model that for a suitable choice of weights reproduce two-dimensional Causal Dynamical Triangulations (CDT) coupled to the Ising model. When Ising degrees of freedom are removed, this model corresponds to the CDT-matrix model introduced by Benedetti and Henson (Phys Lett B 678:222, 2009). We present exact as well as approximate results for the Gaussian averages of characters of a Hermitian matrix A and $$A^2$$ A 2 for a given representation and establish the present limitations that prevent us to solve the model analytically. This sets the stage for the formulation of more sophisticated matter models coupled to two-dimensional CDT as dually weighted multi-matrix models providing a complementary view to the standard simplicial formulation of CDT-matter models.

Pseudo-Eulerian model formulation for the determination of breakage frequency and daughter size distribution: Single droplet breakup experiments in turbulent flow

The study of breakage of single oil droplet in a turbulent flow is experimentally performed by means of direct visualization using high-speed imaging. A comparison of two different approaches for estimation of the breakage frequency is presented using the same set of experimental data. The first approach, estimates the breakage frequency based on the estimation of the averaged breakage time and breakage probability calculation based on single oil breakage experiments. The second approach consists in combining and superposing the different measurements into one population of droplets, to investigate the evolution of the size distribution of droplets emulating a pseudo-Eulerian representation. Using this approach, the breakage frequency can be estimated by following the evolution of the number of droplets of a particular size. We found that the pseudo-Eulerian approach is more accurate for construction of closure model for the implementation of population balance equation.

Viscoelasticty with physics-augmented neural networks: model formulation and training methods without prescribed internal variables

Viscoelasticty with physics-augmented neural networks: model formulation and training methods without prescribed internal variables

An approach for topology optimization of heat sinks for two-phase flow boiling: Part 1 – Model formulation and numerical implementation

Two-phase flow boiling in heat sinks and cold plates is attractive for various thermal management applications due to high effective heat capacity rates and high heat transfer coefficients compared to single-phase operation. In addition, multi-physics topology optimization is sought for generation of high performance thermal management components. Yet, the design of heat sinks using topology optimization has been restricted to single-phase flow physics, due to incompatibility between available two-phase flow models and traditional single-phase topology optimization approaches. Interface-capturing two-phase flow models are too computationally expensive for optimization; mixture and two-fluid models that treat the liquid and vapor phases as an interpenetrating continuum with interfacial transport phenomena captured through empirical correlations are computationally tractable for heat-sink-scale optimization. However, the penalization approaches commonly used to define the structures formed during topology optimization results in arbitrary fin and channel geometries for which a universal two-phase flow correlation is not available. To enable coupling with two-phase mixture models, this work leverages a homogenization approach to topology optimization wherein heat sink designs are represented using spatially varying microstructures with optimized dimensions. A predefined microstructure geometry is chosen for which two-phase flow correlations exist and therefore topology optimization can be performed. This work is the first to develop a topology optimization algorithm using a mixture model for simulating two-phase flow boiling to design heat sinks and cold plates. Part 1 of this study develops and implements the algorithm to investigate topology optimized heat sinks at various heat inputs, topology optimization grid sizes, and maximum vapor quality constraints. Topology optimized heat sinks designed for single-phase versus two-phase flow are compared. There are significant differences in hydraulic and thermal responses of the single-phase and two-phase designs due to high effective heat capacity rates and high heat transfer coefficients of flow boiling. A companion paper (Part 2) focuses on manufacturing, model calibration, and experimental validation of the topology optimized heat sinks under two-phase flow boiling. The algorithm demonstrated in this work extends the capabilities of topology optimization to two-phase flow physics, and thereby enables the design of various two-phase flow components such as evaporators, condensers, heat sinks, and cold plates.

