scholarly journals Dynamics of a Homogeneous and Isotropic Space in Pure Cubic f(R) Gravity

Physics ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 379-385
Author(s):  
Polina Petriakova
Keyword(s):  
Slow Growth ◽  
Initial Conditions ◽  
Ricci Scalar ◽  
Gravity Models ◽  
Model Parameters ◽  
Inflationary Scenario ◽  
Extended Gravity ◽  
Isotropic Space ◽  
Walker Metric

The possible ways of dynamics of a homogeneous and isotropic space described by the Friedmann–Lemaitre–Robertson–Walker metric in the framework of cubic in the Ricci scalar f(R) gravity in the absence of matter are considered. This paper points towards an effective method for limiting the parameters of extended gravity models. A method for f(R)-gravity models, based on the metric dynamics of various model parameters in the simplest example is proposed. The influence of the parameters and initial conditions on further dynamics are discussed. The parameters can be limited by (i) slow growth of space, (ii) instability and (iii) divergence with the inflationary scenario.

Kinetic Model of Adiabatic Temperature Rise of Mass Concrete

2021 ◽  
Vol 13 (5) ◽  
pp. 771-780
Author(s):  
Shou-Kai Chen ◽  
Bo-Wen Xu
Keyword(s):  
Temperature Field ◽  
Temperature Rise ◽  
Initial Conditions ◽  
Dynamic Change ◽  
Adiabatic Temperature ◽  
Model Parameters ◽  
Hydration Reaction ◽  
Mass Concrete ◽  
Adiabatic Temperature Rise ◽  
Proposed Model

The adiabatic temperature rise model of mass concrete is very important for temperature field simulation, same to crack resistance capacity and temperature control of concrete structures. In this research, a thermal kinetics analysis was performed to study the exothermic hydration reaction process of concrete, and an adiabatic temperature rise model was proposed. The proposed model considers influencing factors, including initial temperature, temperature history, activation energy, and the completion degree of adiabatic temperature rise and is theoretically mature and definitive in physical meaning. It was performed on different initial temperatures for adiabatic temperature rise test; the data were employed in a regression analysis of the model parameters and initial conditions. The same function was applied to describe the dynamic change of the adiabatic temperature rise rates for different initial temperatures and different temperature changing processes and subsequently employed in a finite element analysis of the concrete temperature field. The test results indicated that the proposed model adequately fits the data of the adiabatic temperature rise test, which included different initial temperatures, and accurately predicts the changing pattern of adiabatic temperature rise of concrete at different initial temperatures. Compared with the results using the traditional age-based adiabatic temperature rise model, the results of a calculation example revealed that the simulated calculation results using the proposed model can accurately reflect the temperature change pattern of concrete in heat dissipation conditions.

scholarly journals Elasto-plastic-adhesive DEM model for simulating hillslope debris flows: cross comparison with field experiments

2018 ◽  
Author(s):  
Adel Albaba ◽  
Massimiliano Schwarz ◽  
Corinna Wendeler ◽  
Bernard Loup ◽  
Luuk Dorren
Keyword(s):  
Numerical Model ◽  
Flow Velocity ◽  
Debris Flows ◽  
Field Experiments ◽  
Initial Conditions ◽  
Experimental Tests ◽  
Height Velocity ◽  
Model Parameters ◽  
Fine Content ◽  
Adhesive Model

Abstract. This paper presents a Discrete Element-based elasto-plastic-adhesive model which is adapted and tested for producing hillslope debris flows. The numerical model produces three phases of particle contacts: elastic, plastic and adhesion. The model capabilities of simulating different types of cohesive granular flows were tested with different ranges of flow velocities and heights. The basic model parameters, being the basal friction (ϕb) and normal restitution coefficient (ϵn), were calibrated using field experiments of hillslope debris flows impacting two sensors. Simulations of 50 m3 of material were carried out on a channelized surface that is 41 m long and 8 m wide. The calibration process was based on measurements of flow height, flow velocity and the pressure applied to a sensor. Results of the numerical model matched well those of the field data in terms of pressure and flow velocity while less agreement was observed for flow height. Those discrepancies in results were due in part to the deposition of material in the field test which are not reproducible in the model. A parametric study was conducted to further investigate that effect of model parameters and inclination angle on flow height, velocity and pressure. Results of best-fit model parameters against selected experimental tests suggested that a link might exist between the model parameters ϕb and ϵn and the initial conditions of the tested granular material (bulk density and water and fine contents). The good performance of the model against the full-scale field experiments encourages further investigation by conducting lab-scale experiments with detailed variation of water and fine content to better understand their link to the model's parameters.