A novel approach for the lifetime prediction and structural health monitoring of concrete sewer systems exposed to biogenic sulphide corrosion

A novel, combined experimental-modelling approach is presented for the estimation of the corrosion depth, load bearing capacity and lifetime of unreinforced concrete sewer pipes exposed to prolonged biogenic sulphide corrosion. The biogenic sulphide corrosion process is mimicked through two types of representative chemical experiments, namely: (i) long-term experiments performed under moderately controlled pH conditions, where dry-cast concrete cube samples are exposed to monthly refreshed sulphuric acid solutions with initial pH values of 3, 2 and 1 for a period of 12 months, and (ii) short-term experiments carried out under highly controlled pH conditions, in which dry-cast concrete disk samples are subjected to sulphuric acid solutions with almost constant pH values of 2, 1 and 0.5 for a period of two months. By applying X-ray diffraction, optical microscopy, scanning electron microscopy and energy dispersive X-ray spectroscopy analyses, insight into the micro-scale morphology and elemental composition of the corrosion profile is obtained. In addition, the corrosion front and depth characteristics are measured by conducting phenolphthalein tests and analyses of surface colour and texture of macro-scale samples. From the experimental results, the time course of the corrosion depth is calibrated with a model for sulphate attack under a constant pH level. The model formulation is combined with detailed finite element method results from the literature to predict the long-term load bearing capacity of a concrete sewer pipe. The model is subsequently generalised for sulphate corrosion under a varying pH level. When combined with the installation of pH measuring devices on the inside of sewer pipes, the current engineering model may serve as an excellent practical tool for continuously monitoring the structural health and predicting the lifetime of in-situ sewer systems subject to sulphate attack under random acidity fluctuations.

A zero‐inflated Poisson spatial model with misreporting for wildfire occurrences in southern Italian municipalities

AbstractWe propose a Poisson model for zero‐inflated spatial counts contaminated by measurement error: we accommodate the excess of zeroes in the counts, consider the possible under/over reporting of the response and account for the neighboring structure of spatial areal units. Bayesian inferences are provided by MCMC implementation through the R package NIMBLE. To evaluate the model performance, a simulation study is carried out under configurations that allow for structured and unstructured spatial random effects. The proposed model is applied to investigate the distribution of the counts of wildfire occurrences in the municipal areas of two neighboring Italian regions for the summer season 2021. Fire counts are obtained by processing MODIS satellite data, while several socio‐economic and environmental‐driven potential risk factors are also considered in the model formulation. Data from multiple sources with different spatial support are processed in order to comply with the municipal units. Results suggest the appropriateness of the approach and provide some insights on the features of wildfire occurrences.

Using a Novel, Subconjunctival, Sustained-Release Mitomycin C Formulation in a Rabbit Model of Filtration Surgery with Gel Stent Implantation.

Purpose: To investigate gel stent implantation with and without intraoperative sustained-release mitomycin C (MMC SR) in a rabbit model for gel stent implantation, and to examine aqueous humor outflow (AHO) postimplantation. Methods: Four groups of rabbits were included. Group 1 was untreated (control). Groups 2, 3, and 4 received the gel stent without MMC, with MMC solution (subconjunctival injection), and with MMC SR (subconjunctival injection), respectively. Intraocular pressure (IOP) and AHO were assessed via tonometry and indocyanine green-based angiography, respectively. The main efficacy measure was change in IOP from baseline. Results: Following gel stent implantation, Groups 2, 3, and 4 maintained ≥20% IOP reduction (response) for a median duration of 1 week, 6.5 weeks, and 30 weeks, respectively. Angiography showed normal aqueous humor drainage (Group 1) beginning at the perilimbal trabecular plexus and continuing posteriorly to episcleral outflow vessels. Following implantation, drainage occurred preferentially and directly into the subconjunctival bleb. Conclusions: Gel stent implantation with MMC SR was most effective in achieving sustained, long-term IOP reduction in the rabbit model, compared with implantation with or without MMC solution. Bleb presence and the postimplantation aqueous angiography results indicated redirection of the AHO to the subconjunctival vasculature and presumed lymphatics, suggesting efficient glaucoma filtration to lower IOP in this model. This rabbit model and aqueous angiography may help refine understanding of the mechanism of action of minimally invasive glaucoma surgeries and ultimately translate to improved surgical devices and procedures for patients with glaucoma.