scholarly journals Hamiltonian formalism for nonlocal gravity models

2022 ◽  
Author(s):  
Pawan Joshi ◽  
Utkarsh Kumar ◽  
Sukanta Panda
Keyword(s):  
Ricci Tensor ◽  
Degrees Of Freedom ◽  
Hamiltonian Formalism ◽  
Riemann Tensor ◽  
Ricci Scalar ◽  
Gravity Models ◽  
Lagrangian Formalism ◽  
Acceleration Of The Universe ◽  
Nonlocal Action ◽  
The Universe

Nonlocal gravity models are constructed to explain the current acceleration of the universe. These models are inspired by the infrared correction appearing in Einstein–Hilbert action. Here, we develop the Hamiltonian formalism of a nonlocal model by considering only terms to quadratic order in Riemann tensor, Ricci tensor and Ricci scalar. We show how to count degrees of freedom using Hamiltonian formalism including Ricci tensor and Ricci scalar terms. In this model, we have also worked out with a choice of a nonlocal action which has only two degrees of freedom equivalent to GR. Finally, we find the existence of additional constraints in Hamiltonian required to remove the ghosts in our full action. We also compare our results with that of obtained using Lagrangian formalism.

scholarly journals Disease control as an optimization problem

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257958
Author(s):  
Miguel Navascués ◽  
Costantino Budroni ◽  
Yelena Guryanova
Keyword(s):  
Disease Control ◽  
Stochastic Models ◽  
Optimization Problem ◽  
Initial Conditions ◽  
Optimization Theory ◽  
Model Parameters ◽  
Grid Search ◽  
Brute Force ◽  
Time Required ◽  
Policy Optimization

In the context of epidemiology, policies for disease control are often devised through a mixture of intuition and brute-force, whereby the set of logically conceivable policies is narrowed down to a small family described by a few parameters, following which linearization or grid search is used to identify the optimal policy within the set. This scheme runs the risk of leaving out more complex (and perhaps counter-intuitive) policies for disease control that could tackle the disease more efficiently. In this article, we use techniques from convex optimization theory and machine learning to conduct optimizations over disease policies described by hundreds of parameters. In contrast to past approaches for policy optimization based on control theory, our framework can deal with arbitrary uncertainties on the initial conditions and model parameters controlling the spread of the disease, and stochastic models. In addition, our methods allow for optimization over policies which remain constant over weekly periods, specified by either continuous or discrete (e.g.: lockdown on/off) government measures. We illustrate our approach by minimizing the total time required to eradicate COVID-19 within the Susceptible-Exposed-Infected-Recovered (SEIR) model proposed by Kissler et al. (March, 2020).

scholarly journals Parameter inference in dynamical systems with co-dimension 1 bifurcations

2019 ◽  
Vol 6 (10) ◽  
pp. 190747
Author(s):  
Elisabeth Roesch ◽  
Michael P. H. Stumpf
Keyword(s):  
Dynamical Systems ◽  
Kinetic Parameters ◽  
Initial Conditions ◽  
Model Parameters ◽  
Biological Processes ◽  
Parameter Inference ◽  
Qualitative Dynamics ◽  
Small Change ◽  
Bifurcation Behaviour ◽  
Practical Implications

Dynamical systems with intricate behaviour are all-pervasive in biology. Many of the most interesting biological processes indicate the presence of bifurcations, i.e. phenomena where a small change in a system parameter causes qualitatively different behaviour. Bifurcation theory has become a rich field of research in its own right and evaluating the bifurcation behaviour of a given dynamical system can be challenging. An even greater challenge, however, is to learn the bifurcation structure of dynamical systems from data, where the precise model structure is not known. Here, we study one aspects of this problem: the practical implications that the presence of bifurcations has on our ability to infer model parameters and initial conditions from empirical data; we focus on the canonical co-dimension 1 bifurcations and provide a comprehensive analysis of how dynamics, and our ability to infer kinetic parameters are linked. The picture thus emerging is surprisingly nuanced and suggests that identification of the qualitative dynamics—the bifurcation diagram—should precede any attempt at inferring kinetic parameters.

scholarly journals Bounds on higher derivative f(R,□R,T) models from energy conditions

2019 ◽  
Vol 34 (11) ◽  
pp. 1950082 ◽  
Author(s):  
M. Ilyas ◽  
Z. Yousaf ◽  
M. Z. Bhatti
Keyword(s):  
Perfect Fluid ◽  
Energy Momentum Tensor ◽  
Momentum Tensor ◽  
Ricci Scalar ◽  
Energy Conditions ◽  
Higher Derivative ◽  
Derivative Formula ◽  
Cosmological Solutions ◽  
Walker Metric ◽  
Cosmic Parameters

This paper studies the viable regions of some cosmic models in a higher derivative [Formula: see text] theory with the help of energy conditions (where [Formula: see text], [Formula: see text] and [Formula: see text] are the Ricci scalar, d’Alembert’s operator and trace of energy–momentum tensor, respectively). For this purpose, we assume a flat Friedmann–Lemaître–Robertson–Walker metric which is assumed to be filled with perfect fluid configurations. We take two distinct realistic models that might be helpful to explore stable regimes of cosmological solutions. After taking some numerical values of cosmic parameters, like crackle, snap, jerk (etc.) as well as viable constraints from energy conditions, the viable zones for the under observed [Formula: see text] models are examined.

scholarly journals Estimation of Coastal Currents Using a Soft Computing Method: A Case Study in Galway Bay, Ireland

2019 ◽  
Vol 7 (5) ◽  
pp. 157 ◽  
Author(s):  
Lei Ren ◽  
Jianming Miao ◽  
Yulong Li ◽  
Xiangxin Luo ◽  
Junxue Li ◽  
...  
Keyword(s):  
Numerical Model ◽  
Soft Computing ◽  
Initial Conditions ◽  
Numerical Models ◽  
Surface Velocity ◽  
Training Dataset ◽  
Model Parameters ◽  
Surface Currents ◽  
Coastal Currents ◽  
Computing Models

In order to obtain forward states of coastal currents, numerical models are a commonly used approach. However, the accurate definition of initial conditions, boundary conditions and other model parameters are challenging. In this paper, a novel application of a soft computing approach, random forests (RF), was adopted to estimate surface currents for three analysis points in Galway Bay, Ireland. Outputs from a numerical model and observations from a high frequency radar system were used as inputs to develop soft computing models. The input variable structure of soft computing models was examined in detail through sensitivity experiments. High correlation of surface currents between predictions from RF models and radar data indicated that the RF algorithm is a most promising means of generating satisfactory surface currents over a long prediction period. Furthermore, training dataset lengths were examined to investigate influences on prediction accuracy. The largest improvement for zonal and meridional surface velocity components over a 59-h forecasting period was 14% and 37% of root mean square error (RMSE) values separately. Results indicate that the combination of RF models with a numerical model can significantly improve forecasting accuracy for surface currents, especially for the meridional surface velocity component.