An enhanced motorcycle tyre model characterised through experimental riding data

Tyre-road interaction governs motorcycle dynamics; however, the most widespread tyre model formulations must be characterised through a dedicated test bench on the lab or road, unavailable to many interested subjects. This article proposed a new tyre model formulation, conceived to be characterised through riding data using standard instrumentation. Albeit its coefficients are identified through quasi-static, uncombined slip manoeuvres, the model addresses transient, combined manoeuvres and is adaptive to road friction levels and static weight through statistical relationships from the literature. A pre-existing formulation was improved and expanded. The model’s behaviour in demanding conditions was investigated through a high-fidelity simulation environment, using a Magic Formula tyre model as the reference. Next, the characterisation procedure was carried out using actual riding data. The model’s accuracy is shown by reproducing numerically one of the manoeuvres and through comparison with the results of a bench test. The proposed model could correctly reproduce the primary behaviour of a Magic Formula model, also concerning tyre moments and steering torque. Characterising the tyre model through real riding data proved feasible, and its robust formulation limited the propagation of estimation errors. The proposed tyre model formulation and characterisation procedure should interest, among others, those subjects that lack access to a tyre testing machine.

Proposal of a practical stability probability model for cut slopes reflecting characteristics of weathering and angle of stratification

This research evaluates the stability of cut slopes, considering the effects of weathering and the angle of stratification. Incorporating both a weathering degree index and a factor of safety, we developed a novel formula to assess the temporal deterioration of cut slopes. Utilizing this formula, logistic regression was conducted to ascertain cut slope stability. We used the Hierarchical Bayesian model to refine the parameters of the logistic regression function, culminating in the formulation of a comprehensive slope stability probability prediction model. The model’s predicted stability probabilities for diverse cut slopes exhibited a compelling congruence with empirical data upon validation. Importantly, this approach provides expressway management authorities with a tool to preliminarily assess whether longstanding in-service cut slopes require intervention or stabilization measures.

Research on Predicting Welding Deformation in Automated Laser Welding Processes with an Enhanced DEWOA-BP Algorithm

Research on Predicting Welding Deformation in Automated Laser Welding Processes with an Enhanced DEWOA-BP Algorithm

Optimization of parameters and formulation of numerical model employing GRA–PCA and RSM approach for friction stir welded Ti–6Al–4V alloy joints

In this work, an endeavour was made to determine the impact of the tool’s shoulder diameter, pin profile, rotational and traverse speeds on the mechanical properties of the friction stir welded namely Ti–6Al–4 V alloy joints. A total of 21 experiments were carried out based on the central composite design (CCD) concept of response surface methodology (RSM). A quadratic regression based numerical model was formulated to ascertain the relationship amidst the parameters of FSW process and the mechanical properties of the fabricated Ti alloy joints. Analysis of variance (ANOVA) was employed to confirm the importance of parameters and their interactive impacts. Optimized process parameter combinations were ascertained by grey relation based analysis (GRA) was coupled together with principal component analysis (PCA), a hybrid based approach. Single score of GRG based response was determined and GRG scores were ranked for all experiments. 1st rank was attained by the experiment no. 20 possessing a GRG score of 2.9989. Optimized values of 25 mm shoulder diameter having a taper cylindrical pin geometry employed at a tool traverse speed of 40 mm min−1, rotational speed of 1400 rpm resulted in the generation of flaw free Ti alloy joint possessing a largest tensile strength of 809.8 MPa, yield strength of 778.7 MPa and percentage of elongation of 6.9%. SEM based fractography of Ti alloy joint specimens announced that taper cylindrical pin geometry along with 25 m shoulder diameter of employed tool have an inevitable part in generating frictional heat in ideal volumes and a perfect stirring action during FSW process.

Characterisation and damage modelling of oxide/oxide composites considering temperature dependence

Continuous fibre reinforced ceramic matrix composites (CMCs) are increasingly being employed in safety critical applications. As a result, their use in these applications requires the adoption of appropriate design methodologies that are able to consider their complex non-linear mechanical behaviour. In this paper, a simple but robust formulation for continuum damage model, thermodynamically consistent and written under plane stress condition, is proposed for a laminated 2D woven composite material. This model is implemented via the Classical Laminate Theory (CLT) extended to non-linear behaviour to predict the behaviour of different stacking sequences. In-plane tensile tests were performed on an oxide/oxide composite up to 1000 °C to fully identify the model. The procedure is described and used on tests at room temperature before being extended higher temperature tests. Finally, the law and its coupling with the CLT are validated by means of tests on quasi-isotropic and cross-ply laminates at different temperatures.