Networks of export markets and export market diversification

2020 ◽  
Author(s):  
Qi Guo ◽  
Shengjun Zhu ◽  
Ron Boschma
Keyword(s):  
Developed Countries ◽  
Gravity Models ◽  
Export Market ◽  
Gravity Effect ◽  
Export Markets ◽  
Policy Makers ◽  
Extended Gravity ◽  
Gravity Effects ◽  
Better Than ◽  
Developing And Developed Countries

Abstract In the era of globalization, policy makers in both developing and developed countries have sought to expand their export destinations, with the expectation that export market diversification can boost export upgrading and economic development. Although extant literature has confirmed that exporters search for new markets in two distinct ways: direct search underpinned by the gravity effect and remote search driven by the extended gravity effect, it has not advanced very far due to the lack of adequate measures of those effects. This article presents a technique that uses available export data to develop measures of those two effects that capture a larger range of factors and thus allow us to more easily predict export market diversification. Our new indicator also simplifies the prediction by combining gravity and extended gravity effects. Empirical results show that the explanatory and predictive power of our new method is better than that of the traditional one based on gravity and extended gravity models.

scholarly journals Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles

2019 ◽  
Vol 485 (2) ◽  
pp. 2806-2824 ◽  
Author(s):  
Linda Blot ◽  
Martin Crocce ◽  
Emiliano Sefusatti ◽  
Martha Lippich ◽  
Ariel G Sánchez ◽  
...  
Keyword(s):  
Growth Rate ◽  
Distribution Function ◽  
Power Spectrum ◽  
Probability Distribution Function ◽  
Initial Conditions ◽  
Covariance Matrices ◽  
Full Density ◽  
Model Parameters ◽  
Approximate Methods ◽  
Parameter Constraints

ABSTRACT We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix. We propagate the differences in covariances into parameter constraints related to growth rate of structure, Alcock–Paczynski distortions, and biasing. We consider seven methods in three broad categories: algorithms that solve for halo density evolution deterministically using Lagrangian trajectories (ICE–COLA, pinocchio, and peakpatch), methods that rely on halo assignment schemes on to dark matter overdensities calibrated with a target N-body run (halogen, patchy), and two standard assumptions about the full density probability distribution function (Gaussian and lognormal). We benchmark their performance against a set of three hundred N-body simulations, running similar sets of approximate simulations with matched initial conditions, for each method. We find that most methods reproduce the monopole to within $5{{\ \rm per\ cent}}$, while residuals for the quadrupole are sometimes larger and scale dependent. The variance of the multipoles is typically reproduced within $10{{\ \rm per\ cent}}$. Overall, we find that covariances built from approximate simulations yield errors on model parameters within $10{{\ \rm per\ cent}}$ of those from the N-body-based covariance.

Radial heat and water transport across the airway wall

1990 ◽  
Vol 69 (1) ◽  
pp. 222-231 ◽  
Author(s):  
C. L. Tsai ◽  
G. M. Saidel ◽  
E. R. McFadden ◽  
J. M. Fouke
Keyword(s):  
Initial Conditions ◽  
Variable Parameter ◽  
Blood Perfusion ◽  
Breath Hold ◽  
Model Parameters ◽  
Airway Wall ◽  
Healthy Human ◽  
Asthmatic Patients ◽  
Order Of Magnitude ◽  
The Difference

The thermal profiles in the airways of healthy human volunteers and patients with asthma differ after cessation of hyperpnea. The asthmatic patients rewarm their airways more rapidly. To identify thermal properties and processes that could account for the difference between these populations, we developed a model describing the radial transport of heat and water across the trachea. A distinctive feature of the model is a variable parameter describing blood supply to the mucosal and submucosal layers. Simulations performed with the model are initiated by a breath-hold maneuver and are propagative in time. Blood perfusion rates in the airway wall, the thickness of the layer of airway surface liquid, and the mucosa-submucosa thickness, all thought to be more pronounced in asthmatic patients, were varied by changing model parameters and initial conditions. Increasing the thickness of the liquid layer by more than an order of magnitude had little effect on the temperature or water content in the airway lumen. Doubling the blood flow to the mucosa-submucosa resulted in a slight increase in airway temperature. When this effect was coupled, however, with an increase in the thickness of the mucosa-submucosa layer, the increase in temperature was more pronounced. Because the bronchial circulation is the major source of heat to the airway, these results indicate that differences in airway wall thickness coupled with differences in the magnitude or responsiveness of the bronchial microcirculation could account for the differences in intra-airway temperature between the two populations.

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